Journal of Engineering and Applied Sciences
ISSN: Online 1818-7803ISSN: Print 1816-949x
Abstract
Sea transportation is a mainstay transportation in Indonesia, it is because Indonesia consists of thousands of islands, so that, to connect between islands, sea transportation is needed. Waves are very closely related to the sea, waves that are negative that is waves that can endanger shipping. One of the factors causing sea accidents is natural disasters, namely high waves. To minimize accidents due to high waves, wave predictions can be made in the hours to come using the neural network algorithm. Neural network was chosen because of its advantages in processing system input-output data even though the system is nonlinear. The advantage is that the neural network is chosen as a wave height predictor algorithm. ANFIS is an algorithm for the development of a combination of neural networks and fuzzy artificial intelligence. The ability of ANFIS to predict wave heights is no less good with neural networks, it is because ANFIS is a combination of neural network and fuzzy. It is hoped that by doing this research it can compare which algorithm is better in predicting wave heights.
How to cite this article:
Mufidatul Islamiyah, Wisnu Wardhana and Wimala L. Dhanistha. Maritime Weather Predictor Design Based Neural Network and
ANFIS to an Increase in Accuracy in the Java Sea.
DOI: https://doi.org/10.36478/jeasci.2020.1724.1727
URL: https://www.makhillpublications.co/view-article/1816-949x/jeasci.2020.1724.1727