{"title":"利用机器学习预测太阳能电池板的功率","authors":"Umang Garg, Deepak Kumar Chohan, D. Dobhal","doi":"10.1109/ComPE53109.2021.9751901","DOIUrl":null,"url":null,"abstract":"The Solar panels are depending on the various parameters like air pollution and environment. The air pollution and bad weather conditions are generated very critical condition for the generation of power from solar panels. The prediction of solar panel’s power in advance improves the overall functionality of the solar panels and generated the best results for end-users. In this paper, a prediction of solar power using machine learning algorithms has been done and analysis the impact of air pollution and bad weather on it. A machine learning model is able to generate the best results with the extraction of features like bad environment, air and weather pollutions. The experimental results show the efficient results on the dataset collected from the open-source system.","PeriodicalId":211704,"journal":{"name":"2021 International Conference on Computational Performance Evaluation (ComPE)","volume":"29 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"The Prediction of Power in Solar Panel using Machine Learning\",\"authors\":\"Umang Garg, Deepak Kumar Chohan, D. Dobhal\",\"doi\":\"10.1109/ComPE53109.2021.9751901\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The Solar panels are depending on the various parameters like air pollution and environment. The air pollution and bad weather conditions are generated very critical condition for the generation of power from solar panels. The prediction of solar panel’s power in advance improves the overall functionality of the solar panels and generated the best results for end-users. In this paper, a prediction of solar power using machine learning algorithms has been done and analysis the impact of air pollution and bad weather on it. A machine learning model is able to generate the best results with the extraction of features like bad environment, air and weather pollutions. The experimental results show the efficient results on the dataset collected from the open-source system.\",\"PeriodicalId\":211704,\"journal\":{\"name\":\"2021 International Conference on Computational Performance Evaluation (ComPE)\",\"volume\":\"29 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2021 International Conference on Computational Performance Evaluation (ComPE)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ComPE53109.2021.9751901\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 International Conference on Computational Performance Evaluation (ComPE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ComPE53109.2021.9751901","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
The Prediction of Power in Solar Panel using Machine Learning
The Solar panels are depending on the various parameters like air pollution and environment. The air pollution and bad weather conditions are generated very critical condition for the generation of power from solar panels. The prediction of solar panel’s power in advance improves the overall functionality of the solar panels and generated the best results for end-users. In this paper, a prediction of solar power using machine learning algorithms has been done and analysis the impact of air pollution and bad weather on it. A machine learning model is able to generate the best results with the extraction of features like bad environment, air and weather pollutions. The experimental results show the efficient results on the dataset collected from the open-source system.