Universiti Teknologi Malaysia Institutional Repository

Genetic algorithm for oil spill automatic detection from envisat satellite data

Marghany, Maged Mahmoud (2013) Genetic algorithm for oil spill automatic detection from envisat satellite data. In: Lecture Notes In Computer Science (Including Subseries Lecture Notes In Artificial Intelligence And Lecture Notes In Bioinformatics).

Full text not available from this repository.

Official URL: https://doi.org/10.1007/978-3-642-39643-4_42

Abstract

The merchant ship collided with a Malaysian oil tanker on May 25, 2010, and spilled 2,500 tons of crude oil into the Singapore Straits. The main objective of this work is to design automatic detection procedures for oil spill in synthetic aperture radar (SAR) satellite data. In doing so the genetic algorithm tool was designed to investigate the occurrence of oil spill in Malaysian coastal waters using ENVISAT ASAR satellite data. The study shows that crossover process, and the fitness function generated accurate pattern of oil slick in SAR data. This shown by 85% for oil spill, 5% look–alike and 10% for sea roughness using the receiver –operational characteristics (ROC) curve. It can therefore be concludedcrossover process, and the fitness function have the main role in genetic algorithm achievement for oil spill automatic detection in ENVISAT ASAR data.

Item Type:Conference or Workshop Item (Paper)
Subjects:T Technology > TK Electrical engineering. Electronics Nuclear engineering
Divisions:Others
ID Code:51089
Deposited By: Haliza Zainal
Deposited On:27 Jan 2016 01:53
Last Modified:17 Sep 2017 07:05

Repository Staff Only: item control page