2020 IEEE Symposium on Industrial Electronics & Applications (ISIEA)最新文献

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Machine Learning Price Prediction on Green Building Prices 绿色建筑价格的机器学习预测
2020 IEEE Symposium on Industrial Electronics & Applications (ISIEA) Pub Date : 2020-07-01 DOI: 10.1109/ISIEA49364.2020.9188114
Syafiqah Jamil, Thuraiya Mohd, S. Masrom, Norbaya Ab Rahim
{"title":"Machine Learning Price Prediction on Green Building Prices","authors":"Syafiqah Jamil, Thuraiya Mohd, S. Masrom, Norbaya Ab Rahim","doi":"10.1109/ISIEA49364.2020.9188114","DOIUrl":"https://doi.org/10.1109/ISIEA49364.2020.9188114","url":null,"abstract":"In the era of Industry 4.0, Machine Learning models have become increasingly popular and influential as they are often used to solve different prediction and classification problems in various industries and including the real estate industry. However, to obtain the best combination of these approaches for a good of Green Building (GB) price predictor model, it is important to be identify and require extensive empirical experiments work by identifying the best parameters configurations, techniques, and algorithms. GB is known as a potential approach to improve the performance of the building. Where in Malaysia involving five distinctly different assessment criteria namely, Energy Efficiency (EE), Indoor Environment Quality (EQ), Sustainable Site Planning & Management (SM), Material & Resources (MR), Water Efficiency (WE). This paper provides a report of an empirical study that model building price prediction based on GB dataset that covered Kuala Lumpur District, Malaysia. The experiments used five common algorithms namely Linear Regression, Decision Tree, Random Forest, Ridge and Lasso that tested on a set of real estate building datasets. The result showed the Decision Tree Regressor outperforms the other four algorithms on the test dataset.","PeriodicalId":120582,"journal":{"name":"2020 IEEE Symposium on Industrial Electronics & Applications (ISIEA)","volume":"264 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129625951","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
Self-Management of Diabetes Mellitus Patients Using mHealth Applications: A Systematic Review 使用移动健康应用程序的糖尿病患者自我管理:系统综述
2020 IEEE Symposium on Industrial Electronics & Applications (ISIEA) Pub Date : 2020-07-01 DOI: 10.1109/ISIEA49364.2020.9188234
Ricardo Buettner, Carla Burkert, Jenny Mueller
{"title":"Self-Management of Diabetes Mellitus Patients Using mHealth Applications: A Systematic Review","authors":"Ricardo Buettner, Carla Burkert, Jenny Mueller","doi":"10.1109/ISIEA49364.2020.9188234","DOIUrl":"https://doi.org/10.1109/ISIEA49364.2020.9188234","url":null,"abstract":"We review diabetes-related mHealth application literature included in peer-review journals and conferences and present a state-of-the-art overview.","PeriodicalId":120582,"journal":{"name":"2020 IEEE Symposium on Industrial Electronics & Applications (ISIEA)","volume":"53 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114684818","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
Towards Elderly Monitoring Management System Using IOT 基于物联网的老年人监控管理系统研究
2020 IEEE Symposium on Industrial Electronics & Applications (ISIEA) Pub Date : 2020-07-01 DOI: 10.1109/ISIEA49364.2020.9188191
Sani Salsabil bin Eddy Yusuf, Rabab Alayham Abbas Helmi, Muhammad Irsyad Bin Abdullah, A. Jamal
{"title":"Towards Elderly Monitoring Management System Using IOT","authors":"Sani Salsabil bin Eddy Yusuf, Rabab Alayham Abbas Helmi, Muhammad Irsyad Bin Abdullah, A. Jamal","doi":"10.1109/ISIEA49364.2020.9188191","DOIUrl":"https://doi.org/10.1109/ISIEA49364.2020.9188191","url":null,"abstract":"The increasing elderly population around the world makes everyone wonder, who is going to monitor our senior citizens. The median age in Malaysia has increased from 28.3 years to 28.6 years in 2018. Hence, elderly population has increased in Malaysia. In Malaysian culture, the responsibility to monitor the elderly usually fall on their children or extended family. For unmarried individuals or childless couples, it was very common for them to adopt a child. Therefore, they would have someone to take care when they become old. The proposed system can handle the traditional method of monitoring. UHF RFID monitoring system can monitor the elderly all day.","PeriodicalId":120582,"journal":{"name":"2020 IEEE Symposium on Industrial Electronics & Applications (ISIEA)","volume":"37 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123514812","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: 3
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