{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,7]],"date-time":"2026-07-07T02:40:29Z","timestamp":1783392029165,"version":"3.54.6"},"reference-count":0,"publisher":"World Scientific Pub Co Pte Lt","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["J. Info. Know. Mgmt."],"abstract":"<jats:p> Accurate weather prediction is always a challenge for meteorologists. This paper suggests a Deep Neural Network (DNN) model to predict minimum and maximum values of temperature based on various weather parameters such as humidity, dew point, and wind speed. Particle Swarm Optimisation (PSO) algorithm is applied to select relevant and important features of the datasets to improve the prediction accuracy of the model. The grid search algorithm is employed to determine the hyperparameters of the proposed DNN model. The statistical indicators Mean Square Error, Mean Absolute Error, Mean Absolute Percentage Error, Nash\u2013Sutcliffe model efficiency coefficient, and Correlation Coefficient are used to evaluate the accuracy of the prediction model. Performance comparison of the proposed model is performed with the Support Vector Machine (SVM) and Vector Autoregression (VAR) models. The experimental outcomes show that the proposed model optimised using PSO achieves better prediction accuracy than traditional approaches. <\/jats:p>","DOI":"10.1142\/s0219649221500295","type":"journal-article","created":{"date-parts":[[2021,6,18]],"date-time":"2021-06-18T06:22:13Z","timestamp":1623997333000},"page":"2150029","source":"Crossref","is-referenced-by-count":5,"title":["An Improved Multivariate Weather Prediction Model Using Deep Neural Networks and Particle Swarm Optimisation"],"prefix":"10.1142","author":[{"given":"K U","family":"Jaseena","sequence":"first","affiliation":[{"name":"Division of Information Technology, School of Engineering, Cochin University of Science and Technology, Kochi, Kerala, India"},{"name":"Department of Computer Applications, MES College Marampally, Aluva, Kochi, Kerala, India"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Binsu C","family":"Kovoor","sequence":"additional","affiliation":[{"name":"Division of Information Technology, School of Engineering, Cochin University of Science and Technology, Kochi, Kerala, India"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"219","published-online":{"date-parts":[[2021,6,17]]},"container-title":["Journal of Information &amp; Knowledge Management"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.worldscientific.com\/doi\/pdf\/10.1142\/S0219649221500295","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2021,6,18]],"date-time":"2021-06-18T06:22:14Z","timestamp":1623997334000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.worldscientific.com\/doi\/abs\/10.1142\/S0219649221500295"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,6,17]]},"references-count":0,"alternative-id":["10.1142\/S0219649221500295"],"URL":"https:\/\/doi.org\/10.1142\/s0219649221500295","relation":{},"ISSN":["0219-6492","1793-6926"],"issn-type":[{"value":"0219-6492","type":"print"},{"value":"1793-6926","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021,6,17]]}}}