bluuebunny/crossref_metadata_2025 huggingface dataset:
Study on afterbody-effects of multi-stage separation at high-speed
Authors: Zheng Yongqian , Jia Hongyin , Cui Pengcheng , Li Huan , Wu Xiaojun
Published: December 2021

The stage separation of high-speed vehicle is complicated at high dynamic pressure, usually accompanied by strong shock and vortex interaction. There exists a strong interaction between first stage and second stage, which called “afterbody-effects”. The aerodynamic mechanism of “afterbody-effects” is studied in this paper based on numerical simulation. The aerodynamic characteristics of a simplified three-dimensional projectile model at different distances between stages at 0° angle of attack is researched with structural mesh. The results show that the vortexes of stages have a significant impact on the aerodynamic characteristics of different stages, As the distance between stages increases, the drag coefficient of the first stage increases, and the drag coefficient of the second stage increases first and then decreases.
Computer Intelligent Numerical Simulation of TIG Welding Using Platy Tungsten Electrode
Authors: Zhang Jianhua , Huang Zicheng , Xie Yulun , Zhao Qiming , Wang Ketao
Published: December 2021

In order to reveal the law of arc plasma flow and heat transfer in the process of flat tungsten electrode TIG welding as auxiliary heat source for hardfacing of cast iron surface. According to the free burning TIG arc using platy tungsten electrode, A three dimensional (3D) model for tungsten inert gas welding using platy tungsten electrode has been developed. The whole region of platy tungsten TIG arc, namely, platy tungsten cathode, arc plasma and anode surface is treated in a unified numerical model. By using fluent software to do the second development of equations source and solve these equations, the distribution of temperature, velocity and current density are obtained. The simulation results show that the current of flat tungsten electrode is more dispersed, and the heat generation of arc is more dispersed, which leads to the decrease of arc temperature; The current density on the cathode is much higher than that on the anode.
Comparison and adaptability evaluation of formation pressure calculation methods and computer simulation in Jingbian gas field
Authors: Liu Haifeng , Wang Hua , He Lei , Zhang Fang , Fu Yu , Zhang Yuanjie
Published: December 2021

In the process of oilfield development, formation pressure is an essential parameter for evaluating oilfield development effect, calculating dynamic geological reserves, conducting daily dynamic analysis of oil and water Wells and predicting oilfield performance. The pressure recovery time of conventional gas well after shut-in is very long, and it is difficult to effectively carry out targeted implementation due to the influence of gas field external supply task. In this paper, based on the actual data of Jingbian gas field, through the comparison of several calculation methods of formation pressure, the best method to calculate formation pressure is comprehensively screened out. The results show that: ①For a single method, the accuracy of the method from high to low is the well head casing pressure conversion method, the pressure drop curve method, the binomial productivity equation method, and the quasi-steady state mathematical model method.②The absolute error of multi-method comprehensive calculation method is 0.9MPa, which is far less than the average absolute error directly calculated by one method. The multi-method comprehensive calculation method is reliable when applied to the formation pressure evaluation of typical gas Wells in Jingbian gas field, which lacks data.
Study on Smart Numerical Simulation Mechanism in Complex Reservoir Using Embedded Discrete Fracture Model
Authors: Wang Yong , Jiang Hanqiao , Li Junjian , Lv Chunhua , Liu Jianbo , Ma Xiaobin
Published: December 2021

The embedded discrete fracture model (EDFM) method is used to study the mechanism model of the reservoir with a complex fracture system, and the sensitivity analysis of the development effect is carried out. The results show that: 1) the EDFM method can directly characterize the fracture morphology and fracture attributes in the reservoir; 2) Through comparative analysis of reservoir type, capillary force, and fracture development degree, it is found that different reservoir types have great differences in development effect, fracture opening has little influence on the reservoir, capillary force and fracture density have a great influence on the reservoir development effect, and with the increase of fracture density, the reservoir development effect increases significantly.
Numerical simulation on the leakage and diffusion of the natural gas of the underground pipeline in the soil
Authors: Hu Meijuan , Li He , Chen Li , Xie Ping , Zhang Zheju , Yang Ming , Wu Mingze , Zhang Qingming
Published: December 2021

For the transportation pipeline with the diameter 1.219 m and the internal pressure 3-12 MPa, the leakage and diffusion of the natural gas of the pipeline in the soil was studied by numerical simulation. First, the finite model containing both pipeline and soil was established, and the porous media was used to simulate the real soil environment. And, the leakage amount of the natural gas was calculated at the cases with different porosities, the pressures inside the pipeline and the diameters of leakage port. Based on the classical theoretical leakage model of small hole in the air and simulation results analysis, the formula of the leakage amount was modified by the soil coefficient α to be suitable for soil environment. Then, the variation trends of the diffusion concentration of methane along different directions in the soil were analyzed by simulation, the influences of internal pressure of pipeline, the diameter of leakage and the porosity of soil were also discussed. Besides, the relationship of the safety distance with time was obtained.
Pedestrian Re-identity Based on ResNet Lightweight Network
Authors: Li Xingxing , Duan Chao , Yin Panpan , Wang Ningxing
Published: December 2021

With the development of deep learning technology, pedestrian re-identity technology has been widely used in multi-target tracking and cross mirror tracking tasks. In this paper, the classical deep learning ResNet18 network is used for pedestrian re-identity tasks. The advantage of the network is that it can easily realize lightweight deployment. In addition, the labeled smooth cross entropy loss function and migration learning technology are used in the process of training the network, which can realize the accuracy of map 67.8 on the Market1501 data set while lightening the network, and promote the engineering landing of pedestrian re-identity network.
A Corner Detection Algorithm Based on Regional Center of Mass in Imaging through Water Surface
Authors: Mai Changli , Jian Bijian , Ling Yongfa
Published: December 2021

Structural light active imaging can obtain more information about the target scene, which is widely used in image registration,3D reconstruction of objects and motion detection. Due to the random fluctuation of water surface and complex underwater environment, the current corner detection algorithm has the problems of false detection and uncertainty. This paper proposes a corner detection algorithm based on the region centroid extraction. Experimental results show that, compared with the traditional detection algorithms, the proposed algorithm can extract the feature point information of the image in real time, which is of great significance to the subsequent image restoration.
Research on Network Platform System Under Mobile Internet and Smart Electronic Commerce Big Data Digitization
Authors: Li Bin , Zhou Zhisheng
Published: December 2021

Based on the intelligent big data method and the cross-border e-commerce logistics service system as the research object, the paper constructs a cross-border e-commerce logistics service system based on mobile Internet. According to the user’s preference, the products matching the user’s preference are obtained through association rule mining, and recommended to the user. The research shows that the digital cross-border e-commerce platform system involved in the paper has good compatibility, and the user preference recommendation algorithm involved in the paper has high accuracy, which meets the needs of users.
Multi-Modal Remote Sensing Image Matching Method Based on Deep Learning Technology
Authors: Han Hao , Li Canhai , Qiu Xiaofeng
Published: December 2021

Remote sensing is a scientific technology that uses sensors to detect the reflection, radiation or scattering of electromagnetic wave signals from ground objects in a non-contact and long-distance manner. The images are classified by the extracted image feature information Recognition is a further study of obtaining target feature information, which is of great significance to urban planning, disaster monitoring, and ecological environment evaluation. The image matching framework proposed in this paper matches the depth feature maps, and reversely pushes the geometric deformation between the depth feature maps to between the original reference image and the target image, and eliminates the geometric deformation between the original images. Finally, through feature extraction of the corrected image, the extracted local feature image blocks are input into the trained multi-modal feature matching network to complete the entire matching process. Experiments show that the negative sample set construction strategy that takes into account the sample distance proposed in this experiment can effectively deal with the problem of neighboring point interference in RSI matching, and improve the matching performance of the network model.
The Parameter Estimation of Double Exponential Pulse Based on a Least Infinity Norm Fitting Method
Authors: Shi Yuewu , Wang Wei , Zhu Zhizhen , Nie Xin
Published: December 2021

This paper presents an estimation method of double exponential pulse (DEP) between the physical parameters rise time (t
r), full width at half maximum amplitude (t
FWHM) and the mathematical parameters α, β. A newly fitting method based on the least infinity norm criterion is proposed to deal with the estimation problem of DEP. The calculation process and equation of parameters of this method is proposed based on an m-th-order polynomial fitting model. This estimation method is compared with the least square method by the same data and fitting function. The results show that the maximum estimation error of parameters of double exponential pulse obtained by the least infinity norm method is 1.5 %.
Research on Fan Operation Evaluation and Error State Judgment Relying on Improved Neural Network and Intelligent Computing
Authors: Liu Xueyi , Dong Junhao , Tu Guangyu
Published: December 2021

Fan, as the most commonly used mechanical equipment, is widely used. In order to solve the problem of fan bearing fault diagnosis, this paper analyzes the main factors affecting fan spindle speed and power generation in operation. The input and output parameters of the performance prediction model are determined. The performance prediction model of wind turbine is established by using generalized regression neural network, and the smoothing factor of GRNN is optimized by comparing the prediction accuracy of the model. Based on this model, the sliding data window method is used to calculate the residual evaluation index of wind turbine speed and power in real time. When the evaluation index continuously exceeds the pre-set threshold, the abnormal state of wind turbine can be judged. In order to obtain wind turbine blades with better aerodynamic performance, a blade aerodynamic performance optimization method based on quantum heredity is proposed. The B é zier curve control point is used as the design variable to represent the continuous chord length and torsion angle distribution of the blade, the blade shape optimization model aiming at the maximum power is established, and the quantum genetic algorithm is used to optimize the chord length and torsion angle of the blade under different constraints. The optimization results of quantum genetic algorithm and classical genetic algorithm are compared and analyzed. Under the same parameters and boundary conditions, the proposed blade aerodynamic optimization method based on quantum genetic optimization is better than the classical genetic optimization method, and can obtain better blade aerodynamic shape and higher wind energy capture efficiency. This method makes up for the shortcomings of traditional fault diagnosis methods, improves the recognition rate of fault types and the accuracy of fault diagnosis, and the diagnosis effect is good.
Research on the Application of Artificial Intelligence Machine Learning Technology in Improving the Accuracy of Engineering Image Processing
Authors: Liu Xiaowen , Lei Juncheng
Published: December 2021

Image recognition technology mainly includes image feature extraction and classification recognition. Feature extraction is the key link, which determines whether the recognition performance is good or bad. Deep learning builds a model by building a hierarchical model structure like the human brain, extracting features layer by layer from the data. Applying deep learning to image recognition can further improve the accuracy of image recognition. Based on the idea of clustering, this article establishes a multi-mix Gaussian model for engineering image information in RGB color space through offline learning and expectation-maximization algorithms, to obtain a multi-mix cluster representation of engineering image information. Then use the sparse Gaussian machine learning model on the YCrCb color space to quickly learn the distribution of engineering images online, and design an engineering image recognizer based on multi-color space information.
Research on underwater image enhancement algorithm based on improved DCP
Authors: Wu Zhe , Han Jianfgui , Cao Chenghao
Published: December 2021

All for underwater images, there are some drawbacks, such as low definition, serious color bias, dark brightness, etc. On the basis of in-depth analysis of common image enhancement algorithms, This paper uses the improved dark channel priority algorithm to enhance the underwater image, Improving the contrast of underwater images and color correction of underwater images. Color correction is added based on dark channel prior algorithm; Make the image look more even, higher contrast, more acceptable. The improved algorithm model has a higher transfer rate; PSNR is more balanced and has better contrast to meet the requirements of underwater image observation.
Comparison and intelligent analysis of NTRU and ETRU signature algorithms for public key digital signature
Authors: Zhu Zifeng , Tian Fei
Published: December 2021

Three American mathematicians made the NTRU public-key cryptosystem in 1996, it has a fast speed, small footprint, and also it is easy to produce key advantages. The NTRU signature algorithm is based on an integer base, the performance of the signature algorithm will change when the integer base becomes other bases. Based on the definition of “high-dimensional density” of lattice signatures, this paper chooses the ETRU signature algorithm formed by replacing the integer base with the Eisenstein integer base as a representative, and analyzes and compares the performance, security of NTRU and ETRU signature algorithms, SVP and CVP and other difficult issues, the speed of signature and verification, and the consumption of resources occupied by the algorithm.
Research on Key Technologies of FDM 3D Printing Based on Computer Assisted 3D Reconstruction
Authors: Gao Zihang , Zhao Nannan
Published: December 2021

As a core technology in the field of high and new tech manufacturing,3D printing occupies an important position in the production process of aviation, shipbuilding, and automobiles. With the rapid development of 3D printing basic theory in recent years, how to further improve product accuracy, quality and modeling efficiency has become the current research focus in this field. Firstly, we conducted further research on the key technologies of FDM 3D printer, and combining 3D reconstruction technology with pretreatment technology. Secondly, we constructed and optimized the corresponding model layered slice and filling path planning algorithm. Thirdly, we designed a 3D suitable for rapid prototyping products printing control system. The research can provide an effective experience for the application of 3D printing technologies.
Material selection and optimization scheme of Seabed Data Center
Authors: Xu Kechao , Gu Xiaotong , Jiao Shangyi , Ren Boyang , Tian Zhengyu , Fan Yutong , An Yan , Lin Yuhan , Wang Hanxiao
Published: December 2021

With the advent of the era of big data, the number of global data centers increases rapidly. But at the same time, it also brings some conflicts of resources. Because electronics use a lot of energy to dissipate heat. In this paper, In order to select the most suitable materials for Seabed Data Center, we established a material screening model based on weight and entropy weight method, and finally obtained the optimal design scheme.
Path planning method of smart mobile robot based on genetic algorithm
Authors: Fu Yan
Published: December 2021

Robot path planning is an important topic in the field of robots. Unlike previous methods which consider the smoothness of paths in the process of genetic algorithm, this paper presents a new method of robot path planning that separates the genetic algorithm process from the path smoothing process. First, a simple genetic algorithm with variable length encoding is designed to generate a better polyline path, and then a new type of spiral with shape parameters is introduced to smooth it to smooth a larger corner. Throughout the path planning process, only obstacle coordinates are input to select parameters adaptively to generate the robot’s walking path. The simulation results show that separating the genetic algorithm process from the path smoothing process reduces the complexity of the genetic algorithm itself, so the designed smoothing operation not only improves the smoothness of the path, but also reduces the length of the path.
Application of Big Data in Security Precaution by Network Technology and Video Image Database
Authors: Yao Yougang , Zou Linling
Published: December 2021

The security industry is generated by the needs of modern public security precaution. With the popularization of hardware and network technology, the amount of data in the field of security increases rapidly. Under such a condition, big data technology in the field of security arises. This paper discusses the current situation of the security industry, and discusses the related security problems in the application process of big data in the field of public security precaution. Taking the video image database application platform as an example, combined with the national standards 28181, 25724, 35114, this paper discusses the data security problems involved in the process of data acquisition and data transmission. Based on the Kerberos authentication mechanism of Hadoop, this paper introduces the big data security and access control technology, and forms relevant solutions in the whole process of data acquisition, data transmission and data access.
Research on Vehicle Scheduling of Cross-Regional Collection Using Hierarchical Agglomerative Clustering and Algorithm Optimization
Authors: Wei Zeming , Liang Chufeng , Tang Hua
Published: December 2021

At present, municipal solid waste (MSW) collection is based on the divide-regional operation mode, which has many deficiencies. This paper proposes a cross-regional operation scheme. Through the initial assignment, type labeling, and reassignment, and use the improved hierarchical agglomerative clustering (IHAC) algorithm and garbage collecting route optimization (GCRO) algorithm to realize intelligent allocation of garbage and scheduling route planning of collection vehicles. The experimental results demonstrate the proposed scheme improves the utilization of vehicle resources, reduces the operating cost, realizes the balanced allocation of garbage, and solves the problems caused by limitations of the original operation scheme, which demonstrates the feasibility and effectiveness of the cross-regional operation.
ERDBNet: Enhanced Residual Dense Block Net --A New Net to Rich ESRGAN Image Details
Authors: Gao Lizhuo
Published: December 2021

Super resolution is applied in many digital image fields. In many cases, only a set of low-resolution images can be obtained, but the image needs a higher resolution, and then SR needs to be applied. SR technology has undergone years of development. Among them, SRGAN is the key work to introduce GAN into the SR field, which can truly restore a large number of details on the basis of low-pixel pictures. ESRGAN is a further improvement on SRGAN. By removing the BN layer in SRGAN, the effect of artifacts in SRGAN is eliminated. However, there is still a problem that the restoration of information on small and medium scales is not accurate enough. The proposed ERDBNet improve the model on the basis of ESRGAN, and use the ERDB block to replace the original RRDB block. The new structure uses a three-layer dense block to replace the original dense block, and a residual structure of the starting point is added to each dense block. The pre-trained network can reach a PSNR of 30.425 after 200k iterations, and the minimum floating PSNR is only 30.213. Compared with the original structure, it is more stable and performs better in the detail recovery of many low-pixel images.
A New Knowledge Distillation Method for Object Detection Based on EMD
Authors: Liang Zhihao
Published: December 2021

As a common method of model compression, the knowledge distillation method can distill the knowledge from the complex large model with strong learning ability to student small model with weak learning ability in the training process, to improve the accuracy and performance of the small model. At present, there has been much knowledge distillation methods specially designed for object detection and achieved good results. However, almost all methods failed to solve the problem of performance degradation caused by the high noise in the current detection framework. In this study, we proposed a feature automatic weight learning method based on EMD to solve these two problems. That is, the EMD method is used to process the space vector to reduce the impact of negative transfer and noise as much as possible, and at the same time, the weights are allocated adaptive to reduce student model’s learning from the teacher model with poor performance and make students more inclined to learn from good teachers. The loss (EMD Loss) was redesigned, and the HEAD was improved to fit our approach. We have carried out different comprehensive performance tests on multiple datasets, including PASCAL, KITTI, ILSVRC, and MS-COCO, and obtained encouraging results, which can not only be applied to the one-stage and two-stage detectors but also can be used radiatively with some other methods.
UAV formation obstacle avoidance control method based on artificial potential field and consistency
Authors: Wei Boyu
Published: December 2021

As a typical multi-agent formation, UAV formation is playing an increasingly powerful role in the civilian and military fields. Obstacle avoidance, as an important technology in controlling formation, determines the application prospects of UAVs. This paper studies the time-varying formation of UAVs with interactive topology to avoid obstacles, aiming to improve the ability of UAV formations to deal with complex environments while traveling. Firstly, a repulsive force field is reasonably introduced based on the existing control scheme, and an improved distributed time-varying formation control scheme based on artificial potential field is proposed. Then combined with the basic idea of model predictive control, an obstacle avoidance strategy in which UAV obstacle avoidance and formation shaping are carried out simultaneously is proposed. Finally, a time-varying formation simulation experiment containing four UAVs was carried out to verify the validity of the results.
Application of Information Technology and Artificial Intelligence in Computer Assisted Costume Design
Authors: Jing Fei
Published: December 2021

Costume Design and information technology can be used as a collision between fashion and information technology. As a course that combines artistry and technology, costume and costume design have higher and higher teaching requirements for technical environment on the basis of art display, and attaches equal importance to students’ innovative thinking and practical ability in the teaching process. Compared with traditional teacher-centered, only attach importance to knowledge and neglecting the students’ ability development of teaching mode can meet the demand for professional talents, and reasonable use of the information technology as the guide, give full play to student’s main body role, respect students’ individual differences, according to the diverse learning needs of students, In order to better train out of the garment industry needs high-quality talents.
Research on Computer Numerical Simulation System and Information Digitization Using Competition and Confrontation Network
Authors: Wang Liangyu
Published: December 2021

The competitive characteristics and training requirements of each event group that can dominate the category of difficult and beautiful performance of technical warfare have multi-dimensional similarities. From the aspects of competition characteristics, determinants of sports performance, structural characteristics of competitive ability, and training requirements, it analyses the antagonistic event group that can dominate the class of technical warfare, and puts forward corresponding training requirements. The development of computer simulation technology of human body system will undoubtedly bring unprecedented opportunities to sports training and sports science research, and is changing the mode of sports science research and training. The article uses the confrontation network to conduct competitive sports simulation training, which can carry out the scientific selection of competitive sports athletes, improve the overall training level and effect of competitive sports athletes, optimize, and innovate the technical movement and movement combination arrangement of competitive sports, and can truly construct competitive sports training scenes.
Path Planning Algorithm for Mobile Robot Based on Improved Ant Colony Algorithm
Authors: Li Yanyun , Liu Fenggang
Published: December 2021

Due to the influence of full traversal environment, the path length obtained by existing methods is too long. In order to improve the performance of path planning and obtain the optimal path, a full traversal path planning method for omnidirectional mobile robots based on ant colony algorithm is proposed. On the basis of the topology modeling schematic diagram, according to the position information of the mobile robot in the original coordinate system, a new environment model is established by using the Angle transformation. Considering the existing problems of ant colony algorithm, the decline coefficient is introduced into the heuristic function to update the local pheromone, and the volatility coefficient of the pheromone is adjusted by setting the iteration threshold. Finally, through the design of path planning process, the planning of omnidirectional mobile robot’s full traversal path is realized. Experimental results show that the proposed method can not only shorten the full traversal path length, but also shorten the time of path planning to obtain the optimal path, thus improving the performance of full traversal path planning of omnidirectional mobile robot.
Path planning of intelligent mobile robot based on Dijkstra algorithm
Authors: Li Xueyan
Published: December 2021

Under the premise of grid environment modeling method, a relaxed Dijkstra algorithm is proposed to solve the problem of real-time path planning for mobile robot in large-scale and obstacle intensive working environment. Firstly, four neighborhood search is used to construct the Manhattan distance potential field from the source point to the global point in linear time, and then eight neighborhood search is performed from the target point to the source point to return a collision free and approximately optimal path. Matlab simulation results show that the algorithm is 10 times faster than dijksta algorithm and A-star algorithm, and the error of path length is within a reasonable range compared with the shortest path.
Research And Analysis of Nonlinear Identification Adaptive Control of Fitness Using MATLAB Numerical Simulation
Authors: Gou Xiaoping , Zhang WanJun , Zhang Feng , Qi Yu , Zhang Wenlan , Zhang WanLiang , Li Yadong
Published: December 2021

Aiming at the problems of non-linearity in physical exercise, difficulty in predictive model identification control, and difficulty in exercise in control target. A nonlinear identification adaptive control algorithm based on physical exercise is proposed, and a nonlinear identification adaptive control system based on physical exercise is established and simulated with MATLAB. Simulation results show that the recognition ability of physical exercise is strong, which improves the requirements of physical exercise quality, and has the advantages of simple control algorithm, high control accuracy and strong anti-interference ability.
Research on the Algorithm System for Generation and Creation by Computer Artificial Intelligence and Support Vector Machine
Authors: Wu Xuan
Published: December 2021

Algorithmic composition is also called automated composition. It is an attempt to use a specific form of process. Composers make full use of computers to carry out music creation and reduce their access. In this paper, based on the standard support vector machine (SVM) learning neural network, the least square support vector machine (LS-SVM) is combined with the recurrent neural network, and a new least square support vector machine learning neural network is proposed. The article realizes the efficient end-to-end multi-dimensional sound wave time series generation model Music-coder, through which the music style music of the famous singer Jay Chou is generated, and the quantified similarity with the real Jay Chou music data set reaches a maximum of 97.73%. The project in this paper shows that intelligent algorithm as a composition tool for music generation and creation is an effective music production program and will bring new development to music production.
Large-scale Network Survivability Mathematical Association Model under Set Pair Analysis Theory
Authors: Li Jiayi , Zhu Xiaoqing
Published: December 2021

With the expansion of the application field of robots, the use of eight-legged bionic robots to assist or replace human operations in various complex and extreme terrains is constantly being explored. This paper uses octopus as a bionic object, designs an eight-eccentric wheel walking platform, and studies its dynamics, kinematics and trajectory planning. This paper first investigates the development history and research status of multi-legged robots in many countries, analyzes the shortcomings of octa-legged robots, and proposes improved solutions on this basis. Through the bionic of the octopus structure, the Catia software is used to design and establish a three-dimensional model of the octopus-like eight-eccentric wheel robot. By importing the three-dimensional model into the dynamic analysis software Adams for simulation, after adding constraints, driving, torque and contact force, the various functions of the platform are simulated to obtain linear wheel walking, rotary motion, linear leg walking, the parameters of jumping motion and obstacle-crossing motion are drawn into tables for intuitive analysis, and virtual prototype simulation is used to verify the correctness of the established model and trajectory planning.

The research in this paper lays a theoretical foundation for the development and application of this eight-eccentric wheel bionic robot.
Aspect-level sentiment analysis merged with knowledge graph and graph convolutional neural network
Authors: Dai Zuhua , Liu Yuanyuan , Di Shilong , Fan Qi
Published: December 2021

Aspect level sentiment analysis belongs to fine-grained sentiment analysis, w hich has caused extensive research in academic circles in recent years. For this task, th e recurrent neural network (RNN) model is usually used for feature extraction, but the model cannot effectively obtain the structural information of the text. Recent studies h ave begun to use the graph convolutional network (GCN) to model the syntactic depen dency tree of the text to solve this problem. For short text data, the text information is not enough to accurately determine the emotional polarity of the aspect words, and the knowledge graph is not effectively used as external knowledge that can enrich the sem antic information. In order to solve the above problems, this paper proposes a graph co nvolutional neural network (GCN) model that can process syntactic information, know ledge graphs and text semantic information. The model works on the “syntax-knowled ge” graph to extract syntactic information and common sense information at the same t ime. Compared with the latest model, the model in this paper can effectively improve t he accuracy of aspect-level sentiment classification on two datasets.
Computer Intelligent Comprehensive Rapid Risk Assessment System of Barrier Dam by Fuzzy Analytic Hierarchy Process and Big Data
Authors: Xue Danxuan , Duan Yan , Meng Weiwei
Published: December 2021

Barrier dam overall stability and dam break influence degree are the two risks. In order to comprehensively and quickly evaluate the risk of barrier dams, the dam height, the capacity of the barrier lake and the material composition of the dam body are selected as the stability evaluation indexes; the dam failure degree and the risk population and the potential economic loss are taken as the evaluation indexes. Based on the fuzzy hierarchy theory, this comprehensive and rapid risk assessment system of barrier dam is obtained, which is clear, intuitive and rapid, combining qualitative indexes and quantitative indexes.
Smart image recognition system based on machine vision
Authors: Li Lei , Liu Fenggang
Published: December 2021

This paper proposes an efficient and accurate method of two-dimensional code recognition for industrial actual projects, and develops a high-speed and batch two-dimensional code recognition system based on machine vision. Firstly, according to the position of the QR code in the target subspace, a method to locate the region of interest of each QR code by using geometric relationship and batch processing QR code is proposed. On this basis, Gaussian noise is added to simulate the possible noise in production practice, and the anti-noise ability of the system is evaluated. Finally, the relationship between system recognition rate and QR code movement speed is analyzed and the experimental results are compared. The experimental results show that the system can meet the requirement of real-time online detection.
Comparison and analysis of several instantaneous reactive power calculation methods
Authors: Hu YiWen
Published: December 2021

Briefly describes several more common algorithm of reactive power when the input signal is a sine signal and research all kinds of reactive power calculation method, through matlab using the theory of monte carlo random multiple sets of random number them as the amplitude and phase Angle of voltage, current, the different calculation method of the size of the instantaneous reactive power, To get the best calculation method. Multiple groups of random numbers can avoid the error caused by using only one set of data for testing in existing papers.
Computer Mathematical Statistics Analysis of downscaling data of different vegetation index inversion TRMM
Authors: Qu Shuangbao , Zhao Miaoxing , Deng Shuo
Published: December 2021

This paper uses enhanced vegetation index (EVI) data, normalized vegetation index (NDVI) data, DEM, aspect data, and TRMM3B43 (V7) data, based on a geographically weighted regression model (GWR), and uses a statistical downscaling method to achieve Central China Downscaling of regional TRMM data from 2010 to 2019. The research results show: (1) TRMM data has good applicability in Central China, and the R2of TRMM data and weather station measured data is above 0.8. (2) Improve the ground resolution from 0.25°×0.25° (approximately 27.5km×27.5km) to 1km×1km while ensuring the same accuracy as the original data. (3) Overall, the accuracy of EVI downscaled precipitation data in Central China is better than that of NDVI downscaled precipitation data.
Mathematical model and calculation of safety and stability evaluation of underground space engineering by TOPSIS and analytic hierarchy process
Authors: Zhu Henghua , Li Xin , Jia Chao , Liu Chunhua , Zhu Xiao , Liu Zhizheng , Wei Zhengrun , Li Hu , Tang Junping
Published: December 2021

The development of economy promotes the development of urbanization, and the power of urban space engineering, so the stability research of urban underground space engineering is very important. Although the existing evaluation models can consider a single form of underground space safety problems, they seldom consider the uncertainty of cross-blending of multiple information types within a certain interval, and cannot continuously express the quantitative results of the suitability assessment of urban underground space. This paper takes an underground tunnel in China as the research background, calculates the weight of the selected construction stability index through the analytic hierarchy process, and finally evaluates the stability of different sections of the project by TOPSIS method, and draws the corresponding conclusions.
Safe Distance Mathematical Calculation and Quantitative Analysis on Covid-19 Using Einstein Equation and Gaussian Distribution
Authors: Miao Hanwen
Published: December 2021

Most of the diseases caused by virus mainly spread through droplets in the air. The pathogen bearing droplets go deep into people’s lungs and cause infection. In this paper, we analyze the safe distance, the minimum range to keep droplets containing virus particles from entering lungs, and thereby carrying the virus inside the lung. Einstein equation for diffusivity of a particle and the wide of the Gaussian distribution of the particles in Brownian movement are used in the calculation of the range a virus-containing mucosal vary droplet can reach. Moreover, we used datas recorded in a previous paper named “Visualization of sneeze ejecta: steps of fluid fragmentation leading to respiratory droplets” by B. E. Scharfman et. all to generate our results.
Research on Precise Control of a Cylinder Delay Oscillation System Based on Response Surface and Genetic Algorithm
Authors: Bao Zhongfu , Zeng Dejiang , Gu Runxi
Published: December 2021

A cylinder time-delay oscillation system can be constructed by using air bag and throttle valve. The air bag and throttle valve are used to realize the time-delay transmission of pressure in the feedback circuit, and the feedback pressure is used to promote the reversing of two position five-way valve, so as to realize the reciprocating action of the cylinder. The experimental design is carried out based on the simulation analysis, and the response surface is constructed based on the experimental data to clarify the relationship between the cylinder dwell time and the main component parameters. Based on response surface, genetic algorithm is used to search for the best control parameters to realize the accurate control of cylinder dwell time.
Study on an efficiency algorithm for the opening middle tap of steam feed pump
Authors: Zhu Lingkai , Wang Qian , Gao Song , Han Yue , Zhong Ziwei , Zheng Wei , Shang Panfeng , Guo Junshan
Published: December 2021

This paper presents a method for calculating the efficiency of steam feed pump, which fills the literature gap in calculating the efficiency of steam feed pump when the middle tap of feed pump is opened. This method has the advantages of convenient measurement and few measurement parameters. Combined with IFCIFC-97 industrial water and steam thermodynamic property model, the efficiency of feed pump can be calculated
Research computer numerical simulation on heat dissipation model of submarine data centre based on TOPSIS model
Authors: Qin Rui , Zhang Man , Chen Lijie , Liu Xiao , Lei Zhengtao , Shi Guoyong , Zhou Tianwen , Hou Guiwen
Published: December 2021

Due to the huge energy consumption of land-based data centers, it is necessary to establish undersea data centers as soon as possible in order to alleviate the problem of resource tension. In this paper, the uniformity of containers is assumed. Through force analysis, it is found that the stress of containers is uniformly distributed, so only the external stress should be considered. Hypothesis submarine data center in the 50 m deep seawater, calculate the container need to withstand stress is 76.417403 Mpa, common material in engineering field, then physical parameters of material to deal with the dimensional and normalization, and establishes a comprehensive evaluation model material, the Topsis method is adopted to solve, to solve the optimal evaluation of the results can be divided into: 7-4 PH Stainless Stee 0.7450 points, so choose it as IU server container material.
Construction of elliptic stochastic partial differential equations solver in groundwater flow with convolutional neural networks
Authors: Pang Xue , Wang Jian , Yin Faliang , Yao Jun
Published: December 2021

Elliptic stochastic partial differential equations (SPDEs) play an indispensable role in mathematics, engineering and other fields, and its solution methods emerge in endlessly with the progress of science and technology. In this paper, we make use of the convolutional neural networks (CNNs), which are widely used in machine learning, to construct a solver for SPDEs. The SPDEs with Neumann boundary conditions are considered, and two CNNs are employed. One is used to deal with the essential equation, and the other satisfies the boundary conditions. With the help of the length factor, the integrated neural network model can predict the solution of the equations accurately. We show an example of groundwater flow to evaluate the model proposed with Gaussian random field (GRF). The experimental results show that the proposed neural network solver can approximate the traditional numerical algorithm, and has high computational efficiency.
Computer Big Data Technology in Internet Network Communication Video Monitoring of Coal Preparation Plant
Authors: Chen Hao , Zi XinLi , Zhang Qing , Zhu YuGe , Wang JiaYin
Published: December 2021

The paper uses the control technology of computer big data and PLC, fieldbus communication technology and video monitoring technology to research, design and develop the monitoring system of the coal preparation plant’s production process. In this plan, the coal preparation plant’s video monitoring system, production centralized control system and other production support systems are fully integrated through network technology, to achieve the purpose of improving its safety guarantee function. The system improves the level of visual management, realizes unattended operation, and reduces potential safety hazards.
Simulation study on pitch system of floating wind turbine
Authors: Chen Dianhui , Li Jianguo , Hong Xuanyu , Chen Diankai
Published: December 2021

Due to the complex sea conditions, floating wind turbines produce unbalanced loads. Firstly, this paper will take NERL-5MW floating wind turbine as the model, and apply brainstorming algorithm (BSO) to the independent pitch system based on PID azimuth weight coefficient. Then, a joint simulation will be carried out in OpenFAST-Matlab/Simulink to study its impact on the load of floating wind turbine. Finally, the simulation results reveal that compared with the independent pitch system based on PID azimuth weight coefficient, the proposed method can reduce the load of the floating platform to a certain extent.
Design of electric power emergency communication system based on multi-network integration
Authors: Sun Xiaoguang , Geng Jianyu , Liu Kai , Wang Yuanzhi , Wang Zhipeng
Published: December 2021

Natural disasters and emergencies generally pose serious threats to power facilities. Therefore, it is necessary to establish an efficient electric power emergency communication (EPEC) system. Existing systems based on a single network carrier (for example,4G, satellite, and Wi-Fi) may not meet the requirements of complex environments. We design a new EPEC system based on multi-network convergence technology by integrating the above three network carriers. It overcomes the limitations of single network carrier and improves the efficiency of power emergency communication. The test results show that the system can improve the transmission line bandwidth, automatically switch to the optimal signal network, and guarantee the security and stability of data transmission.
Research on Computer Assisted Intelligent Emission System of High-rise Building Based on BIM Technology and Wireless Automatic Monitoring
Authors: Huang Xinyao
Published: December 2021

In response to the needs of low-carbon design and carbon emission measurement of public buildings, we use advanced information tools, building information model BIM technology to solve these problems, and from the perspective of strategic development, we will establish a set of home improvement design systems based on BIM technology for unification Three-dimensional home improvement design. The system includes analysis of thermal performance of high-rise building decoration and building light environment, and proposes optimization countermeasures for low-carbon design.
Discrete wavelet transform processing system based on digital watermarking algorithm
Authors: Shi Miao
Published: December 2021

This paper introduces the concept of multimedia digital watermarking and summarizes the current technology status. This paper summarizes the research status and basic principle of digital watermarking. The advantages of digital watermarking algorithm based on wavelet transform are analyzed. The proposed algorithm combines Arnold scrambling method and DWT transform multi-resolution characteristics, and adopts linear and different embedding strength methods. Effectively improve the security of the watermark. According to the classification results, different intensity watermarking components are embedded into the DCT low frequency coefficients of different image blocks. Experimental results show that this algorithm has strong masking and robustness, and the watermarking realized by using the proposed algorithm has good robustness against common image processing and noise interference.
Design of Massive Image Duplicate Search Algorithm in Cloud Computing Environment
Authors: Yao Shunyu
Published: December 2021

Massive image replay algorithm adopts cloud computing technology to realize image uploading, processing and classification on cloud platform. Image classification is realized by image classifier. Zernike matrix was used to compare the classified images and determine the pseudo-edge blocks around the image. According to the pixel value of the image, the binarization method was used to process the image. After processing, edge detection and line detection were carried out to determine the real image size. The similarity of two real images is calculated by normalized similarity criterion, and the image repetition is judged accordingly. The results show that the accuracy of the algorithm is higher than 99%, and the accuracy of the algorithm is higher than that of the comparison algorithm, and the accuracy of the algorithm is the highest when the similarity threshold is 0.8∽0.9.