Optimization of neural network based on hybrid method of genetic algorithm and particle swarm optimization for maritime weather forecasting in buoyweather station type II

Syamsul Arifin*, Dvitiya Srestha Prajna Mahistha, Magfiroh Fatwaning Ukhti, Muhammad Rifki Kurniawan, Aulia Siti Aisjah

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

The object the research is to forecast maritime weather variables such wind speed and direction, temperature and wave height for an hour ahead by using artificial intelligence approach. Artificial intelligence is comprised of hybrid neural networks modified by genetic algorithms and particle swarm optimization which are functioned as a model predictor. The hybrid predictor works on every single predictor by weighing both artificial neural network-genetic algorithm (ANN-GA) and artificial neural network-particle swarm optimization (ANN-PSO) which weight is calculated by differential evolution algorithm optimization. When the unsurpassed model is obtained, it will be validated across real-time data that is delivered from type II buoyweather station measurement at the Madura Strait, Java Sea. The prediction results of learning and validation process indicate that the ANN-Hybrid predictor perform more accurate than the ANN-GA and ANN PSO on training and validation. However, the gap of RMSE on real-time test is relatively high compared to validation or training. It can be influenced by the different frequent of weather fluctuation between them. Concurring to real-time test stage, the foremost appropriate variable that predicted by this ANN-Hybrid is temperature.

Original languageEnglish
Title of host publicationAdvanced Industrial Technology in Engineering Physics
EditorsAgus Muhamad Hatta, Katherin Indriawati, Gunawan Nugroho, Totok Ruki Biyanto, Dhany Arifianto, Doty Dewi Risanti, Sonny Irawan
PublisherAmerican Institute of Physics Inc.
ISBN (Electronic)9780735418189
DOIs
Publication statusPublished - 29 Mar 2019
Event2nd Engineering Physics International Conference 2018, EPIC 2018 - Surabaya, Indonesia
Duration: 31 Oct 20182 Nov 2018

Publication series

NameAIP Conference Proceedings
Volume2088
ISSN (Print)0094-243X
ISSN (Electronic)1551-7616

Conference

Conference2nd Engineering Physics International Conference 2018, EPIC 2018
Country/TerritoryIndonesia
CitySurabaya
Period31/10/182/11/18

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