Sonar Data Classification Using a New Algorithm Inspired from Black Holes Phenomenon

• Published in: International journal of information retrieval research Vol. 8; no. 2; pp. 25 - 39
• Main Authors: Rahmani, Mohamed Elhadi, Amine, Abdelmalek, Hamou, Reda Mohamed
• Format: Journal Article
• Language: English
• Published: Hershey IGI Global 01.04.2018
• Subjects: Algorithms; Classification; Computer science; Data mining; Foraging behavior; Genetic algorithms; Heuristic; Heuristic methods; Information retrieval; Knowledge discovery; Light; Machine learning; Nature; Radar systems; Social networks; Sonar; Sonar systems; Sound propagation; Sound waves; Underwater acoustics; Wave propagation; Algeria
• ISSN: 2155-6377; 2155-6385
• DOI: 10.4018/IJIRR.2018040102

Sound Navigation and Ranging (Sonar) is underwater sound detection used in boats or submarines to navigate, communicate with or detect objects under the surface of water based on sound propagation. It is helpful for exploring and mapping the ocean because sound waves travel farther in the water than do radar and light waves. Based on signal data obtained from sonar, this article presents a new heuristic approach inspired from black holes' phenomenon proposed by Schwarzschild, it has been applied to the classification sonar returns from two undersea targets, a metal cylinder and a similarly-shaped rock. Results are very satisfied (almost 83% of accuracy) compared to original works. in manner that encourage to keep working on paper, the main idea of this article is to benefit from the power of nature to solve complex problems in computer science