Prediction of temperature using linear regression

Autor:	Sindhu P. Menon, Pooja Shetty, Sai Nagendra, Prajwal Sanu, Ramith Bharadwaj
Rok vydání:	2017
Předmět:	Pollution geography education.field_of_study geography.geographical_feature_category Variables media_common.quotation_subject Population Urban area Metropolitan area Linear regression Statistics Environmental science Urban heat island Time series education media_common
Zdroj:	2017 International Conference on Electrical, Electronics, Communication, Computer, and Optimization Techniques (ICEECCOT).
Popis:	An urban heat island (UHI) is an urban area or metropolitan area that is significantly warmer than its surrounding rural areas due to human activities. The project aims to showcase the effect of UHI using temperature as the independent variable with pollution and population as the dependent factor variables. Using the Time Series analysis we obtained the trend in temperature, population and pollution. Using Multiple Linear Regression we have predicted the temperature based on the factors. The accuracy of the predicted values is depicted by comparing the predicted and measured values of the years 2013–2016. Hence proving that the predicted value is accurate and measures must be taken to prevent this or the temperature will increase to an unlivable extent.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::089b2460837a473ba047d8b1b8142afb https://doi.org/10.1109/iceeccot.2017.8284588 Zobrazit plný text záznamu