Frontiers of Traffic and Transportation Engineering最新文献_第4页

Neural network prediction model for ultimate collision force in ship-bridge collision 船桥碰撞极限碰撞力的神经网络预测模型

Frontiers of Traffic and Transportation Engineering Pub Date : 2022-11-21 DOI: 10.1117/12.2652792

Tianqi Wang

{"title":"Neural network prediction model for ultimate collision force in ship-bridge collision","authors":"Tianqi Wang","doi":"10.1117/12.2652792","DOIUrl":"https://doi.org/10.1117/12.2652792","url":null,"abstract":"The numerical prediction of ultimate collision force in ship-bridge collision accident has a great influence on the safety of pier and bridge superstructure. However, ship-bridge collision problem is a complex nonlinear dynamic problem, and the linear empirical formula in the existing domestic and foreign standards cannot reflect the numerical value of collision force. In this paper, based on the data of established finite element model, the influence factors of maximum collision force are analyzed, four factors such as the time at which the maximum collision force occurs in the collision force curve, ship speed, hull quality and a coefficient which is related to the elastic deformation coefficient of the specimen of collision block (hull) and bridge pier are selected as the input of networks. BP and RBF neural network prediction models are established to predict the ultimate collision force of ship bridge collision. Combined with the prediction results, poor prediction accuracy of BP neural network is believed to be due to the over-fitting problem. Therefore GA-BP and PSO-BP algorithms are introduced to optimize the original BP neural network, of which the relative errors are 2.38% and 2.24% respectively and prediction accuracy is higher. The results show that it is feasible to predict the ultimate collision force of ship-bridge collision by using neural networks. Especially for the over-fitting problem of BP prediction model, the prediction accuracy of PSO-BP network after solving the over-fitting problem is convincing. The research in this paper successfully proves that the prediction of ultimate collision force by neural network in ship-bridge collision field is feasible with high precision accuracy, which provides scientific guidance and reference for the engineering safety of piers and other substructures in bridge design and construction.","PeriodicalId":116712,"journal":{"name":"Frontiers of Traffic and Transportation Engineering","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132424391","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Data acquisition system of Internet of Things based on Kohonen multi-protocol adaptation 基于Kohonen多协议适配的物联网数据采集系统

Frontiers of Traffic and Transportation Engineering Pub Date : 2022-11-21 DOI: 10.1117/12.2652742

Changhua Wang, Xiliang Zhang, Xihao Zhu, Hancheng Yu, Shuangjing Ni

{"title":"Data acquisition system of Internet of Things based on Kohonen multi-protocol adaptation","authors":"Changhua Wang, Xiliang Zhang, Xihao Zhu, Hancheng Yu, Shuangjing Ni","doi":"10.1117/12.2652742","DOIUrl":"https://doi.org/10.1117/12.2652742","url":null,"abstract":"With the development of highway information, according to the actual demand of highway electromechanical equipment management, this paper designs a multi-protocol internet of things data acquisition system to realize instant messaging and data sharing of electromechanical equipment. The Kohonen neural network is used to train the adaptive module of the existing input protocol. According to the eigenvalues of the header, the shaping number of the end bytes and the length of a single packet of the protocol, the function of automatically selecting the appropriate protocol is realized. In the later stage, the ability to learn more protocol adaptation independently can be realized by updating the protocol knowledge base on the internet of things platform. The results show that the average processing time of Kohonen network for each protocol data is about 109ms, and the average recognition rate reaches 95.45%. Kohonen network can be applied in traffic engineering field and realize the conversion of various information data of electromechanical equipment with different protocols into unified information data through protocol conversion rules.","PeriodicalId":116712,"journal":{"name":"Frontiers of Traffic and Transportation Engineering","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117222490","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

The level of developments of green logistics in Guangdong Province 广东省绿色物流的发展水平

Frontiers of Traffic and Transportation Engineering Pub Date : 2022-11-21 DOI: 10.1117/12.2652737

Fan Zhang, Leili Liu

引用次数: 0

Study on optimization of rural passenger and cargo bus based on ant colony algorithm 基于蚁群算法的农村客货客车优化研究

Frontiers of Traffic and Transportation Engineering Pub Date : 2022-11-21 DOI: 10.1117/12.2652724

Jiamin Dai, Fengli Zheng, Huaqiong Liu

引用次数: 0

Scenario-based requirements analysis for Chinese new train control system 基于场景的中国新型列控系统需求分析

Frontiers of Traffic and Transportation Engineering Pub Date : 2022-11-21 DOI: 10.1117/12.2652804

Haotong Xu, Kaicheng Li, Lei Yuan, Qiang Fu

引用次数: 0

Construction of evaluation index system for investment decision-making stage of automated container terminal 自动化集装箱码头投资决策阶段评价指标体系的构建

Frontiers of Traffic and Transportation Engineering Pub Date : 2022-11-21 DOI: 10.1117/12.2652715

Wen Jian, Ming Jin, Peng Cai

引用次数: 0

Intelligent logistics SaaS platform design 智能物流SaaS平台设计

Frontiers of Traffic and Transportation Engineering Pub Date : 2022-11-21 DOI: 10.1117/12.2652329

Xinyi Lu, Xinhong Lv, Huaqiong Liu

引用次数: 0

The construction of urban common distribution information platform under the mode of express delivery + takeaway 快递+外卖模式下的城市共同配送信息平台建设

Frontiers of Traffic and Transportation Engineering Pub Date : 2022-11-21 DOI: 10.1117/12.2652699

Haoming Ma, Yuyao Zhao, Huaqiong Liu

{"title":"The construction of urban common distribution information platform under the mode of express delivery + takeaway","authors":"Haoming Ma, Yuyao Zhao, Huaqiong Liu","doi":"10.1117/12.2652699","DOIUrl":"https://doi.org/10.1117/12.2652699","url":null,"abstract":"With the rapid development of logistics industry, express delivery industry and takeaway industry ushered in new opportunities, and urban end distribution as an important part of logistics distribution will directly affect the efficiency of the whole distribution. In view of the current situation of multi-agent urban distribution service, fragmented distribution resources and low distribution efficiency, this paper applies the joint distribution mode to the urban “express delivery + takeaway” distribution and constructs the urban common distribution information platform. Combined with the characteristics of express delivery business and takeout business, the platform is divided into four modules: user layer, platform logic layer, access layer and database layer. Then, detailed planning and development of each module are carried out. Big data, RFID, GIS geographic services, cloud computing and other technologies are used to build a common urban distribution information platform. Through the construction of urban common distribution information platform, it provides reference for future intelligent logistics management.","PeriodicalId":116712,"journal":{"name":"Frontiers of Traffic and Transportation Engineering","volume":"56 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133175203","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Optimization analysis of inbound and outbound efficiency of four-way shuttle storage system 四向梭式仓储系统进出库效率优化分析

Frontiers of Traffic and Transportation Engineering Pub Date : 2022-11-21 DOI: 10.1117/12.2652515

Zhao Fu, Yuan-yi Xia, Huaqiong Liu

引用次数: 0

Practice of the travel forecasting model of CCX-expressway accommodating tourism travel ccx高速公路旅游出行预测模型的实践

Frontiers of Traffic and Transportation Engineering Pub Date : 2022-11-21 DOI: 10.1117/12.2652609

Zhou Liang

引用次数: 0