bluuebunny/crossref_metadata_2025_split huggingface dataset:
Visual Servo Control of Industrial Robot Based on Convolutional Neural Network
Authors: Li Quanfang , Zhu Liucun , Li Boquan , Zheng Xiaodong , Luo Junqi 
Published: January 2021

Abstract
Aiming at the problem of poor flexibility of traditional industrial robot, the vision system and industrial robot control system are combined to propose a visual servo control method based on Faster RCNN. The image information of the target object is collected through the camera, and the Convolutional Neural Network(CNN) is used to detect the entire picture, then the category and position of the object to be grasped are obtained, which improves the control performance of the robot system. Experiments show that the visual servo robot control system can quickly complete the position recognition of different objects. Mean average precision of this method can reach 0.867. The maximum error between the recognized grasping position and the actual position on the coordinate axis does not exceed 3.4 mm, the detection time of each picture in the GPU environment is 17.1ms, which has certain guiding significance in the visual servo control of industrial robots.
The Fault Diagnosis of Diesel Fuel Supply System Based on BP Neural Network Optimized by Genetic Algorithm
Authors: He Jiangjiang , Li Xiaoquan , Zhao Yuwei 
Published: January 2021

Abstract
As an important power source of diesel engine, the fuel supply system has the characteristics of high failure rate and being difficult to be detected, which is critical to detect and diagnose the fault for the reliable and stable operation of diesel engine. In the paper, principal component analysis (PCA) was used to process the initial data, back-propagation (BP) neural network was used to diagnose fault of diesel engine, BP diagnosis efficacy was analyzed, then the BP neural network fault diagnosis system was optimized by being introduced in the genetic algorithm , and the comparison results of training error and diagnostic analysis showed that: the fault diagnosis of BP neural network optimized by genetic algorithm is more accurate than that of traditional BP, which can effectively improve the fault diagnosis accuracy and reduce the training time.
Research on parallel algorithm based on AABB bounding box coordinate chain method
Authors: Qu Huiyan 
Published: January 2021

Abstract
With the rapid development of virtual reality technology and collision detection technology, virtual reality has become a lot of research fields in China. Collision detection is one of the most important technologies, and virtual surgery simulation has gradually become an important application of medicine in virtual reality technology. Virtual surgery can not only provide a skilled training platform for medical staff, but also analyze the feasibility and danger of surgical scheme, so that medical staff can have the same authenticity and strong immersion in virtual environment as in physical surgery. In this paper, a mixed hierarchical bounding box is constructed to detect the collision between the virtual human soft tissue and the rigid tissue of surgical instruments, and a parallel algorithm, fast bounding box coordinate chain calculation, compression storage and so on are introduced. For the deformation model of the software which is difficult to construct, the collision detection can be completed quickly and accurately, which can effectively save the collision detection time and improve the real-time performance of the collision.
Combine the AGA and L-M algorithms to predict the oil-water flow profile of production wells
Authors: Shi Hangyu , Song Hongwei , Guo Haimin 
Published: January 2021

Abstract
Production logging is the main means of dynamic monitoring of oil wells at present. The interpretation method of production logging fluid profiles is the key to the dynamic evaluation of oil wells and is of great significance. A joint optimization technique of a AGA and L-M is proposed to deal with the profile data of oil-water two-phase flow. The method is based on the energy conservation of the fluid in the production unit space. According to the nonlinear weighted least squares principle and the error theory, the objective function of the minimum value is established by the difference between the theoretical fluid temperature and the measured value of the thermometer. According to the fluid volume conversion, the flow rate of each phase in the well and the flow log value at the bottom of the control body are constrained. In order to improve the interpretation accuracy, the global search method (AGA) of genetic algorithm and the direct local search method of L-M algorithm are combined to solve the optimal solution. Firstly, the adaptive genetic algorithm is used for heuristic global search, and then as a result of the initial parameters, the L-M method is applied to approach the optimal solution. The interpretation results from the joint inversion are stable and reliable. This method is not only suitable for vertical wells but also for inclined wells.
Algorithm Study of New Association Rules and Classification Rules in Data Mining
Authors: Yang Xiaobo 
Published: January 2021

Abstract
In order to further improve the efficiency of data mining, it proposes a kind of data mining algorithm based on new association rules and classification rules. Specific research process is as follows. Firstly, MDML-PP algorithm is analyzed and applied to the multi-dimensional multi-level association rules in data mining, and then selects the test data sets for performance evaluation, meanwhile, it also studies the multi-support rate cut and classification rule mining algorithm, which is applied to multi-support rate classification rules in data mining, finally, using the compare experiment to verify the effectiveness of multi-support rate classification rules. The results show that the proposed algorithm in this paper can be better used in data mining with multi-dimensional and multi-layer association rules, which can improve the efficiency and quality of data mining.
The Research on Clustering Ensembles Selection Algorithm based on Semi-supervised K-means Clustering
Authors: Wu Xiaoxuan , Guo Changjian , Hu Tanglei 
Published: January 2021

Abstract
Selective clustering ensemble algorithm can eliminate the inferior quality clustering member’s influence and can achieve a better clustering solution relative to the clustering ensemble algorithm. For high dimensional data clustering, in this paper, a novel selective ensemble algorithm based on semi-supervised K-means clustering is proposed. In this paper, through a large number of experiments to verify the validity of the proposed algorithm for dealing with high dimensional data clustering. The new algorithm can achieve statistically significant performance improvement over other clustering algorithms.
A multi-objective optimization method for aerospace product research and development process based on particle swarm optimization algorithm and critical path algorithm
Authors: Liu Yan , Yin Bo , Jia Dongning 
Published: January 2021

Abstract
In order to realize the multi-objective management objectives in the production cycle of aviation products, this paper combines particle swarm optimization algorithm and critical path optimization algorithm to carry out multi-objective optimization on the research and development process of aviation products. First, calculate the start time of each process by the critical path method and construct the initial population. Then construct the fitness function. Finally, particle swarm optimization is used for optimization, and through continuous iteration, the optimal combination that can achieve multi-objective optimization is obtained. Through the optimization experiment on the research and development process of aviation products, the global optimal research and development process calculated in this paper can shorten the production period by 32.4% and reduce the cost by 41.1%. Therefore, the multi-objective optimization scheme based on hybrid optimization algorithm proposed in this paper has theoretical and practical significance for the model management of the whole life cycle of aviation products.
Moving Object Detection Algorithm based on Improved Visual Background Extractor
Authors: Yang Xuewen , Liu Tangyou 
Published: January 2021

Abstract
Aiming at the problems that the ViBe algorithm causes error detection when the camera jitter, ghosts appear when processing moving targets, and the detected moving targets are incomplete, an improved ViBe algorithm based on motion compensation is proposed. In the background modeling stage, the motion compensation method based on KLT is used to obtain background model to enhance the robustness of the algorithm to the dynamic background. In the foreground detection stage, combined the background model of the current pixel with 8 neighbor pixel background model, by the double discriminant algorithm to eliminate ghost areas caused by detecting the real background points as foreground points, introduce OTSU algorithm to obtain the optimal threshold for foreground detection. In the post processing stage, filter the connected components for segmentation masks and update models to limit the wrong background points scattered in the foreground.Finally, the connected domain is repaired by morphological opening operation. The results show that the algorithm can effectively eliminate the interference caused by camera jitter, and suppress the ghost phenomenon to obtain more accurate foreground images.
Improved ECO Algorithm Based on Residual Neural Network
Authors: Qi Huifang , Wang Changmeng , Li Bo 
Published: January 2021

Abstract
Video target tracking is one of hot fields of computer vision, and its application is also very extensive. However, due to the complexity and variability of tracking environment, which brings some challenges to the research of target tracking. ECO(Efficient Convolution Operators) Algorithm is proposed based on convolutional neural network in three aspects. Firstly, residual neural network ResNet50 is adopted instead of convolutional neural network to extract the appearance features of target, and deeper residual neural network is applied to obtain more abundant target semantic information, so as to improve the tracking effect of tracking algorithm.Secondly, sample space classification strategy is improved. Different weights are assigned to shallow feature and deep feature, which make the deep feature play a more important role and improve the effect of target tracking. Finally, the method of scale estimation is improved so that better bounding boxes can be estimated with the scale changing. Experimental results show that the distance accuracy and success rate of the algorithm.
Photovoltaic output prediction of regional energy Internet based on LSTM algorithm
Authors: Weng Geping , Pei Chuanxun , Ren Jiaorong , Ye Chen , Cui Qinyue , Qing Hua , Liu Yuan , Guan Xinyu 
Published: January 2021

Abstract
By the huge development of large scale and modular photovoltaic power generation, accurate photovoltaic (PV) output prediction can help PV power station, scheduling department and power system operate safely and economically. In the process of PV output prediction, the data density is large, and the output data is relatively regular. Therefore, this paper considers the use of long-termed and short-termed memory neural network algorithm to optimize the problem of algorithm gradient vanishment in recurrent neural network, and complete the output prediction of PV power in the regional energy Internet on the basis of historical output data. In this paper, LSTM algorithm is used to analyze the historical output data of PV stations in an industrial zone of a certain city. It can be found that LSTM algorithm has good adaptability for short-term PV output prediction, which can meet the needs of application.
The Wolf pack assignment rule based on ant colony algorithm and the path planning of scout ants in complex raster diagra
Authors: Zhu Yu , Zhu Liucun , Long Yong , Luo Junqi 
Published: January 2021

Abstract
The traditional ant colony algorithm based on raster algorithm has slow searching speed and convergence speed in the problem of robot path planning, and it is easy to fall into the problem of local optimal. In order to solve this problem, an improved ant colony algorithm based on Wolf distribution rules and reconnaissance ant strategy is proposed, which can adjust the pheromone coefficient adaptively and obtain a more suitable proportion of pheromone allocation. Experiments show that this algorithm is superior to the traditional ant colony algorithm in terms of optimal path searching speed, quality and convergence speed in simple and complex environments.
Voltage sag severity analysis based on improved FP-Growth algorithm and AHP algorithm
Authors: Lin Yan , Lin Fang , Huang Daoshan , Fang Xiaolin 
Published: January 2021

Abstract
In order to accurately evaluate the impact of voltage sag on both utility and customer, a data mining analysis method based on improved FP-growth algorithm and AHP algorithm is proposed. The proposed method selects and classifies voltage sag characteristics and combines voltage sag severity level to construct a data mining analysis framework. The improved FP-growth algorithm is used for data mining on voltage sag events to improve the efficiency of mining. The association rule matching model is constructed by AHP algorithm for evaluating the voltage sag severity level, which improves the accuracy of the evaluation results. Finally, a practical example verifies the practicability of the proposed method.
Inter-annual and Inter-decadal Variation of Temperature during 1960-2013 in Dabie Mountain of West Anhui Province
Authors: Zhao Yongmei , Luo Yuan , Luan Xiaoxiao , Cheng Xinyu 
Published: January 2021

Abstract
The inter-annual and inter-decadal variation of temperature in Dabie Mountain of West Anhui Province is analyzed according to actually measured data of daily average temperature, maximum temperature and minimum temperature during 1960-2013 in five meteorological stations in Dabie Mountain. Results show: The quarterly and annual average temperature, average maximum temperature and average minimum temperature (except the average maximum temperature in summer) in Dabie Mountain of West Anhui Province are all in a rising tendency. The annual average temperature increases remarkably at an amplitude of 0.165°C/10 years. The increase amplitude of average minimum temperature is 1-2 times of the average maximum temperature, and the daily range shows obvious reduction. The annual extremely maximum temperature and extremely minimum temperature are both on the rise, and the amplitude of the latter is larger than that of the former. From 1960s, the average temperature, average maximum temperature and average minimum temperature turned rising in Dabie Mountain of West Anhui Province. The abnormally warm years are 1967, 1968, 206, 207, 1998 and 2013, while the abnormally cold years are 1967 and 1981.
Consistency Analysis of two Lightning Systems in Hubei Province
Authors: Li Guoliang , Li Jun , Li Xiang , Yuan Fang 
Published: January 2021

Abstract
In order to study the Hubei lightning locating system detection efficiency in 2015-2016, this paper adopts the method of mathematical statistics, compared and analyzed the distribution structure, detection efficiency, space-time distribution and lightning current characteristics between two lightning systems. The results show that the more sub-stations and the smaller the baseline distance are, the higher the detection efficiency is. The average number of cloud and ground lightning in 3D lightning locating system is 86.8% more than that in 2D system, and the proportion of positive ground lightning is slightly higher than that in 2D system. The positive and negative flashover of the 3D system are between 0-90kA, Positive current of 10-20kA and negative current of 20-30kA are the most. The positive and negative lightning in 2D system are between 10-100kA, the current has the highest percentage of 20-30kA and the lowest percentage of 10-20kA. The 3D system detection efficiency and lightning density distribution are better than 2D system. two sets are consistent in lightning time characteristics, geographical distribution and intensity distribution rules, which plays an important role in lightning disaster investigation, lightning monitoring and early warning and other business applications.
Rainfall Variety and its Effect to Runoff Reduction of Status Year in the Region from Hekouzhen to Longmen
Authors: Jin Shuangyan , Ma Zhijin , Zhao Wenrong , Gao Yajun , Guo Shaomeng 
Published: January 2021

Abstract
The natural runoff of the Yellow River has been reduced sharply since 2000. Based on rainfall network of 1966 and 1977 are built on GIS platform, the trend of rainfall variety in 1956∼2013 is analyzed. The turning point of runoff of natural period and human activities impact period in the eighteen tributaries was analyzed with the method of orderly clustering and MWP test and so on. The model was established with the data from 1956 to the turning point year, and the runoff during this period was regarded as benchmark value. The runoff variety and the impacts brought by rainfall in the status series from 2007 to 2013 were analyzed by equation of runoff division. It is showed that natural runoff reduced 5.411 billion cubic meters, among which brought by rainfall not negative value but increased 0.424 billion cubic meter.
Annual natural runoff forecast of Panjiakou Reservoir
Authors: Wang Zhe , Guo Huifang , Li Taotao , Zhu Jingsi 
Published: January 2021

Abstract
Haihe River Basin is an area with frequent droughts and floods in China. There is a serious shortage of water resources in the Haihe River Basin. The average annual water resources in the basin are 37.2 billion cubic meters, with a per capita share of 305 cubic meters, 1/7 of China. which is one of the serious water shortage areas in China. Panjiakou Reservoir is a large reservoir in the Haihe River Basin, with a water storage capacity of 2.93 billion cubic meters. It is responsible for the water supply of Tianjin, Tangshan and other large and medium-sized cities. The reasonable operation of Panjiakou Reservoir plays an important role in Haihe River Basin. In this paper, the support vector machine model is used to predict the runoff of Panjiakou Reservoir. The prediction results can provide reference for the reasonable operation of Panjiakou Reservoir.
The spatial distribution of soil nutrients matter and variation characteristics of Datong Abandoned Coal Mine area in Huainan City
Authors: Sun Xianbin , Sun Liangping , Zhang Xing , Li Guangyao , Yu Maohui 
Published: January 2021

Abstract
This paper describes the analysis of nutrients matter in soil sampled from Datong abandoned mining area in Huainan City. Spatial interpolation in GIS is applied to the revelation of spatial distribution of nutrients matter. Results show that: In abandoned land in Datong coal mining, the level of available phosphorus in soil was very short and the following grades, and the level of nitrogen was short grades, and the level of organic matter was medium and the following grades. Distribution of these heavy metals present a stronger spatial relevance because their spatial pattern are mainly influenced by natural factors such as complex micro-geomorphology, vegetation, topography, strongly human disturbance and other structural factors. All of spatial variability was middle and small scale. Characteristic of spatial variation was relation with the complex distribution object. Random factors, such as sampling interval, soil type and so on, play a relatively greater role in spatial variability of nutrients matter.
Empirical Study on Environmental Pollution effect of FDI
Authors: Yan Xiaoming 
Published: January 2021

Abstract
This paper combs the relevant theories and literature, and analyses the three impact mechanisms of FDI on environmental pollution which includes economic scale, technology and structural effects , This paper selects foreign direct investment panel data of 29 provinces in China in 2009-2017, explores the impact of foreign direct investment on China’s environmental pollution, verifies that the “pollution shelter” hypothesis does exist in China, and concludes that the inflow of foreign direct investment aggravates China’s environmental pollution, and based on this, the paper puts forward targeted policy recommendations.
Analysing PM2.5 concentrations using MODIS and monitoring measurements for Shanghai area
Authors: Miao Lizhi , Wen Yi , Ren Yanhui 
Published: January 2021

Abstract
Analyzing PM2.5 concentrations from remote sensing images and surface measurements using the model of aerosol optical depth (AOD) is a popular method to evaluate the exposure to PM2.5 in some geographic regions. For analyzing the ground-level PM2.5 density on a daily basis using satellite-derived AOD in Shanghai area, we use Aqua MODIS (Moderate Resolution Imaging Spectroradiometer) to obtain the AOD values at 3-km resolution by dark pixel. However, AOD values are missing in many regions caused by processing method and imaging process. Interpolating the AOD values to extend the coverage area of MODIS and integrating the surface measurements, we filter the AOD values and PM2.5 measurements. The analysis results indicate that the correlation coefficient is 0.54 in Shanghai area. Satellite derived mean PM2.5 for Shanghai was 42.69 ug/m3 during the study period (Jan 2016 to Dec. 2018), whereas mean PM2.5 is highest in winter period (61.68 ug/m3), and lowest in autumn period (31.4 ug/m3) over study period in study area.
Wavelet Analysis on Temperature and Precipitation Changes in Dabie Mountain of West Anhui
Authors: Zhao Yongmei , Luo Yuan 
Published: January 2021

Abstract
The wavelet analysis method is applied to analysis of multi-level time change characteristics of temperature and precipitation in Dabie Mountain based on the meteorological observation data of five stations in Dabie Mountain from 1960 to 2013. According to results, the temperature shows oscillation periods of 22 years and 10 years in Dabie Mountain, West Anhui. While the precipitation shows an oscillation period of26 years. The change relationships of temperature and precipitation are not the same based on different time scales. From the scale of 3 years, to 10 years and 20 years, the out-of phase becomes weaker. The tendency of consistence appears gradually.
Numerical analysis of concrete temperature stress at different loading ages
Authors: Liu Longlong , Zhang Zhaosheng , Huangfu Zehua , Huang Dahai 
Published: January 2021

Abstract
This paper investigates the thermal stresses of low-heat cement concrete under different loading ages, and thermal stresses were calculated with different compensation cycles by the Boltzmann superposition principle. An application of the Boltzmann superposition principle on the temperature stress test shows how the formulation may be used to evaluate the mechanical properties of low-heat cement concrete and how the accuracy of calculated stresses applies to measured stresses. The comparison between measured stresses and the simulated results shows good agreement under different compensation cycles, which indicates that the thermal stresses can be well estimated via the line superposition. Furthermore, these experiment results indicate that the maximum compression stresses increase rapidly with the increment of curing ages while the cracking stresses have subtle differences.
Research on slope investigation using high density resistivity method
Authors: Liu Fei , Yang Zhong 
Published: January 2021

Abstract
In this paper, high-density resistivity of the north bank of Huangming Reservoir in Yuyao City was detected by the Wenner device. Through the detection of multiple sections in the longitudinal and transverse sections, the distribution rules of the rock mass of the slope are summarized, and the weathering grade of the rock is judged. The research results will provide a strong basis for the disaster prevention and mitigation work in the later period.