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2020 IEEE International Conference on Industrial Application of Artificial Intelligence (IAAI)最新文献

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Modular Design of Distance Self-Learning Innovation and Entrepreneurship Teaching System Based on Cloud Platform 基于云平台的远程自学创新创业教学系统模块化设计
2020 IEEE International Conference on Industrial Application of Artificial Intelligence (IAAI) Pub Date : 2020-12-25 DOI: 10.1109/iaai51705.2020.9332890
Zhu Tian-Yuan
{"title":"Modular Design of Distance Self-Learning Innovation and Entrepreneurship Teaching System Based on Cloud Platform","authors":"Zhu Tian-Yuan","doi":"10.1109/iaai51705.2020.9332890","DOIUrl":"https://doi.org/10.1109/iaai51705.2020.9332890","url":null,"abstract":"In order to improve the performance of the remote self-learning innovation and entrepreneurship teaching system, which is affected by the hardware and software of teaching equipment, the modular design of remote self-learning innovation and entrepreneurship teaching system based on cloud platform is proposed. Through login verification and course query, the user management module is designed. The teaching module of the system is designed by using the design of course setting and video learning. The online programming module is designed through code editing, code execution and code synchronization. Finally, combined with the design of testing practice module, the modular design of remote self-learning innovation and entrepreneurship teaching system is carried out. The test results show that the remote self-learning innovation and entrepreneurship teaching system based on cloud platform has high performance and meets the teaching requirements of remote self-learning innovation and entrepreneurship.","PeriodicalId":232194,"journal":{"name":"2020 IEEE International Conference on Industrial Application of Artificial Intelligence (IAAI)","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133316263","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: 1
Numerical simulation analysis of extrusion shield tunnel construction process based on virtual reality 基于虚拟现实的挤压盾构隧道施工过程数值模拟分析
2020 IEEE International Conference on Industrial Application of Artificial Intelligence (IAAI) Pub Date : 2020-12-25 DOI: 10.1109/iaai51705.2020.9332856
Linh T. Nghe
{"title":"Numerical simulation analysis of extrusion shield tunnel construction process based on virtual reality","authors":"Linh T. Nghe","doi":"10.1109/iaai51705.2020.9332856","DOIUrl":"https://doi.org/10.1109/iaai51705.2020.9332856","url":null,"abstract":"The traditional numerical simulation analysis method lacks the detection of the matter-element model, which leads to the numerical simulation analysis results of the tunnel construction process under complex conditions, and it is difficult to find the risk factors. Therefore, based on the virtual reality technology, the numerical value of the extrusion shield tunnel construction process is studied. Simulation analysis method. This method constructs the matter-element model of the shield tunnel construction by calculating the temperature field of the extruded shield tunnel construction; uses virtual reality technology to detect the matching degree of the tunnel structure, and realizes the numerical analysis of the dynamic characteristics of the extruded shield tunnel. Test results: the numerical simulation analysis method of tunnel construction process in this study has higher expert evaluation results, which shows that the construction parameters obtained under the application of virtual reality technology are more practical.","PeriodicalId":232194,"journal":{"name":"2020 IEEE International Conference on Industrial Application of Artificial Intelligence (IAAI)","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115610505","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
Image Classification Algorithm Based on Improved AlexNet in Cloud Computing Environment 云计算环境下基于改进AlexNet的图像分类算法
2020 IEEE International Conference on Industrial Application of Artificial Intelligence (IAAI) Pub Date : 2020-12-25 DOI: 10.1109/IAAI51705.2020.9332891
Yang Lu
{"title":"Image Classification Algorithm Based on Improved AlexNet in Cloud Computing Environment","authors":"Yang Lu","doi":"10.1109/IAAI51705.2020.9332891","DOIUrl":"https://doi.org/10.1109/IAAI51705.2020.9332891","url":null,"abstract":"In the cloud computing environment, the traditional classification algorithms often ignore the feature relationship between images, which leads to unstable classification process, poor accuracy of classification results and other problems, which can not achieve the ideal classification effect. An image classification algorithm based on improved AlexNet is proposed and designed. After preprocessing the collected images, such as normalization, mean value and standardization, the convolutional nerve is introduced to train the features of the standard images. On this basis, the image classification algorithm model based on improved AlexNet is established. Through the optimization training of the classification model, the high-level semantic features of the image are extracted, and the process of image classification and calculation is realized. The experiments show that the improved AlexNet image classification algorithm improves the accuracy and stability of image classification, and has good effectiveness and robustness, which provides a good reference for the development of network technology.","PeriodicalId":232194,"journal":{"name":"2020 IEEE International Conference on Industrial Application of Artificial Intelligence (IAAI)","volume":"104 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114472726","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: 8
Crack Detection Method of Shadow Asphalt Pavement based on Cuckoo Search 基于布谷鸟搜索的阴影沥青路面裂缝检测方法
2020 IEEE International Conference on Industrial Application of Artificial Intelligence (IAAI) Pub Date : 2020-12-25 DOI: 10.1109/IAAI51705.2020.9332894
Weiwei Zhan, Xulan Gui, Xinghang Long
{"title":"Crack Detection Method of Shadow Asphalt Pavement based on Cuckoo Search","authors":"Weiwei Zhan, Xulan Gui, Xinghang Long","doi":"10.1109/IAAI51705.2020.9332894","DOIUrl":"https://doi.org/10.1109/IAAI51705.2020.9332894","url":null,"abstract":"The daily detection of shadow asphalt pavement cracks, there are multiple sets of zero points in the asphalt pavement image, which causes the detection process to take too long. Therefore, a method of shadow asphalt pavement crack detection based on cuckoo search is studied. According to the three-dimensional laser data acquisition system, the asphalt pavement crack characteristics are extracted. The zero pixel of the adjacent image area is processed by median filter. The cuckoo search algorithm is used to complete the crack search, and the crack skeleton is extracted to complete the crack detection of the shadow asphalt pavement. A section of asphalt pavement data collected by wireless laser in a certain area is used as experimental data. Three different asphalt crack samples are prepared. Two traditional crack detection methods and the crack detection methods studied in the article are used to conduct experiments. The results show that the proposed crack detection The method requires the shortest detection time.","PeriodicalId":232194,"journal":{"name":"2020 IEEE International Conference on Industrial Application of Artificial Intelligence (IAAI)","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129164531","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
Numerical Simulation System of Aerocraft Aerodynamic Characteristics for Intelligent Internet of Things 面向智能物联网的飞行器气动特性数值模拟系统
2020 IEEE International Conference on Industrial Application of Artificial Intelligence (IAAI) Pub Date : 2020-12-25 DOI: 10.1109/IAAI51705.2020.9332820
W. Ke, Zhou Ze-you
{"title":"Numerical Simulation System of Aerocraft Aerodynamic Characteristics for Intelligent Internet of Things","authors":"W. Ke, Zhou Ze-you","doi":"10.1109/IAAI51705.2020.9332820","DOIUrl":"https://doi.org/10.1109/IAAI51705.2020.9332820","url":null,"abstract":"In the current numerical simulation system of aircraft aerodynamic characteristics, the calculation of motion coordinates is not good. When the data deviation occurs, the numerical deviation cannot be effectively controlled, which affects the simulation accuracy. Therefore, a numerical simulation system for aerocraft aerodynamic characteristics oriented to the intelligent Internet of things is proposed. In the design, the traditional numerical simulation system is used in the hardware design, and only the software part is designed. Firstly, the input interface of calculation parameters of the system is designed, and the hierarchical structure of the software is given. The transport equation of the motion coordinate system is set up to calculate the relevant motion parameters of the input value After correcting the deviation, the calculation method of aerodynamic wind energy is designed, and the final simulation data are obtained. In order to verify whether the designed numerical simulation system can effectively control the numerical deviation, the design system is compared with reference [3], reference [5] and document [7], and connected with the intelligent Internet of things, and the relevant deviation values are extracted and controlled. The experimental results show that the designed numerical simulation system can achieve deviation control quickly, and The feasibility of the design is proved for overshoot.","PeriodicalId":232194,"journal":{"name":"2020 IEEE International Conference on Industrial Application of Artificial Intelligence (IAAI)","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127522265","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: 1
Numerical Simulation of Strength Limit of Surrounding Rock in Geotechnical Engineering Based on Machine Learning 基于机器学习的岩土工程围岩强度极限数值模拟
2020 IEEE International Conference on Industrial Application of Artificial Intelligence (IAAI) Pub Date : 2020-12-25 DOI: 10.1109/iaai51705.2020.9332823
Mudan Gu
{"title":"Numerical Simulation of Strength Limit of Surrounding Rock in Geotechnical Engineering Based on Machine Learning","authors":"Mudan Gu","doi":"10.1109/iaai51705.2020.9332823","DOIUrl":"https://doi.org/10.1109/iaai51705.2020.9332823","url":null,"abstract":"When the traditional method numerically simulates the strength of the surrounding rock, the error of obtaining the strength parameters is large, which leads to a large range of the numerical value of the strength simulation. Therefore, a numerical simulation method based on machine learning for the strength limit of surrounding rock in geotechnical engineering is proposed. Evaluate the volume joints and structural surfaces of the surrounding rock, collect the surrounding rock environment information and geotechnical characteristics, perform mechanical simulation on it, use machine learning technology to optimize the strength parameter algorithm, obtain the optimal stress parameter, and realize the strength numerical simulation. The experimental results show that the variation range of numerical simulation method of surrounding rock strength is less than that of two traditional methods, which improves the accuracy of numerical simulation.","PeriodicalId":232194,"journal":{"name":"2020 IEEE International Conference on Industrial Application of Artificial Intelligence (IAAI)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129831759","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
Research on the Improvement of Data Mining Algorithm Based on “Internet +” System in Cloud Computing 云计算中基于“互联网+”系统的数据挖掘算法改进研究
2020 IEEE International Conference on Industrial Application of Artificial Intelligence (IAAI) Pub Date : 2020-12-25 DOI: 10.1109/IAAI51705.2020.9332879
Jia Yu
{"title":"Research on the Improvement of Data Mining Algorithm Based on “Internet +” System in Cloud Computing","authors":"Jia Yu","doi":"10.1109/IAAI51705.2020.9332879","DOIUrl":"https://doi.org/10.1109/IAAI51705.2020.9332879","url":null,"abstract":"In cloud computing environment, the research on data mining has very important practical significance. The traditional method of data mining has the problems of poor clustering effect and slow speed of data mining. In order to solve this problem, the “Internet +” system is used to improve the algorithm of data mining. Combined with the result of multiple sampling, the mining center of the data set is determined. On the basis of which, the multi-layer variable weighting concept is introduced, the non-leaf node data is distributed processing, the Euclidean distance algorithm is introduced to analyze the data linear relation, and the data convergence speed and the critical value in the data mining process are controlled, the optimal design of the data mining algorithm is realized. The simulation results show that, the improved algorithm improves the speed of data mining by 37.25%, and has higher distribution accuracy, better data clustering effect than the conventional algorithm.","PeriodicalId":232194,"journal":{"name":"2020 IEEE International Conference on Industrial Application of Artificial Intelligence (IAAI)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126738269","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
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