Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Faculty Publications Conference Paper Faculty Publications- Conference Papers Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Creator An entity primarily responsible for making the resource Rathore, Nitasha; Anubha; Singh, Kuljeet; Kaur, Gaganpreet; Sharma, Chetna; Sinha, Anurag Title A name given to the resource Using Recurrent Neural Networks to Forecast Climate Change: A Time Series Analysis of Global Temperature Variability Date A point or period of time associated with an event in the lifecycle of the resource 01-01-2025 Source A related resource from which the described resource is derived 1st International Conference on Advances in Computer Science, Electrical, Electronics, and Communication Technologies, CE2CT 2025;pp.425-430 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1109/CE2CT64011.2025.10939247" target="_blank" rel="noreferrer noopener">https://doi.org/10.1109/CE2CT64011.2025.10939247</a> <br /><br /><a href="https://www.scopus.com/pages/publications/105002701506?origin=resultslist" target="_blank" rel="noreferrer noopener">https://www.scopus.com/pages/publications/105002701506?origin=resultslist</a> Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Rathore N., Bharatiya Vidyapeeth College of Engineering, Department of Computer Science and Engineering, New Delhi, India; Anubha, KIET Group of Institutions, India; Singh K., School of Sciences, Christ University, Department of Computer Science, Delhi NCR, India; Kaur G., Chitkara University Institute of Engineering and Technology, Chitkara University, Punjab, India; Sharma C., Chitkara University Institute of Engineering and Technology, Chitkara University, Punjab, India; Sinha A., IGNOU, Department of Computer science, New Delhi, India Description An account of the resource Predicting the upcoming weather instances is very crucial. It depends on different climatic parameters like humidity, pressure, temperature, etc. In this paper, the historical data of the weather in the India area is used for future weather instances of the India for farmers' convenience in terms of the agricultural instance which depends on the weather and, functioning according to that which will restore the energy. For weather forecasting we have use the machine learning algorithm and probabilistic predictions of the predictive analytics based on soft computing and. NGBoost algorithm and. Linear models of the machine learning for predictive. Comparative weather incidence spaced on the historical data. We have also used, sliding window algorithm of the statistics for predicting the ideology of the concept of different contrasted windows and year. We've also used utility thirds and machine learning algorithm, classified for predicting the weather based on different features The overall implementation in this paper, shows the accuracy which we have gathered from the data set. An implementation of algorithm which ranges between 80% to 90% and the entire algorithm have been compared based on the feature instances. Work can be concluded on the measurement of the algorithm, which we have got after the implementation of Models. Which rely upon the different data features and thus it can be beneficial for preserving the energy and materials in the India agriculture area and forecasting the weather as per day Agricultural conditions. 2025 IEEE. Subject The topic of the resource Climate change; Deep learning; Recurrent Neural Network Publisher An entity responsible for making the resource available Institute of Electrical and Electronics Engineers Inc. Relation A related resource ISBN: 979-833151857-8; Language A language of the resource English Type The nature or genre of the resource Conference paper Rights Information about rights held in and over the resource Restricted Access; Hardcopy may be available in the library Format The file format, physical medium, or dimensions of the resource online