Comparison of coastal wind speed in Southeast Asian Countries using ANN backpropagation algorithm

Abstract

This study aims to analyze the neural network backpropagation (ANN-BP) algorithm in seeing the development and comparison of wind speed. We estimated the wind speed of coastal areas with a case study of five countries in Southeast Asia. We used data for the last 10 years in the form of monthly data. The ANN-BP architecture uses input layers, three hidden layers, and one output layer with 12-25-10-1 architecture. From the simulation results in the training stage, we obtained information that the data model that is closest or follows the wind speed pattern with the smallest MSE value is the coastal area in Thailand with an MSE value of 0.00012 in the training stage and 0.00011 in the testing stage. Then, we also obtained that the average prediction of wind speed on the coast of Brunei Darusslam obtained the smallest value compared to other countries.