Prediction of solar irradiation in Bangladesh using artificial neural network (ANN) and data mapping using GIS technology

Khan Md. Rabbi, I. Nandi, A. Saleh, Faiaz Faisal, S. Mojumder
{"title":"Prediction of solar irradiation in Bangladesh using artificial neural network (ANN) and data mapping using GIS technology","authors":"Khan Md. Rabbi, I. Nandi, A. Saleh, Faiaz Faisal, S. Mojumder","doi":"10.1109/ICDRET.2016.7421482","DOIUrl":null,"url":null,"abstract":"In this paper, an artificial neural network (ANN) model is used to predict the monthly solar energy potential in Bangladesh. Used data are taken from NASA database for the past 22 years average from 1983 to 2005 and eight divisional cities are considered in this study. A multi-layered feed forward ANN model of four layers with eight independent input variables i.e. average temperature, sunshine duration, wind speed, precipitation, humidity, elevation, cloud coverage and atmospheric pressure to predict the monthly solar irradiation. Data from six cities are used for training and the remaining two cities were considered for testing and validation. A solar irradiation map is developed by data mapping using GIS technology. From the illustrations, the predicted data show good agreement with the observed data. This indicates that, this model can be used to predict solar irradiation of Bangladesh and to provide sufficient information about the feasibility of solar powered projects.","PeriodicalId":365312,"journal":{"name":"2016 4th International Conference on the Development in the in Renewable Energy Technology (ICDRET)","volume":"19 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-02-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"8","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 4th International Conference on the Development in the in Renewable Energy Technology (ICDRET)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICDRET.2016.7421482","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 8

Abstract

In this paper, an artificial neural network (ANN) model is used to predict the monthly solar energy potential in Bangladesh. Used data are taken from NASA database for the past 22 years average from 1983 to 2005 and eight divisional cities are considered in this study. A multi-layered feed forward ANN model of four layers with eight independent input variables i.e. average temperature, sunshine duration, wind speed, precipitation, humidity, elevation, cloud coverage and atmospheric pressure to predict the monthly solar irradiation. Data from six cities are used for training and the remaining two cities were considered for testing and validation. A solar irradiation map is developed by data mapping using GIS technology. From the illustrations, the predicted data show good agreement with the observed data. This indicates that, this model can be used to predict solar irradiation of Bangladesh and to provide sufficient information about the feasibility of solar powered projects.
利用人工神经网络(ANN)和地理信息系统(GIS)技术的数据制图预测孟加拉国的太阳辐照
本文采用人工神经网络(ANN)模型对孟加拉国的月太阳能潜力进行预测。所使用的数据取自美国国家航空航天局(NASA)数据库,平均为1983年至2005年的22年,本研究考虑了8个分区城市。采用平均温度、日照时数、风速、降水、湿度、海拔、云量和气压等8个独立输入变量,建立4层多层前馈人工神经网络模型,用于预测月太阳辐照量。来自六个城市的数据用于培训,其余两个城市用于测试和验证。利用GIS技术进行数据制图,绘制了太阳辐照图。算例表明,预测数据与观测数据吻合较好。这表明,该模式可用于预测孟加拉国的太阳辐照,并提供关于太阳能项目可行性的充分资料。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信