Pub Date : 2021-06-01DOI: 10.1109/ICAA53760.2021.00041
Hanqing Hu, Xiang Ma, Hengxing Pan, Hongxi Zhang, Fan Gu
With the rapid development of the information age, the traditional knowledge management system has many problems such as large amount of information and complex content, which leads to the low efficiency of users to obtain the correct information and affects the efficiency of knowledge transfer and knowledge sharing. In this paper, the intelligent recommendation system based on knowledge management is introduced to solve the problem of information overload, so as to effectively improve the efficiency of knowledge transmission and sharing and maximize the value of knowledge.
{"title":"Research on Intelligent Recommendation System Based on Knowledge Management","authors":"Hanqing Hu, Xiang Ma, Hengxing Pan, Hongxi Zhang, Fan Gu","doi":"10.1109/ICAA53760.2021.00041","DOIUrl":"https://doi.org/10.1109/ICAA53760.2021.00041","url":null,"abstract":"With the rapid development of the information age, the traditional knowledge management system has many problems such as large amount of information and complex content, which leads to the low efficiency of users to obtain the correct information and affects the efficiency of knowledge transfer and knowledge sharing. In this paper, the intelligent recommendation system based on knowledge management is introduced to solve the problem of information overload, so as to effectively improve the efficiency of knowledge transmission and sharing and maximize the value of knowledge.","PeriodicalId":121879,"journal":{"name":"2021 International Conference on Intelligent Computing, Automation and Applications (ICAA)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128095051","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}
Pub Date : 2021-06-01DOI: 10.1109/ICAA53760.2021.00174
Qi Wang, Shaohui Zhou, Hourong Zhang, Haohui Su, Wenjian Zheng
In this paper, the ice thickness prediction model of WRF field prediction elements is constructed using Makkonen icing model using comprehensive monitoring data of high-voltage transmission line ice accumulation in five southern provinces from Dec. 13, 2020 to Dec. 19, 2020. For the random forest algorithm, the actual icing thickness derived by conductor tension is inputted, 19 predictor variables are selected, such as tower number, phase, and predicted ice thickness value. The WRF-random forest model for icing prediction is constructed, and the best parameters are found by using Bayesian parameter optimization method, showing a coefficient of determination of 0.968 for the training set and 0.949 for the testing set.
{"title":"Prediction of Conductor Icing Thickness Based on Random Forest and WRF Models","authors":"Qi Wang, Shaohui Zhou, Hourong Zhang, Haohui Su, Wenjian Zheng","doi":"10.1109/ICAA53760.2021.00174","DOIUrl":"https://doi.org/10.1109/ICAA53760.2021.00174","url":null,"abstract":"In this paper, the ice thickness prediction model of WRF field prediction elements is constructed using Makkonen icing model using comprehensive monitoring data of high-voltage transmission line ice accumulation in five southern provinces from Dec. 13, 2020 to Dec. 19, 2020. For the random forest algorithm, the actual icing thickness derived by conductor tension is inputted, 19 predictor variables are selected, such as tower number, phase, and predicted ice thickness value. The WRF-random forest model for icing prediction is constructed, and the best parameters are found by using Bayesian parameter optimization method, showing a coefficient of determination of 0.968 for the training set and 0.949 for the testing set.","PeriodicalId":121879,"journal":{"name":"2021 International Conference on Intelligent Computing, Automation and Applications (ICAA)","volume":"46 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134102604","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}
In order to excavate the influencing factors of recidivsim of the prisoners so as to achieve the purpose of prevention and redction of crime. This article proposes a feature selection method based on the experience of field experts and chi-square test, and uses the data from 2004 survey of inmates in state and federal correctional facilities as source, through data cleaning and data discretizes, and select five machine learning models for training and prediction respectively. Taking the accuracy rate, recall rate and values as evaluation indicators, compared the recidivism prediction capabilities of the five models. The results show that the feature selection method proposed in this paper can greatly impove the accuracy and recall rate of each model, and the logisitc regression model has a strong comprehensive ability.
{"title":"Comparative Analysis of Machine Learning Models for Recidivism Prediction Based on Chi-square Test","authors":"Zhihao Zhang, Zhaohua Huang, Zhongbao Wan, Lingci Meng","doi":"10.1109/ICAA53760.2021.00012","DOIUrl":"https://doi.org/10.1109/ICAA53760.2021.00012","url":null,"abstract":"In order to excavate the influencing factors of recidivsim of the prisoners so as to achieve the purpose of prevention and redction of crime. This article proposes a feature selection method based on the experience of field experts and chi-square test, and uses the data from 2004 survey of inmates in state and federal correctional facilities as source, through data cleaning and data discretizes, and select five machine learning models for training and prediction respectively. Taking the accuracy rate, recall rate and values as evaluation indicators, compared the recidivism prediction capabilities of the five models. The results show that the feature selection method proposed in this paper can greatly impove the accuracy and recall rate of each model, and the logisitc regression model has a strong comprehensive ability.","PeriodicalId":121879,"journal":{"name":"2021 International Conference on Intelligent Computing, Automation and Applications (ICAA)","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132827889","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}
Pub Date : 2021-06-01DOI: 10.1109/ICAA53760.2021.00112
D. Yin, Mingshu Zhang, Bin Wei, Wen-Hsiung Lin
Electronic voting can greatly reduce the cost of voting activities and solve many problems of voting information leakage caused by traditional paper voting. As the development and extension of blockchain technology, Ethereum technology can well solve the centralization problem of traditional electronic voting. This solution proposes an electronic voting system based on Ethereum technology to meet the security requirements of electronic voting, and uses Ethereum smart contract technology to replace the traditional trusted third party, which solves the possible drawbacks of the centralized voting system and improves Security and voters' trust in the voting system reduce voting costs. Finally, the electronic voting function is realized, and the normal operation of the system is guaranteed through the test.
{"title":"Design and Implementation of Voting System Based on Ethereum","authors":"D. Yin, Mingshu Zhang, Bin Wei, Wen-Hsiung Lin","doi":"10.1109/ICAA53760.2021.00112","DOIUrl":"https://doi.org/10.1109/ICAA53760.2021.00112","url":null,"abstract":"Electronic voting can greatly reduce the cost of voting activities and solve many problems of voting information leakage caused by traditional paper voting. As the development and extension of blockchain technology, Ethereum technology can well solve the centralization problem of traditional electronic voting. This solution proposes an electronic voting system based on Ethereum technology to meet the security requirements of electronic voting, and uses Ethereum smart contract technology to replace the traditional trusted third party, which solves the possible drawbacks of the centralized voting system and improves Security and voters' trust in the voting system reduce voting costs. Finally, the electronic voting function is realized, and the normal operation of the system is guaranteed through the test.","PeriodicalId":121879,"journal":{"name":"2021 International Conference on Intelligent Computing, Automation and Applications (ICAA)","volume":"121 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121911578","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}
Pub Date : 2021-06-01DOI: 10.1109/ICAA53760.2021.00008
Shaojie Sheng, Qijie Zhao, K. Xu
The detection of assembly station scene features is a hot research issue in the field of computer vision. Its purpose is to superimpose assembly-related information on the corresponding assembly station scene and provide intuitive online guidance to assembly operators. To this end, this paper proposes a method based on machine vision to detect assembly station scene features, and uses dimensionality reduction processing to simplify the detected high-dimensional features, and uses a bag of words model to construct a Code Book representation method of assembly station scene feature vectors. The dimensionality reduction method is used to solve the problem of the large amount of calculations directly using natural features to match the scene.
{"title":"Feature Detection Method of Assembly Position Based on Machine Vision","authors":"Shaojie Sheng, Qijie Zhao, K. Xu","doi":"10.1109/ICAA53760.2021.00008","DOIUrl":"https://doi.org/10.1109/ICAA53760.2021.00008","url":null,"abstract":"The detection of assembly station scene features is a hot research issue in the field of computer vision. Its purpose is to superimpose assembly-related information on the corresponding assembly station scene and provide intuitive online guidance to assembly operators. To this end, this paper proposes a method based on machine vision to detect assembly station scene features, and uses dimensionality reduction processing to simplify the detected high-dimensional features, and uses a bag of words model to construct a Code Book representation method of assembly station scene feature vectors. The dimensionality reduction method is used to solve the problem of the large amount of calculations directly using natural features to match the scene.","PeriodicalId":121879,"journal":{"name":"2021 International Conference on Intelligent Computing, Automation and Applications (ICAA)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122248688","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}
Pub Date : 2021-06-01DOI: 10.1109/ICAA53760.2021.00034
Xu Bao, Yingzi Tan
In the process of constructing a three-dimensional environment in a large scene, the problem of large accumulated errors is likely to occur, which makes it impossible to construct a globally consistent map. To solve this problem, this paper proposes a loop detection method based on NDT and ICP registration algorithms. The NDT algorithm is used for the initial registration, which can quickly reduce the number of the candidate loop frames and provide the initial pose. On the basis of the initial pose provided by the NDT algorithm, ICP algorithom is performed to determine the precise loopback frame. In this paper, the proposed loop detection algorithm is added to the SLAM framework, verified on the inspection robot platform, and compared with the LOAM and LeGO-LOAM algorithms. Experiments show that the proposed loop detection algorithm can effectively eliminate the cumulative error in the construction of the large environment, build a global consistency map, and have high realtime performance.
{"title":"Improved Loop Detection Method Based on ICP and NDT Registration Algorithm","authors":"Xu Bao, Yingzi Tan","doi":"10.1109/ICAA53760.2021.00034","DOIUrl":"https://doi.org/10.1109/ICAA53760.2021.00034","url":null,"abstract":"In the process of constructing a three-dimensional environment in a large scene, the problem of large accumulated errors is likely to occur, which makes it impossible to construct a globally consistent map. To solve this problem, this paper proposes a loop detection method based on NDT and ICP registration algorithms. The NDT algorithm is used for the initial registration, which can quickly reduce the number of the candidate loop frames and provide the initial pose. On the basis of the initial pose provided by the NDT algorithm, ICP algorithom is performed to determine the precise loopback frame. In this paper, the proposed loop detection algorithm is added to the SLAM framework, verified on the inspection robot platform, and compared with the LOAM and LeGO-LOAM algorithms. Experiments show that the proposed loop detection algorithm can effectively eliminate the cumulative error in the construction of the large environment, build a global consistency map, and have high realtime performance.","PeriodicalId":121879,"journal":{"name":"2021 International Conference on Intelligent Computing, Automation and Applications (ICAA)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126016924","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}
Pub Date : 2021-06-01DOI: 10.1109/ICAA53760.2021.00183
Seyha Song, Miaoping Sun, Musaddiq Shehu Musa
High voltage direct current system-based voltage source converter (VSC HVDC) has been increasing a more robust solution, especially for supplying power to remote regions and offshore wind plants to enhance transmission capacity. VSCs supply power to remote and isolated loads when the commutating voltage is not required from the connected AC grid. HVDC system-based VSC has various advantages. In the future, it is going to be one of the essential works in power systems. In recent years, the AC system is used in power transmission to be robust and efficient. The complexities involved in precise power controllability are one main problem on the AC transmission system. By using VSC-based HVDC transmission, it may solve this problem. Nowadays, the work of HVDC transmission-based VSC for transient power systems is studied.
{"title":"Modeling and Simulation of VSC-HVDC System","authors":"Seyha Song, Miaoping Sun, Musaddiq Shehu Musa","doi":"10.1109/ICAA53760.2021.00183","DOIUrl":"https://doi.org/10.1109/ICAA53760.2021.00183","url":null,"abstract":"High voltage direct current system-based voltage source converter (VSC HVDC) has been increasing a more robust solution, especially for supplying power to remote regions and offshore wind plants to enhance transmission capacity. VSCs supply power to remote and isolated loads when the commutating voltage is not required from the connected AC grid. HVDC system-based VSC has various advantages. In the future, it is going to be one of the essential works in power systems. In recent years, the AC system is used in power transmission to be robust and efficient. The complexities involved in precise power controllability are one main problem on the AC transmission system. By using VSC-based HVDC transmission, it may solve this problem. Nowadays, the work of HVDC transmission-based VSC for transient power systems is studied.","PeriodicalId":121879,"journal":{"name":"2021 International Conference on Intelligent Computing, Automation and Applications (ICAA)","volume":"56 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127577726","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}
Pub Date : 2021-06-01DOI: 10.1109/ICAA53760.2021.00028
Ruhua Lu, Shuangwei Wang, Yalan Li
SQL injection attack has been listed as one of the top ten network application risks by the open web application security project (OWASP) for five consecutive years, and has always been the focus of network security research. In this paper, a SQL injection detection model based on Convolutional neural network (CNN) is proposed. The model is divided into model training stage and classification detection stage. The key parts are the word vector model and CNN model. Firstly, the SQL injection data set is pre-processed, word2vec, word vectorization and other steps to get the vectorized data, and then input to the CNN model for model training and classification detection in turn. The method proposed in this paper realizes the purpose of SQL injection detection, and provides a theoretical reference for researchers and database security maintainers of relevant departments in academic circles, which has a certain application value.
{"title":"Research on SQL Injection Detection Model Based on CNN","authors":"Ruhua Lu, Shuangwei Wang, Yalan Li","doi":"10.1109/ICAA53760.2021.00028","DOIUrl":"https://doi.org/10.1109/ICAA53760.2021.00028","url":null,"abstract":"SQL injection attack has been listed as one of the top ten network application risks by the open web application security project (OWASP) for five consecutive years, and has always been the focus of network security research. In this paper, a SQL injection detection model based on Convolutional neural network (CNN) is proposed. The model is divided into model training stage and classification detection stage. The key parts are the word vector model and CNN model. Firstly, the SQL injection data set is pre-processed, word2vec, word vectorization and other steps to get the vectorized data, and then input to the CNN model for model training and classification detection in turn. The method proposed in this paper realizes the purpose of SQL injection detection, and provides a theoretical reference for researchers and database security maintainers of relevant departments in academic circles, which has a certain application value.","PeriodicalId":121879,"journal":{"name":"2021 International Conference on Intelligent Computing, Automation and Applications (ICAA)","volume":"316 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124496477","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}
Pub Date : 2021-06-01DOI: 10.1109/ICAA53760.2021.00045
Xiaoying Zhao
With nearly 70 years of development, artificial intelligence technology has made many major breakthroughs. Machine translation based on artificial intelligence technology is becoming more and more powerful. Machine translation has greatly improved the quality and efficiency of translation, but there are still some deficiencies. In order to improve the quality of machine translation, post-editing is becoming more and more important. This thesis attempts to explore the post-editing machine translation of children's picture books in the framework of multimodal discourse analysis, in the hope of benefiting the development of post-editing research and providing reference for the translation practice of children's picture books.
{"title":"A Study on Post-editing Strategies in the Translation of Multimodal Texts under the Background of Artificial Intelligence: With Examples from Children's Picture Books","authors":"Xiaoying Zhao","doi":"10.1109/ICAA53760.2021.00045","DOIUrl":"https://doi.org/10.1109/ICAA53760.2021.00045","url":null,"abstract":"With nearly 70 years of development, artificial intelligence technology has made many major breakthroughs. Machine translation based on artificial intelligence technology is becoming more and more powerful. Machine translation has greatly improved the quality and efficiency of translation, but there are still some deficiencies. In order to improve the quality of machine translation, post-editing is becoming more and more important. This thesis attempts to explore the post-editing machine translation of children's picture books in the framework of multimodal discourse analysis, in the hope of benefiting the development of post-editing research and providing reference for the translation practice of children's picture books.","PeriodicalId":121879,"journal":{"name":"2021 International Conference on Intelligent Computing, Automation and Applications (ICAA)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121371970","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}
Pub Date : 2021-06-01DOI: 10.1109/ICAA53760.2021.00027
Yaming Ren
The fish swarm algorithm simulates the behavior of the fish swarm. Each individual only exchanges information with the surrounding individuals each time, the fish swarm algorithm is more conducive to global optimization. Fish swarm algorithm is an intelligent algorithm, which does not need to make use of the gradient information of the problem. Each individual corrects its position by exchanging information with individuals in adjacent areas. In this paper, we use fish swarm algorithm to solve the economic dispatching problem of power system and the simulation results show that the fish swarm algorithm is effective.
{"title":"Fish Swarm Algorithm and Its Application in Power System Economic Dispatch","authors":"Yaming Ren","doi":"10.1109/ICAA53760.2021.00027","DOIUrl":"https://doi.org/10.1109/ICAA53760.2021.00027","url":null,"abstract":"The fish swarm algorithm simulates the behavior of the fish swarm. Each individual only exchanges information with the surrounding individuals each time, the fish swarm algorithm is more conducive to global optimization. Fish swarm algorithm is an intelligent algorithm, which does not need to make use of the gradient information of the problem. Each individual corrects its position by exchanging information with individuals in adjacent areas. In this paper, we use fish swarm algorithm to solve the economic dispatching problem of power system and the simulation results show that the fish swarm algorithm is effective.","PeriodicalId":121879,"journal":{"name":"2021 International Conference on Intelligent Computing, Automation and Applications (ICAA)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114271139","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}
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