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 Conference Papers 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/. Title A name given to the resource Prediction of Rainfall Using Seasonal Auto Regressive Integrated Moving Average and Transductive Long Short-Term Model Subject The topic of the resource Accuracy rate; Rainfall prediction; Seasonal Auto Regressive Integrated Moving Average; Time Series Analysis; Transductive Long Short-Term Model Description An account of the resource One of the most crucial parts of the practical application in recent years has been the analysis of time series data for forecasting. Because of the extreme climate variations, it is now harder than ever to estimate rainfall accurately. It is possible to forecast rainfall using a number of time series models that uncover hidden patterns in past meteorological data. Choosing the right Time Series Analysis Models for predicting is a challenging task. This study suggests using a Seasonal Auto Regressive Integrated Moving Average (SARIMA) to forecast values that are similar to historical values that exhibit seasonal patterns. Twelve years of historical weather data for the city of Lahore (from 2005 to 2017) and Blora Regency are taken into account for the prediction. The dataset underwent pre-processing operations like cleaning and normalisation before to the classification procedure. For classification, Transductive Long Short-Term Model (TLSTM) is employed which has learned the dependency values where the memory blocks are recurring and capable of learning long-term dependencies on this model. Further, TLSTM's goal is to increase accuracy close to the test point, where test points are selected as a validation group. The performance of the models has been assessed based on accuracy (99%), precision (98%), recall (96%) and fl-score (98%). Proposed SARIMA model showed optimistic results when compared to existing models. 2023 IEEE. Creator An entity primarily responsible for making the resource Phadke R.; Mohamad Ramadan G.; Archana Reddy R.; Kumar Pani A.; Al-Jawahry H.M. Source A related resource from which the described resource is derived IEEE 1st International Conference on Ambient Intelligence, Knowledge Informatics and Industrial Electronics, AIKIIE 2023 Publisher An entity responsible for making the resource available Institute of Electrical and Electronics Engineers Inc. Date A point or period of time associated with an event in the lifecycle of the resource 2023-01-01 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1109/AIKIIE60097.2023.10390346" target="_blank" rel="noreferrer noopener">https://doi.org/10.1109/AIKIIE60097.2023.10390346</a> <br /><br /><a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85187257517&amp;doi=10.1109%2FAIKIIE60097.2023.10390346&amp;partnerID=40&amp;md5=eefe494d87dd726dbda70f9945426acb" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85187257517&amp;doi=10.1109%2fAIKIIE60097.2023.10390346&amp;partnerID=40&amp;md5=eefe494d87dd726dbda70f9945426acb</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISBN: 979-835031646-9 Format The file format, physical medium, or dimensions of the resource Online Language A language of the resource English Type The nature or genre of the resource Conference paper Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Phadke R., Nitte Meenakshi Institute of Technology, Department of Electronics and Communication Engineering, Bangalore, India; Mohamad Ramadan G., College of Mlt Ahl Al Bayt University, Karbala, Iraq; Archana Reddy R., School of Computer Science and Artificial Intelligence Sr University, Warangal, India; Kumar Pani A., Christ (Deemed to Be University), Department of Computer Science and Engineering, Bangalore, India; Al-Jawahry H.M., The Islamic University, Najaf, Iraq