Sujoy Barua, Anik Nath, Fahim Shahriyar, N. Mohammad
{"title":"孟加拉国发电结构的时空分析与预测","authors":"Sujoy Barua, Anik Nath, Fahim Shahriyar, N. Mohammad","doi":"10.1109/ICASERT.2019.8934479","DOIUrl":null,"url":null,"abstract":"An analysis is presented to show time series data of electricity generation mix and forecasting by 2030 in Bangladesh. The comparative studies have been analyzed using spatiotemporal data of Germany, Australia and Bangladesh. The spatiotemporal data has been taken out from World Bank data bank for analysis. A Linear regression technique is applied for forecasting electricity generation mix from 2015 to 2030. The result shows the rise of renewable energy sources, coal and oil, and the diminution of natural gas gradually.","PeriodicalId":6613,"journal":{"name":"2019 1st International Conference on Advances in Science, Engineering and Robotics Technology (ICASERT)","volume":"13 1","pages":"1-5"},"PeriodicalIF":0.0000,"publicationDate":"2019-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"A Spatiotemporal Analysis and Forecasting of Electricity Generation-Mix in Bangladesh\",\"authors\":\"Sujoy Barua, Anik Nath, Fahim Shahriyar, N. Mohammad\",\"doi\":\"10.1109/ICASERT.2019.8934479\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"An analysis is presented to show time series data of electricity generation mix and forecasting by 2030 in Bangladesh. The comparative studies have been analyzed using spatiotemporal data of Germany, Australia and Bangladesh. The spatiotemporal data has been taken out from World Bank data bank for analysis. A Linear regression technique is applied for forecasting electricity generation mix from 2015 to 2030. The result shows the rise of renewable energy sources, coal and oil, and the diminution of natural gas gradually.\",\"PeriodicalId\":6613,\"journal\":{\"name\":\"2019 1st International Conference on Advances in Science, Engineering and Robotics Technology (ICASERT)\",\"volume\":\"13 1\",\"pages\":\"1-5\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-05-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2019 1st International Conference on Advances in Science, Engineering and Robotics Technology (ICASERT)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICASERT.2019.8934479\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 1st International Conference on Advances in Science, Engineering and Robotics Technology (ICASERT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICASERT.2019.8934479","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A Spatiotemporal Analysis and Forecasting of Electricity Generation-Mix in Bangladesh
An analysis is presented to show time series data of electricity generation mix and forecasting by 2030 in Bangladesh. The comparative studies have been analyzed using spatiotemporal data of Germany, Australia and Bangladesh. The spatiotemporal data has been taken out from World Bank data bank for analysis. A Linear regression technique is applied for forecasting electricity generation mix from 2015 to 2030. The result shows the rise of renewable energy sources, coal and oil, and the diminution of natural gas gradually.
京公网安备 11010802042870号
京ICP备2023020795号-1
分享
求助内容：
应助结果提醒方式：
扫码关注我们
