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

Infrared Image Sequence Small Target Recognition Method Based on Wavelet Transform Domain 基于小波变换域的红外图像序列小目标识别方法

2020 IEEE International Conference on Industrial Application of Artificial Intelligence (IAAI) Pub Date : 2020-12-25 DOI: 10.1109/IAAI51705.2020.9332853

Jiang Zheng-Hong, Zhou Chun-rong

引用次数: 0

Recognition Method of Single Hand over Shoulder Shooting based on Multi-Dimensional Visual Images 基于多维视觉图像的单手过肩射击识别方法

2020 IEEE International Conference on Industrial Application of Artificial Intelligence (IAAI) Pub Date : 2020-12-25 DOI: 10.1109/IAAI51705.2020.9332900

Li Xiao-xia

{"title":"Recognition Method of Single Hand over Shoulder Shooting based on Multi-Dimensional Visual Images","authors":"Li Xiao-xia","doi":"10.1109/IAAI51705.2020.9332900","DOIUrl":"https://doi.org/10.1109/IAAI51705.2020.9332900","url":null,"abstract":"When the current action recognition methods recognize one hand over the shoulder shooting action, it will cause noise and holes, which will affect the recognition of one hand over the shoulder shot action, resulting in low accuracy rate of single hand over shoulder shot action recognition. Therefore, this paper proposes a recognition method of one hand over shoulder shot action based on multi-dimensional visual images. The image acquisition model of one hand over the shoulder shot is established, and the multi-dimensional visual image is used to mark the single hand over the shoulder shooting action; the image segmentation and feature extraction are preprocessed according to the marking results of the single hand shoulder shot action; the four-dimensional vector of the single hand over shoulder shot image is established to calculate the movement process of the one hand over the shoulder shot action and identify the single hand over shoulder shot action. The experimental results show that under the background of the same one handed shoulder shot and arm motion track, the arm motion track can be identified and the recognition accuracy rate can be detected. The identification method of single hand shoulder shot action can accurately identify the single hand shoulder shot action and the arm movement track, and the recognition accuracy rate is high.","PeriodicalId":232194,"journal":{"name":"2020 IEEE International Conference on Industrial Application of Artificial Intelligence (IAAI)","volume":"27 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":"115678928","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

Clinical Nursing Risk Assessment and Early Warning System based on Support Vector Machine 基于支持向量机的临床护理风险评估与预警系统

2020 IEEE International Conference on Industrial Application of Artificial Intelligence (IAAI) Pub Date : 2020-12-25 DOI: 10.1109/iaai51705.2020.9332816

Tong Men, Ya-Hui Zhou

引用次数: 0

Research on Performance Appraisal Method of Grass Roots Staff in the Perspective of Complex Big Data 复杂大数据视角下基层员工绩效考核方法研究

2020 IEEE International Conference on Industrial Application of Artificial Intelligence (IAAI) Pub Date : 2020-12-25 DOI: 10.1109/IAAI51705.2020.9332888

Chu Hao-nan, Zhang Cai-ming

{"title":"Research on Performance Appraisal Method of Grass Roots Staff in the Perspective of Complex Big Data","authors":"Chu Hao-nan, Zhang Cai-ming","doi":"10.1109/IAAI51705.2020.9332888","DOIUrl":"https://doi.org/10.1109/IAAI51705.2020.9332888","url":null,"abstract":"The traditional performance appraisal method of grass-roots staff is not strong enough to motivate employees, which leads to the problem of poor workload completion. To solve this problem, the paper designs the performance appraisal method of grass-roots employees from the perspective of complex big data. Sort out the evaluation procedures, determine the integrated employee performance appraisal indicators, and construct the index system. The weight of assessment index is calculated by the method of priority diagram. The index and index weight are integrated, and the competency model is constructed by combining fuzzy evaluation method. At the same time, set up the rules of appraisal grade division to complete the performance appraisal of grass-roots employees. This paper constructs the case analysis link, obtains the basic information of the enterprise, and realizes the comparison between this method and the traditional method. According to the comparison results, this method has a strong incentive effect on employees, and the completion degree of enterprise workload is better.","PeriodicalId":232194,"journal":{"name":"2020 IEEE International Conference on Industrial Application of Artificial Intelligence (IAAI)","volume":"56 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":"116902723","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

Construction Quality Evaluation Model of Concrete Pouring based on Support Vector Machine 基于支持向量机的混凝土浇筑施工质量评价模型

2020 IEEE International Conference on Industrial Application of Artificial Intelligence (IAAI) Pub Date : 2020-12-25 DOI: 10.1109/iaai51705.2020.9332877

Tian Man-li, Wang Jie

引用次数: 0

E-Commerce Human Capital Performance Evaluation Model based on Fuzzy Pattern Recognition 基于模糊模式识别的电子商务人力资本绩效评价模型

2020 IEEE International Conference on Industrial Application of Artificial Intelligence (IAAI) Pub Date : 2020-12-25 DOI: 10.1109/IAAI51705.2020.9332867

Yu-Min Wei

引用次数: 0

Intelligent Integration Method of Big Data for Time Sharing Regulation of Elastic Load 弹性负荷分时调节大数据智能集成方法

2020 IEEE International Conference on Industrial Application of Artificial Intelligence (IAAI) Pub Date : 2020-12-25 DOI: 10.1109/IAAI51705.2020.9332875

Li Bo, Yang Shi-hai, Yang Yong-biao

{"title":"Intelligent Integration Method of Big Data for Time Sharing Regulation of Elastic Load","authors":"Li Bo, Yang Shi-hai, Yang Yong-biao","doi":"10.1109/IAAI51705.2020.9332875","DOIUrl":"https://doi.org/10.1109/IAAI51705.2020.9332875","url":null,"abstract":"At present, the intelligent data integration method requires a large number of professionals to integrate the time-sharing control big data of electric elastic load. After the integration, there is a large amount of redundant data and the data integration efficiency is low. Therefore, an intelligent integration method of time-sharing regulation big data of electric elastic load is proposed. The data parallel state is calculated, the mathematical description of data parallel state is analyzed, and the change of electric power data in the time-sharing regulation and control of power elastic load is analyzed, and the mathematical description result is modified to further improve the data state analysis result. According to the obtained data state description result, the data state is decomposed to reduce the difficulty of data intelligent integration; data intelligence is designed Integration process, the data in the data intelligent integration of secondary planning, reduce the redundant data in the data, complete the data intelligent integration. The experimental results show that the intelligent data integration method in this study integrates the time-sharing control big data of electric elastic load, which makes the results of data integration more accurate, improves the rate of deleting redundant data, and reduces the redundancy of the integrated data set.","PeriodicalId":232194,"journal":{"name":"2020 IEEE International Conference on Industrial Application of Artificial Intelligence (IAAI)","volume":"42 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":"122810331","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 stability control method of mechanical driving device based on Data Mining 基于数据挖掘的机械驱动装置稳定性控制方法研究

2020 IEEE International Conference on Industrial Application of Artificial Intelligence (IAAI) Pub Date : 2020-12-25 DOI: 10.1109/IAAI51705.2020.9332869

Xiaoyan Wan, Song Zhang, Zhao Huanyu, Sun Jinwei, Zheng Shanshan

{"title":"Research on stability control method of mechanical driving device based on Data Mining","authors":"Xiaoyan Wan, Song Zhang, Zhao Huanyu, Sun Jinwei, Zheng Shanshan","doi":"10.1109/IAAI51705.2020.9332869","DOIUrl":"https://doi.org/10.1109/IAAI51705.2020.9332869","url":null,"abstract":"The stability of the mechanical drive device affects the performance of the device. The control performance of the existing mechanical drive device stability control methods is low. Therefore, this paper designs a stability control method of mechanical drive device based on data mining. First analyze the configuration of the mechanical drive device, and obtain the working data of the mechanical drive device based on this, and then use the data mining algorithm to extract the feature data of the mechanical drive device, and build the vibration equation of the mechanical drive device based on the extracted feature data to analyze the mechanical drive device The stability state. On this basis, direct torque control technology is used to control the stability of mechanical drive device. The simulation experiment results show that the average displacement error of the mechanical drive device of the method in this paper is less than 0.1 under various working conditions, which fully shows that the method in this paper has a better control effect.","PeriodicalId":232194,"journal":{"name":"2020 IEEE International Conference on Industrial Application of Artificial Intelligence (IAAI)","volume":"21 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":"128216297","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

Design of Environmental Quality Management System in Ecotourism Area Based on RBF Network 基于RBF网络的生态旅游区环境质量管理体系设计

2020 IEEE International Conference on Industrial Application of Artificial Intelligence (IAAI) Pub Date : 2020-12-25 DOI: 10.1109/iaai51705.2020.9332811

Huimin Hu, Yi Wei

{"title":"Design of Environmental Quality Management System in Ecotourism Area Based on RBF Network","authors":"Huimin Hu, Yi Wei","doi":"10.1109/iaai51705.2020.9332811","DOIUrl":"https://doi.org/10.1109/iaai51705.2020.9332811","url":null,"abstract":"In order to improve the effect of eco-tourism area environmental quality management, this paper designs a new eco-tourism area environmental quality management system from hardware, database and software using RBF network. In the hardware environment, construct the network environment and connection circuits of the system, and install RFID equipment. Store all data and information about environmental quality in the eco-tourism area in the same way in the database, and combine the logical relationship between the data to get the database link. With the support of hardware environment and database, collect real-time environmental quality information data, and use RBF network to evaluate current environmental quality. Finally, the environmental quality management of the ecotourism area will be realized from the three aspects of air, greening and water environment. The experimental results show that: the application of this system to the daily management of eco-tourism area can effectively improve the environmental quality of air, green and water environment, which proves that the management effect of this system is better.","PeriodicalId":232194,"journal":{"name":"2020 IEEE International Conference on Industrial Application of Artificial Intelligence (IAAI)","volume":"192 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":"120947585","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 of Evacuation Route for Urban Traffic Congestion based on Particle Swarm Optimization 基于粒子群算法的城市交通拥堵疏散路径优化

2020 IEEE International Conference on Industrial Application of Artificial Intelligence (IAAI) Pub Date : 2020-12-25 DOI: 10.1109/iaai51705.2020.9332842

Tan Jia, Donghua Long

引用次数: 0