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Again, chaos, also called as \u201cbutterfly effect,\u201d limits our ability to make weather predictable. So, it is not easy to predict rainfall by conventional machine learning approaches. However, several kinds of research have been proposed to predict rainfall by using different computational methods. To accomplish chaotic rainfall prediction system for Bangladesh, in this study, historical data set-driven long short term memory (LSTM) networks method has been used, which overcomes the complexities and chaos-related problems faced by other approaches. The proposed method has three principal phases: (i) The most useful 10 features are chosen from 20 data attributes. (ii) After that, a two-layer LSTM model is designed. (iii) Both conventional machine learning approaches and recent works are compared with the LSTM model. This approach has gained 97.14% accuracy in predicting rainfall (in millimeters), which outperforms the state-of-the-art solutions. Also, this work is a pioneer work to the rainfall prediction system for Bangladesh.<\/jats:p>","DOI":"10.1515\/comp-2022-0254","type":"journal-article","created":{"date-parts":[[2022,10,18]],"date-time":"2022-10-18T18:12:04Z","timestamp":1666116724000},"page":"323-331","source":"Crossref","is-referenced-by-count":16,"title":["Rainfall prediction system for Bangladesh using long short-term memory"],"prefix":"10.1515","volume":"12","author":[{"given":"Mustain","family":"Billah","sequence":"first","affiliation":[{"name":"Department of Computer Science and Engineering, Jashore University of Science and Technology , Jashore , Bangladesh"}]},{"given":"Md. Nasim","family":"Adnan","sequence":"additional","affiliation":[{"name":"Department of Computer Science and Engineering, Jashore University of Science and Technology , Jashore , Bangladesh"}]},{"given":"Mostafijur Rahman","family":"Akhond","sequence":"additional","affiliation":[{"name":"Department of Computer Science and Engineering, Jashore University of Science and Technology , Jashore , Bangladesh"}]},{"given":"Romana Rahman","family":"Ema","sequence":"additional","affiliation":[{"name":"Department of Computer Science and Engineering, Jashore University of Science and Technology , Jashore , Bangladesh"}]},{"given":"Md. Alam","family":"Hossain","sequence":"additional","affiliation":[{"name":"Department of Computer Science and Engineering, Jashore University of Science and Technology , Jashore , Bangladesh"}]},{"given":"Syed","family":"Md. Galib","sequence":"additional","affiliation":[{"name":"Department of Computer Science and Engineering, Jashore University of Science and Technology , Jashore , Bangladesh"}]}],"member":"374","published-online":{"date-parts":[[2022,10,17]]},"reference":[{"key":"2022101818111748589_j_comp-2022-0254_ref_001","doi-asserted-by":"crossref","unstructured":"E. C. Stephens, A. D. Jones, and D. Parsons, \u201cAgricultural systems research and global food security in the 21st century: An overview and roadmap for future opportunities,\u201d Agricult. Sys., vol. 163, pp. 1\u20136, 2018.","DOI":"10.1016\/j.agsy.2017.01.011"},{"key":"2022101818111748589_j_comp-2022-0254_ref_002","unstructured":"D. Bhandari and A. Dixit, \u201cMissed Opportunities in Utilization of Weather Forecasts: An Analysis of October 2021 Disaster in Nepal,\u201d ISET Nepal Publication, Nepal, 2022."},{"key":"2022101818111748589_j_comp-2022-0254_ref_003","doi-asserted-by":"crossref","unstructured":"F. Mekanik, M. A. Imteaz, S. 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