ANN for Predicting Temperature and Humidity in the Surrounding Environment

Download Edit this record How to cite View on PhilPapers
Abstract: In this research, an Artificial Neural Network (ANN) model was developed and tested to predict temperature in the surrounding environment. A number of factors were identified that may affect temperature or humidity. Factors such as the nature of the surrounding place, proximity or distance from water surfaces, the influence of vegetation, and the level of rise or fall below sea level, among others, as input variables for the ANN model. A model based on multi-layer concept topology was developed and trained using data from several regions in the surrounding environment. The evaluation of testing the dataset shows that the ANN model is capable of correctly predicting the temperature with 100% accuracy.
No categories specified
(categorize this paper)
PhilPapers/Archive ID
Upload history
Archival date: 2020-01-02
View other versions
Added to PP index

Total views
74 ( #49,651 of 2,448,745 )

Recent downloads (6 months)
13 ( #41,162 of 2,448,745 )

How can I increase my downloads?

Downloads since first upload
This graph includes both downloads from PhilArchive and clicks on external links on PhilPapers.