bluuebunny/crossref_metadata_2025_split huggingface dataset:
Single Sea Surface Image Dehazing via Multi-scale Concatenated Attention Network
Authors: He Xin , Ji Wanfeng , Wang Zheng , Zhang Yaoqing 
Published: July 2021

Abstract
Haze degrades obscures and content information of sea surface images, which can negatively impact the navigation safety of the intelligent ship in real-time systems. Therefore, it is imperative to develop algorithms that effectively remove haze and make the intelligent ship have higher environmental adaptability. In this paper, we propose a novel Multi-scale Concatenated Attention Network (MCA-Net) to address this problem. Specifically, we use the concatenation operation to connect multi-scale residual blocks (MRB), while introducing the channel attention mechanism for guiding the hazy region feature extracting. Extensive experiments on both synthetic datasets and real sea surface images, which demonstrate our proposed method outperforms are better than other recent dehazing approaches.
Research on Fault Diagnosis Method of Switch Machine Based on KFCM
Authors: kun Song Ya , Tao He , Yong cheng Wu 
Published: July 2021

Abstract
as one of the most important equipment in railway system, the failure of switch machine has a great impact on the safety and benefit of railway transportation. In order to realize the rapid fault diagnosis of switch machine, according to the power curve of switch machine detected by centralized monitoring system of railway signal, a new fault diagnosis method of switch machine based on variational mode decomposition (VMD) and improved fuzzy clustering algorithm is proposed. Firstly, VMD decomposition method is used to preprocess the collected fault data to remove the outliers and noise; then, the kernel fuzzy c-means clustering algorithm is used to classify different fault types into classes, and the classification results are obtained according to the dynamic clustering graph, so as to realize fault diagnosis. Through simulation analysis and experimental data verification, the algorithm can accurately extract fault features and support multiple fault detection at the same time, which effectively improves the accuracy and efficiency of S700K switch machine fault diagnosis.
A New Estimation Method of the PID Controller In Automatic Train Operation Systems
Authors: Cao Fang , Wang Jin feng , Zhao Shuai 
Published: July 2021

Abstract
PID controller plays an important role in Automatic Train Operation systems. Many researches have been done on the PID parameters estimation. However, the traditional models simplified the characteristics of the trains in different speeds and operation modes. It was difficult to overcome the problems with different kinds of algorithms based on the traditional models, especially the accuracy requirement of the stopping distance. In this paper, a new model of the PID controller was proposed based on the practical train operation stages. And the different response time delay was considered besides of the transmission time delay. With this new model, an Improved Fruit Fly Optimization Algorithm was applied. The tracking performance were greatly improved both on running distance and real time. The simulation results showed a better performance than the traditional methods.
Topology Identification of Low-voltage Transformer Area Based on Improved Particle Swarm Algorithm
Authors: Liu Han , Huizhu Xian , Dapeng Duan , Fengming Lv , Jian Sun , Haofei Mao , Qiang Wang 
Published: July 2021

Abstract
With the continuous changes in the user-side power environment, the low-voltage distribution network has become more and more complex, which brings great challenges to the line loss management and topology identification of the transformer area. To solve the shortcomings of traditional particle swarm optimization such as poor ergodicity of population initialization and easy to fall into premature convergence, this paper proposed a K-means clustering analysis algorithm based on GA-CPSO. First, on the basis of the traditional particle swarm algorithm, the chaotic shrinkage factor was introduced and the parameters were optimized. Secondly, the genetic algorithm was combined with the chaotic particle swarm optimization algorithm, the crossover and mutation operations of the genetic algorithm were used to establish an information exchange mechanism between particles, and it was combined with the K-means clustering method. The simulation results on the test benchmark function show that the improved particle swarm optimization algorithm in this paper has significantly improved the search speed and optimization accuracy. Finally, taking an actual transformer area as an example, the method was applied to the transformer area topology recognition analysis. Using the electrical parameters such as voltage, current, and active power obtained from the monitoring terminal as sample data, a simulation analysis was carried out to verify the effectiveness and feasibility of the algorithm. The performance parameters of different algorithms had been compared and analyzed through multiple experiments, and it was proved that this method can effectively improve the accuracy of platform topology recognition, and has strong practicability and generalization.
Petroleum Equipment Industry to Digitalization—Taking Jereh Equipment as An Example
Authors: Ming Zhao , Sihan Liu 
Published: July 2021

Abstract
The Report on the Work of the Government 2021 voiced that China will strive to develop the Internet in the next few years. It is the fourth year that the industrial Internet has been written in the government report. With the combination of national promotion and social development needs, China’s industrial Internet has experienced unprecedented growth in recent years. Based on the case analysis of Jereh’s IOT, combining theory and practice, this paper studied the development trend of the petroleum equipment industry’s digital transformation and the application scenarios of the Industrial Internet of Things. Through realizing intelligent industrial operations by using the data analysis results obtained by business transformation of machine, computer, and personnel, and based on the application of Internet of Things technology, Jereh’s IOT aims to promote the high integration of enterprise informatization, equipment informatization and operations process informatization, so as to achieve digital and lean industry management.
A Design of Intelligent Garbage Bin System
Authors: Zha Yang , Zhou Min , Yang Jiale , Yang Yongjie 
Published: July 2021

Abstract
Garbage classification is more and more significant recent years. In order to promote the implementation of garbage classification and the improvement of intellectualization of urban sanitation work, a new type of intelligent garbage bin system is designed, which includes the bottom control part, android app and IOT cloud platform. Firstly, the system controls the inlets of intelligent garbage bin through interaction with android app, which realizes the function of ordinary garbage can. On top of that, the bottom control part collects all kinds of data of garbage bin by using some external sensors. And then the data will be reported to Android and Android will report that to cloud platform. Cloud platform server then transmits data to monitoring platform, which facilitates data statistics and the removing of garbage. By deploying the system, garbage classification can be promoted and the status of garbage can be effectively monitored, which will significantly improve garbage recovery efficiency and sanitation work level.
Research on the model and algorithm of the flexible operation sequence of the first-level maintenance in the EMU depot
Authors: Zhao Peng , Han Bao Ming 
Published: July 2021

Abstract
Most of the first-level maintenance of Electric Multiple Unit (EMU) adopts the form of fixed sequence operation, known as “washing-maintenance”. Because of the limitation of the line capacity and the inconsistent arrival time of EMUs, a fixed sequence operation may give rise to such problems as longer waiting time, idle lines and waste of maintenance capacity. To solve these problems, a non-linear integer model with a flexible operational sequence of the first-level maintenance of the EMU depot is proposed in this paper. The proposed model aims at minimizing the latest completion time, taking into account the constraints such as the operation sequence of the same EMU, the limitation of simultaneous operation on the same line and the time requirement for EMU to enter and leave the yard. In the proposed model, genetic algorithm is employed. To a further level, in this paper, an application of the proposed model used in Taiyuan EMU depot is presented. With a comparison of two modes, namely, the fixed sequence mode and the fixed sequence plus manual washing mode, the case of the application by Taiyuan EMU depot provides the verification for the feasibility and validity of the model proposed. The result of the application suggests that the flexible operation sequence mode bring about improvement with regard to reducing waiting time, optimizing line utilization, shortening the latest completion time, and enhancing both working efficiency and ability of the first-level maintenance.
Gray Correlation Comprehensive Evaluation of Port Intermodal Transport Development Level Based on Expert Group Decision-Making Weight Optimization
Authors: Nan Yu , Yu Cao , Ziying Guo 
Published: July 2021

Abstract
This paper adopts the weight optimization method based on expert group decisionmaking technology to optimize the weights of the influencing factors affecting the development level of port intermodal transport, and then adopts the gray correlation comprehensive evaluation method to evaluate the development level of port intermodal transport in China from three aspects of supply capacity, service level and development environment. The results prove that the evaluation method is practical and effective, and can provide support for the evaluation of the development level of port intermodal transport in China.
Deadlock-free and path coordination algorithm for Cooperative Multi-task Allocation Problem with Target Priority Constraints
Authors: Zhao Yiyang , Zhou Deyun , Li Xiaoyang , Yang Zhen , Zhang Kai , Zeng Lina 
Published: July 2021

Abstract
In this paper, we propose a cooperative multi-task allocation problem with target priority constraints (CMTAPTPC) for unmanned aerial vehicles (UAVs). For solving the deadlock problem, a deadlock detection and elimination method, including target priority constraints, is introduced in the graph representation framework. Furthermore, an innovative waitable path coordination (WPC) algorithm is proposed to coordinate the flight path that violates time constraints. It adopted some strategies to reduce the complexity of coordination and save the energy of the UAVs. In the simulation part, a representative complex scenario is designed to illustrate the rationality and effectiveness of the CMTAPTPC model and WPC algorithm.
Study on the Setting Conditions of High Density and Small Spacing Compound Interchange in Stereo-Compound Expressway
Authors: Weibin Zhong , Jianbei Liu , Weiwei Liu , Yuanyuan Jin 
Published: July 2021

Abstract
Due to the limited land space and insufficient design space, the high-density and small-spacing compound interchange needs to adopt the collector-distributor lane without meeting the minimum design spacing. This paper combines the configuration of the interweave section, and the setting requirements of the lanes’ number are refined. Then, it is analyzed the characteristics of lane change behavior in the collector-distributor lane, and the length of interweave section in different design speeds and forms is calibrated. On the basis, the service level of the interweaving area under different traffic needs and different interweaving area lengths is obtained. Finally, VISSIM simulation software is used to verify the calculation results. The results show that when the steering traffic is large, it is not recommended to use the single-in-single-out A and single-in-single-out B design, and single-in-double-out B design should be selected according to actual needs.
Research on Agricultural Product Cold Chain Logistics Management Based on Supply Chain Network Structure
Authors: Li Huihui , Li Na 
Published: July 2021

Abstract
he thesis first analyzes the supply chain network structure for the establishment of a new agricultural product supply chain system. This article is to construct a new agricultural product supply chain construction plan, establishes an innovative idea, the business process is urban fresh agricultural product e-commerce, and builds an urban standard distribution model A data-based cold chain integrated distribution model is proposed. This research is mainly to realize the joint operation and management of cold chain logistics and fresh products, and it is necessary to strengthen the coordination of demand-oriented agricultural industry organizations, the coordination of technological innovation of circulation enterprises, and the coordination of the implementation of innovative supply. As a result, the safety mechanism construction of the new agricultural product supply chain, including dynamic monitoring, detection modules and emergency handling systems, has guiding significance for the efficiency of agricultural cold chain logistics circulation.
A land use optimization model of the multimodal passenger transportation hub on TOD mode based on strategy analyses
Authors: Luo Guanliang , Shao Chunfu , Dong Chunjiao , Zhen Li 
Published: July 2021

Abstract
With the acceleration of urbanization, Station City integration and TOD mode have become the mainstream of the multimodal passenger transportation hub construction. Based on the single factor analyses of SWOT, this paper puts forward a cross factor analyses method which is suitable for the multimodal passenger transportation hub on TOD mode. Through three circle spatial structure and taking the plot ratio of various types of land as decision variable, the land use optimization model is established with the goal of maximizing public transport passenger flow, building good living and commercial conditions in the region and land value-added. Finally, this paper takes Beijing Fengtai station as an example. The results of SWOT analyses show that Fengtai station should focus on solving the problem of traffic distribution in the first circle, optimize the land use, form TOD area and promote land value-added in the second circle. The results of land use optimization model show that the current situation of residential land use around Fengtai station can meet the demand of TOD mode. However, the plot ratio of commercial and business land is low and the area is tight, so it is suggested to improve the plot ratio index of this types of land.
Deep Learning with Bidirectional Long Short-Term Memory for traffic flow Prediction
Authors: Xue Song , Shao Chunfu , Wang Shengyou , Zhuang Yan 
Published: July 2021

Abstract
With the development of cities, the total number of trucks has increased year by year. Traffic flow forecasting has become an indispensable part of the cargo transportation industry and directly affects the development of the transportation industry. In the field of traffic flow prediction, Long Short-Term Memory(LSTM) model has advantages in processing time series, but it cannot extract the periodicity in time series. Therefore, in this experiment, a Bidirectional Long Short-Term Memory (BLSTM) model was constructed to predict traffic flow in the road network. It is worth mentioning that this article considers the non-parametric model autoregressive integrated moving average model (ARIMA) and the parametric model recurrent neural network (RNN) to compare and analyze with LSTM. Data from Guangwu Toll Station, Zhengzhou city, China were used to calibrate and evaluate the models. The experimental results show that the performance of RNN based on deep learning such as BLSTM and LSTM model is better than that of ARIMA. In order to better illustrate the advantages of BLSTM model, we comprehensively considered the performance effects of four models under morning peak, evening peak and flat peak. Experiments have proved that BLSTM has good nonlinear fitting ability and anti-noise ability, and the average prediction accuracy reaches 92.873%.
Intelligent Tidal Lane System Based on Vehicle Attribute Recognition Algorithm and Related Laws and Regulations
Authors: Tong Zeng , Xing Congxin , Zeng Ziming , Lai Binger 
Published: July 2021

Abstract
In this paper, an intelligent tidal lane combined with artificial intelligence technology which can adapt to the change of the number of vehicles is designed. The recognition of vehicle position and the direction of vehicle front and rear are recognized by using the vehicle attribute recognition technology based on artificial intelligence. In order to alleviate the morning and evening peak of traffic flow, holiday travel or emergencies caused by two-way lane traffic imbalance, the tidal lane can automatically switch the direction of tidal lane according to the number and direction of vehicles on the two-way road. In addition, we study and analyze the construction of laws and regulations of tidal lane, explore the problems and put forward some suggestions to protect the interests of travelers and maximize social benefits.
Traffic prediction based on GCN-LSTM model
Authors: Wu Zhizhu , Huang Mingxia , Zhao Aiping , lan Zhixun 
Published: July 2021

Abstract
Traffic flow prediction is an important part of intelligent traffic management system. Because there are many irregular data structures in road traffic, in order to improve the accuracy of traffic flow prediction, this paper proposes a combined traffic flow prediction model based on deep learning graph convolution neural network (GCN), long-term memory network (LSTM) and residual network (RESNET). GCN is used to extract the features of topology structure in traffic data, LSTM is used to extract the features of time structure, combined with ResNet to optimize the overall model, reduce the occurrence of gradient disappearance or explosion in network degradation, and finally achieve the prediction of traffic flow. According g to the experimental results, the combined traffic flow prediction model used in this paper is closer to the actual traffic flow occurrence than the traditional convolutional neural network model (CNN), and the accuracy is improved.
Simulation of Traffic Microcirculation Optimization in Residential Area
Authors: Liangliang Chen , Rongrong Li , Aizeng LI 
Published: July 2021

Abstract
Nowadays, there are many congestion problems in urban main roads, so the traffic flow on the main roads is drained to small branches, the density of road network is increased, a more perfect traffic network is formed, and many vehicle diversion paths are formed. Become one of the effective ways to alleviate traffic congestion. Through the optimization of traffic microcirculation network in residential area and the optimization of intersection signal timing scheme by Webster method, and the data analysis and simulation by using Aidaroe software and Vissim software, It can be concluded that the service level and network density of intersections around residential area are improved and the traffic condition is improved obviously. The results show that this optimization study has an important effect on improving the operation of traffic microcirculation in residential area and the quality of life of residents, realizing the efficiency of traffic microcirculation in residential area and affecting the whole urban traffic system.
Application of Oblique Photogrammetry in Intelligent Transportation System
Authors: Zhang Puheng , Xiao Yanping , Chen Guangqiang , E Jiming , Li Ting , He Shengwen 
Published: July 2021

Abstract
Remote sensing is one of the most effective spatial management tools at home and abroad. Oblique photogrammetry technology, as one representative, can help quickly and accurately obtain the 3D model of the surface, roads and buildings, and provide a more intuitive database for transportation. This paper introduces the production procedure of map image and real-time 3D model, and takes the intelligent transportation system as an example to display the operation flow and application of oblique photogrammetry technology. Oblique photography images can be embedded into intelligent transportation system to comprehensively display traffic and environmental information in detail. Combined with real-time traffic monitoring data, the virtual scene can be more realistic, and user experience can be greatly promoted. Thus, traffic scheduling and control can be more effective and efficient.
A new analysis and prediction model of road traffic based on open community
Authors: Feng Yujie , Li Deyi , Wang Jiufeng 
Published: July 2021

Abstract
This paper aims to optimize the road network structure of open residential areas in China. Firstly, the nonlinear coefficient R0 = t3/T is used to study the road condition, using Matlab programming to calculate road network saturation LOS, establish a reasonable evaluation index system of community opening. Then the theoretical model of road resistance function is established, the influence coefficient η of each factor is determined, the traffic influence degree model is established, and the vehicle passing model is obtained. Finally, three different types of community A, B and C are constructed, and then traffic simulation is carried out according to Vissim software. The conclusion is that the degree of road traffic pressure relief is the largest in one type of community, and the least degree in type B community.
Research on fire fighting and emergency rescue of all-electric vehicle traffic accident
Authors: Li Chao , Liu Liwen , Lin Shuangshuang , Liu Shuai 
Published: July 2021

Abstract
With the popularization of all-electric vehicles, the application of all-electric vehicles in traffic accidents is more and more. It is also difficult to solve the problems such as the selection of fire extinguishing agent for electric vehicles, the update control of high-pressure protection and emergency rescue. Based on the comparison and analysis of the normal operation of automatic sprinkling extinguishing agent and the reaction conditions inside lithium battery, this paper puts forward the updating method of selecting and controlling extinguishing agent for all-electric vehicle. And by analyzing the characteristics and danger of all-electric vehicle traffic accident, the insulation protection and power off method for all-electric fire and emergency rescue are also mentioned in this paper.
Nonlinear Dynamic Analysis of Multi-vehicle Vehicle-bridge Coupling System
Authors: Shen Jian , Zhuo Jin-hao , Wu Lang , Liu Xiao-yun 
Published: July 2021

Abstract
By analyzing different nonlinear models of vehicle-bridge coupling vibration when multiple vehicles travel on a bridge, this paper proposes the nonlinear vibration equation of multiple vehicle vehicle-bridge coupling. A comprehensive analysis is conducted on the quarter vehicle model, the nonlinear motion model of the bridge, and the coupled coupling equation of the vehicle and bridge. The vehicle-bridge coupled nonlinear analysis model of a single vehicle is established, and the correctness of the results calculated by the model is verified by calculation examples. In addition, taking the three-span continuous beam bridge with equal cross section and equal span as an example, this paper studies the driving conditions of multiple vehicles respectively from the influence of vehicle number, vehicle spacing and vehicle speed on the dynamic response value of the bridge. The results show that vehicle speed, vehicle number and vehicle spacing have significant influence on the dynamic response value of the bridge.