Temperature prediction using machine learning approaches

Anjali T, Chandini K, Anoop Kadan, Lajish V. L.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

23 Citations (Scopus)

Abstract

Weather prediction is one of the most important research areas due to its applicability in real-world problems like meteorology, agricultural studies, etc. We propose a method for temperature prediction using three machine learning models - Multiple Linear Regression (MLR), Artificial Neural Network (ANN) and Support Vector Machine (SVM), through a comparative analysis using the weather data collected from Central Kerala during the period 2007 to 2015. The experimental results are evaluated using Mean Error (ME), Mean Absolute Error (MAE), Root Mean Square Error (RMSE) and Correlation Coefficients (CC). The error metrics and the CC shows that MLR is a more precise model for temperature prediction than ANN and SVM.

Original languageEnglish
Title of host publicationProceedings of the 2nd International Conference on Intelligent Computing, Instrumentation and Control Technologies, ICICICT 2019
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1264-1268
ISBN (Electronic)9781728102832, 9781728102818
ISBN (Print)9781728102825, 9781728102849
DOIs
Publication statusPublished - 13 Feb 2020
Externally publishedYes
Event2nd International Conference on Intelligent Computing, Instrumentation and Control Technologies 2019 - Kannur, India
Duration: 05 Jul 201906 Jul 2019

Conference

Conference2nd International Conference on Intelligent Computing, Instrumentation and Control Technologies 2019
Abbreviated titleICICICT 2019
Country/TerritoryIndia
CityKannur
Period05/07/201906/07/2019

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