2016 IEEE 9th International Workshop on Computational Intelligence and Applications (IWCIA)最新文献

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Optimizing the structure of a path analysis model using a real-valued flexibly connected neural network 利用实值柔性连接神经网络优化路径分析模型的结构
Shinya Watanuki, T. Nagao
{"title":"Optimizing the structure of a path analysis model using a real-valued flexibly connected neural network","authors":"Shinya Watanuki, T. Nagao","doi":"10.1109/IWCIA.2016.7805745","DOIUrl":"https://doi.org/10.1109/IWCIA.2016.7805745","url":null,"abstract":"The path analysis model (PAM) is a multivariate statistical modeling technique widely used in the behavioral and social sciences. Although some methods for optimizing the parameters and reducing the variables in PAM have been proposed, only a few studies have focused on flexible optimization of the structure and parameter in PAM. In this study, we used a real-valued flexibly connected neural network (RFCN) to construct PAM. Using survey data, we then confirmed the validity of our approach from two viewpoints. First, we assessed our approach using statistical fitness indices. Then, we compared the obtained results with those obtained from previous studies on consumer psychology. The results confirmed that our proposed approach offers a novel way of constructing PAM using RFCN.","PeriodicalId":262942,"journal":{"name":"2016 IEEE 9th International Workshop on Computational Intelligence and Applications (IWCIA)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133316331","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
Performance optimization in video transmission over ZigBee using Particle Swarm Optimization 基于粒子群算法的ZigBee视频传输性能优化
Iman Samizadeh, H. Kazemian, K. Fisher, K. Ouazzane
{"title":"Performance optimization in video transmission over ZigBee using Particle Swarm Optimization","authors":"Iman Samizadeh, H. Kazemian, K. Fisher, K. Ouazzane","doi":"10.1109/IWCIA.2016.7805742","DOIUrl":"https://doi.org/10.1109/IWCIA.2016.7805742","url":null,"abstract":"IEEE 802.15.4 - ZigBee is a wireless sensor targeted at applications that require low data rate, low power and inexpensive. ZigBee is limited to a throughput of 250kbps and is designed to provide highly efficient connectivity. Hence, IEEE 802.15.4 is not designed to transfer large amounts of data or MPEG-4, as its bandwidth is too low. In engineering and computer science often optimization techniques used to overcome complex issues. In this paper a solution has been accomplished by applying Particle Swarm Optimization (PSO) to improve the quality of transmitted MPEG-4 over IEEE 802.15.4 wireless sensor networks (WSN). The proposed intelligent system should minimize data loss and distortion. The computer simulation results confirm that applying PSO in video transmission improve the quality of picture and reduce data loss when compared with the conventional MPEG video transmission over ZigBee.","PeriodicalId":262942,"journal":{"name":"2016 IEEE 9th International Workshop on Computational Intelligence and Applications (IWCIA)","volume":"92 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-07-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130490801","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: 2
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