bluuebunny/crossref_metadata_2025_split huggingface dataset:
Research on resilience recovery strategy optimization of highway network after disaster based on genetic algorithm
Authors: Zhao Fayu 
Published: December 2021

Abstract
In order to effectively improve the recovery efficiency of the highway network after the disaster and make the road network quickly recover to the normal operation level, the recovery strategy of the highway network after the disaster aiming at the optimal toughness was studied and formulated. First clear the toughness in this paper the definition and put forward the two toughness indexes, then constructs the model of road network resilience restored after a disaster, in considering the time, money, resources and cost conditions, through the corresponding genetic algorithm to solve, it is concluded that the shortest road repair, restore minimum loss in the process of recovery program. Finally, an example is given to illustrate how to use the model established in this paper. The results show that from the beginning of repair to the end of repair, the repair team can achieve the expected task in a faster time, which minimizes the performance loss of the road network and saves the cost.
Transportation route optimization based on heuristic algorithm
Authors: Wu Fan , Zhu Yongan 
Published: December 2021

Abstract
With the rapid development of Internet technology, many enterprises are committed to finding the best solution in transportation organization and solving the vehicle distribution routing problem. Firstly, this paper introduces the current situation of transportation organization of Sichuan Yida Feiniu Transportation Company, and analyzes the main problems of the company. Secondly, through the prediction of freight volume, prepare the truck vehicle operation plan and optimize the company’s transportation organization and production plan. Finally, the heuristic algorithm is used to establish a mixed integer programming mathematical model to optimize the pooled vehicle distribution path problem and the vehicle distribution path with time window. In terms of centralized vehicle distribution, combined with the actual situation of Sichuan Yida Feiniu Transportation Company, an example is analyzed, the shortest total path is obtained, and the goal of shortest vehicle travel distance is realized. Through the optimization of the company’s transportation organization, this paper is of great significance to improve the company’s transportation organization to a certain extent.
Calculation and analysis of landing double rocker arms holding pole based on finite element simulation
Authors: Zhang Xing , Shao Yingpeng , Xing Yu 
Published: December 2021

Abstract
Landing double rocker arms holding pole are widely used in the erection of UHV construction towers. Most of the construction arms are based on experience in engineering application, and there are some potential safety hazards. In this paper, the finite element model is established based on the relevant parameters of 700×700mm2 double rocker arm holding pole, and the actual lifting conditions of the pole are analysed. The finite element method is used to simulate nine working conditions for stress analysis. The results show that the double rocker arm holding pole has good mechanical properties under rated load conditions, which verifies the reliability of the arm design. Asymmetric moment hoisting is an important factor threatening the safety of holding pole, which must be strictly controlled.
The Prediction of CMDB Propellant lifetime Based on Arrhenius accelerated model, Berthelot’s equation and Multi-step Prout-Tompkins Model
Authors: Wang Qiong , Gu Yan , Du Jiao Jiao , Jia Lin , Zhang Lin Jun 
Published: December 2021

Abstract
Different models were provided to predict the storage lifetime of propellants more accurately. The stabilizer was recognized as a vital parameter for double based propellants’ storage lifetime estimation. The stabilizer contents of a certain RDX-CMDB propellant were traced during the accelerated aging tests. Based on that, the safe storage lifetime of this propellant were predicted using the Berthelot’s equation, Arrhenius accelerated equation and the advanced kinetic model, respectively. The predicted results were compared and the causes were analysed. It found that the biggest disadvantage of Berthelot’s equation and Arrhenius accelerated equation is that the predicted results are significantly affected by the original data. In details, the minor difference of original data will bring tremendous errors when extrapolating to normal temperature. The general model which can be used to depict complex reactions adopted in AKTS software was preferred compared to reaction order (RO) model and Prout-Tompkins (PT) model.
3D Digital Twin of Intelligent Transportation System based on Road-Side Sensing
Authors: Guo Yunpeng , Zou Kai , Chen Shengdong , Yuan Feng , Yu Fang 
Published: December 2021

Abstract
Cooperative vehicle-infrastructure is one of the most import developing direction of future intelligent transportation system, while digital twin system can record, reproduce, and even deduce the physical system, which could be helpful for the development of cooperative vehicle-infrastructure. In this study, we proposed a 3D digital twin platform of intelligent transportation system based on road-side sensing, a core component of cooperative vehicle-infrastructure system. This platform consists of real road-side sensing unit,3D virtual environment, and the ROS bridge between them, by receiving the sensing results of physical world in real-time, the virtual world can reproduce the compatible road traffic information, such as the type,3D position and orientation of traffic participants.
Simulation application of three-dimensional GIS based on full-scenario intelligence in power grid company transmission line planning
Authors: Zhang Le 
Published: December 2021

Abstract
Traditional data collection and review methods in power grid planning have always had the problems of time-consuming, poor real-time performance, and cumbersome processes. The application of mobile GIS solves the problems of data collection and review methods and makes more efficient use of mobile GIS terminal collection. The data of the mobile GIS solve the urgent problems that need to be solved since the popularization and application of mobile GIS. This system implements functions such as storage, transmission, and review based on mobile GIS data, which will greatly improve the efficiency of data collection by mobile terminals and reduce the cost of data collection. Realize the planning simulation of the power grid under the intelligent cycle of the whole scene.
Energy-saving Scheme of 5G Base Station Based on LSTM Neural Network
Authors: Wang Yuxuan 
Published: December 2021

Abstract
As China’s new infrastructure,5G has received national and social attention. 5G promotes economic to grow rapidly. But, the high energy consumption caused by the massive deployment of 5G base stations cannot be ignored. The total annual power consumption is expected to reach 243 billion degrees when the 5G base station is fully built. In the tidal scene, some 5G base station in an idle state still power fully, which causes great power waste. The historical volume of base station business data is used to train LSTM model, and predict the future base station business. When the business is lower than the threshold, the base station will be closed to avoid unnecessary power waste. And the LSTM model prediction results fits the original data ideally. By implementing the power saving strategy, the energy consumption of the base station is reduced by 18.97 %. A single station can save 1174 degrees of electricity yearly. It can be seen that the energy saving effect is remarkable.
An Algorithm for Path Planning of Autonomous Ships Considering the Influence of Wind and Wave
Authors: Zhou Yucheng , Gong Yan , Geng Xiongfei , Li Dongsheng , Gao Beili , Li Chunxu 
Published: December 2021

Abstract
Aiming at the problem that external factors such as wind, waves and currents are not considered in the path planning of autonomous sailing ships, which affect the safety of navigation, an improved particle swarm optimization algorithm is proposed. Introduce adaptive inertia weight to improve the convergence of the algorithm, wind and wave influence factors in the algorithm fitness function, increase the wind and wave resistance of the path, and improve the safety of the path. MATLAB simulation experiment results show that the optimized PSO algorithm can obtain the global optimal path and improve the safety of the path.
Robust Prescribed Performance Control of Uncertain Vehicle Lateral System under State Constraints
Authors: Yu Jing 
Published: December 2021

Abstract
In the study of the zero-error tracking control problem for vehicle lateral control systems under full-state constraints and nonparametric uncertainties, the zero-error tracking control problem is presented in this paper. A neural adaptive tracking control scheme is proposed by combining the error transformation of the vehicle lateral control system with the barrier Lyapunov function, which realizes that the tracking error of the vehicle lateral control converges to a prescribed compact set at a controllable or specified convergence rate in a specified finite time. The scheme has the following significant characteristics: 1) Based on the Nussbaum gain, the preset new energy finite-time control algorithm, the tracking error of the vehicle lateral control system with non-parametric uncertainty and external disturbance decreases to zero with t → ∞. In addition, it also has the control ability to cope with the presence or even unknown moment of inertia of the system. 2) Barrier Lyapunov function (BLF) ensures the bounded input of the neural network during the whole system envelope, and ensures the stable learning and approximation of the neural network. Furthermore, the bounded stability of the closed-loop system is proved by Lyapunov analysis. Finally, the effectiveness and superiority of the proposed control method are verified by simulation.
Numerical simulation on Crashworthiness of 105000t LNG Carrier
Authors: Sun Qian , Liu Jianmin , Zhou Hong 
Published: December 2021

Abstract
It is of great significance to study the crashworthiness of LNG carrier to improve its crashresistance and enhance its operation safety. In this paper, the collision process between the bulbous bow of the container ship and the side structure of the LNG ship is analyzed by using nonlinear finite element numerical simulation. Collision performance of LNG carrier and collision indicators during the collision, the impact force, velocity and displacement and energy absorption in the process of collision by changing parameters of the major velocity, impact angle and impact location and others are studied. The relevant research results have a strong practical significance for analyzing the deformation, strengthening measures and structural repair of ship side structure impact damage.
Research on Multi-dimensional Data Collaborative Virtual Inventory Based on Markov
Authors: Sun Shunkai , Li Jie , Lu Haihua , Xu Qi , Cui Haobo , Cao Weilin , Chi Yingxiao , Zhou Jun 
Published: December 2021

Abstract
The three-dimensional elevated warehouse is a production equipment, and it is inevitable that it will malfunction during the operation. If it is not handled properly, there will be inconsistencies between information and practice, resulting in inconsistency between inventory information and the actual product. In order to solve the above problems, this project team carried out functional research on various SQL tables of multi-dimensional data collaboration, and constructed a virtual inventory method based on Markov multi-dimensional data collaboration. The behavioral characteristics of the cargo location information in the cargo location table TWMS_LOC and the pallet status table TWMS_PLT are extracted, and the two are compared. If the deviation between the two exceeds the threshold, the status is judged to be no cargo information. Experiments are conducted to test the feasibility and effectiveness of the sentences of the proposed virtual inventory. The results show that the inventory method can better describe the status of the cargo location and information, and effectively realize the virtual inventory at the database level. The research results of this method will completely replace the complicated manual inventory business. It can provide accurate and efficient virtual inventory solutions for similar logistics elevated warehouses.
Wireless communication network security intelligent monitoring system based on machine learning
Authors: Liu Hongkun , Wang Nianci , Liang Sirong 
Published: December 2021

Abstract
Aiming at the problems of traditional wireless communication network security vulnerability monitoring systems such as low monitoring accuracy and time-consuming, a machine learning-based intelligent monitoring system for wireless communication network security vulnerabilities is proposed. In the hardware design of the monitoring system, based on the overall architecture of the wireless communication network and the data characteristics of the wireless communication network, it is divided into a vulnerability data collection module, a vulnerability data scanning module, and a network security vulnerability intelligent monitoring module. In the vulnerability data collection module, the wireless data collector is used to collect vulnerability data in the vulnerability database, and according to the attributes of the vulnerability data, the XSS vulnerability detection plug-in is connected to the vulnerability scanner to scan for wireless communication network vulnerabilities; When the communication network vulnerability data signal is traced, the system session operation of monitoring the vulnerability data. The software part introduces the neural network algorithm in the machine learning intelligent algorithm to process the hidden data in the security vulnerability data. The experimental results show that the wireless communication network security vulnerability intelligent monitoring system based on machine learning can effectively improve the system monitoring accuracy and the efficiency of wireless communication network security vulnerability monitoring.
Leakage analysis of campus water supply system based on MLP neural network
Authors: Wang Yuanhao 
Published: December 2021

Abstract
Water supply system is an important part of campus public facilities, and the water supply pipeline will leak, not only increase the cost of water supply, but also cause water waste. This paper collects water consumption data of water meters at all levels in a school’s water supply system, establishes MLP multilayer perceptron neural network model, determines the water leakage rate according to the fluctuation of predicted value and actual value, so as to analyze the leakage situation of each school’s water supply system. When the fluctuation between the actual and predicted water consumption exceeds a certain threshold, water leakage occurs on that day. Through solving the model, the following conclusions are finally drawn: (1) the annual water leakage rate of the school is 10.74%, and the water leakage is 29131.418L. (2) The water leakage rate in the first quarter is the highest, and the water leakage in the second quarter is the highest.(3) The school aquaculture area is the most serious leakage phenomenon, and the maximum water leakage rate of each water meter node is more than 10%.
Study of a Privacy Preserving Logistic Regression Algorithm (PPLRA) For Data Privacy in the Context of Big Data
Authors: Chen Qiang , Deng Meiling 
Published: December 2021

Abstract
Regression algorithms are commonly used in machine learning. Based on encryption and privacy protection methods, the current key hot technology regression algorithm and the same encryption technology are studied. This paper proposes a PPLAR based algorithm. The correlation between data items is obtained by logistic regression formula. The algorithm is distributed and parallelized on Hadoop platform to improve the computing speed of the cluster while ensuring the average absolute error of the algorithm.
Power Generation Prediction Model Based on Improved PSO-BPNN
Authors: Yu Yan 
Published: December 2021

Abstract
Electricity generation greatly impacts economic development, and electricity is indispensable for production, transportation, and living. Therefore, forecasting electricity generation accurately is of great research significance for the development of the country and the livelihood of the people. Because of the nonlinear relationship between electricity generation and the influencing factors, this paper, supported by the above data in China over the past 20 years, describes a prediction model based on Improved Particle Swarm Optimization (PSO) -- Back Propagation Neural Network (BPNN) to optimize the algorithm about forecasting electricity generation. The experimental results have shown that the accuracy and stability of the prediction model were constructed in this paper, which was improved by about 2%-6% compared with the traditional ones. In addition, the application of this model could provide a constructive theory for some relevant works in the electric-power industry.
Segmentation of Cracked Silicon Wafer Image Based on Deep Learning
Authors: Li Xingxing , Yin Panpan , Duan Chao , Wang Ningxing 
Published: December 2021

Abstract
With the development of the new energy industry, a large number of silicon wafers need to be tested for production quality through the automation industry. The development of deep learning technology has brought huge technological improvements to the industrial quality inspection industry. Through the image segmentation technology based on deep learning, it can accurately divide the defects existing in the silicon wafer. In this paper, the UNet deep learning network is used to segment the hidden cracks in the silicon wafer. The network can extract the shallow semantic features in the silicon wafer well. It uses 5,000 samples collected on the industrial site as the training set,1,000 pieces the sample is used as the test set, and the segmentation accuracy IOU can reach 58.7%.
Research on Service-Oriented Software Systems and Computer Software and Intelligent Calculation Method
Authors: Ni Zhimin , Zhao Fan 
Published: December 2021

Abstract
For the existing service-oriented software single, favors business processing, cannot guarantee the software business processing into the development of software. When the operator encounters operational problems, software failure problems and other problems related to software operation and operation, software development technicians to provide technical support to ensure the software’s business processing functions. This study will move away from dependence on other software and provide technical support to business software operators accurately and in a timely manner to effectively solve the problems that operators may encounter.
Realization And Network Security Design of Information System Digitization of Scientific Project By JAVA+STRUTS
Authors: Zhao Fan 
Published: December 2021

Abstract
At present, the technical plan project appraised the management systematic characteristic, continuous, the independent not strong third party appraised carries out the advancement to be slow; The project may supervise the measure not strong not to have the explicit monitor target and the baseline data; Has not established a set to conform to the technical project characteristic and the project monitor appraisal system which matches with the science and technology project management. In view of above question, uses JAVA and the STRUTS method of exploitation realization easy to maintain, the easy dynamic expansion, to have the secure technical plan project appraisal management process. Through in the recent three years in the Gansu Province science and technology plan project appraised in the management the application indicated, the system enormous enhancement project appraisal management working efficiency, the system movement has been stable, the speed of response is quick, the security is high.
Research on Geological Disaster Forecast Method Based on PCA Structure BP Model
Authors: Luan Zhangbao 
Published: December 2021

Abstract
The BP neural network prediction method constructed by PCA and the geological hazard prediction method based on the MM5 numerical model were used to establish geological hazard classification short-term objective forecast models. The calculation results show that these two objective forecast methods have a good fitting effect on historical samples. The independent sample’s trial report effect is also good; based on the above two objective forecasting methods, through correction, the comprehensive forecast product is finally obtained.
Computer Image Recognition and Recovery Method for Distorted Underwater Images by Structural Light
Authors: Jian Bijian , Ling Yongfa , Zhang Xuebo , Ou Jiawei 
Published: December 2021

Abstract
When imaging through water surface, the random fluctuation of sea surface will cause the distortion of the target scene image, so the distorted image needs to be corrected and reconstructed. At present, distortion compensation mainly adopts iterative registration strategy based on image sequences which is difficult to satisfy the real-time observation. This paper presents a correction method based on active imaging of structured light for underwater image. Experimental results show that compared with the traditional iterative algorithm, the proposed algorithm cannot only improve the restoration accuracy, but also greatly shorten the processing time. Experimental test results demonstrate that the proposed algorithm has good recovery results.
Research on Application of Computer Recognition Technology in C Language Programming Modeling System
Authors: Zhao Yikun 
Published: December 2021

Abstract
C language programming is more and more favoured by the majority of technical personnel in embedded systems. The application of C language technology in computer software programming can effectively avoid unnecessary language logic problems, ensure the smooth progress of programming work and effectively improve the quality and efficiency of programming. For the development of C language embedded system, the programming ideas of system software are explained, the functional module division based on hierarchical design is given, and the realization methods of project organization, program framework design, module reuse design, etc. in the software development process are clarified. To solve the contradiction between C language flexibility and application development engineering. Although it is introduced for the ARM platform, the basic experience and algorithms are also suitable for software design on other embedded platforms.
Research on the Application of Artificial Intelligence Technology in Computer Graphics Processing
Authors: Yang Xia 
Published: December 2021

Abstract
In structured light geometric reconstruction, due to the complexity of shooting methods and scene lighting conditions, the resulting images may be lack of image details due to uneven light. For this reason, the article proposes a Retinex algorithm with colour restoration and colour saturation correction strategy based on HSV colour space transformation based on artificial intelligence technology. Then distinguish whether it is a bright area according to the threshold value, and modify the insufficient transmittance estimation of the bright area. Finally, the intensity component and saturation value are restored in the HIS colour space, and the histogram is used to stretch the intensity component.