Title :
Damaged ship unsinkability classification model based on fuzzy support vector machine
Author :
Hou, Yue ; Pu, Jin-yun
Author_Institution :
Ship survivability Res. office, Naval Univ. of Eng., Wuhan, China
Abstract :
When the ship is damaged after weapon attack, it is necessary for commanders to recognise its unsinkability grade quickly. Through unsinkability classification, we can know whether the ship will sink or not and its sinking probability. The unsinkability classification is a N-class pattern recognition problem. The fuzzy support vector machine (FSVM) is used to distinguish a certain unsinkability grade from other unsinkability grades firstly. Concerning the definition of fuzzy membership is critical in FSVM, the support vector data description (SVDD) is used to found fuzzy membership function. Through samples test, we found that FSVM of which fuzzy membership calculated through SVDD has better classification efficiency and precision.
Keywords :
fuzzy set theory; marine engineering; pattern classification; ships; support vector machines; N-class pattern recognition problem; damaged ship unsinkability classification model; fuzzy membership function; fuzzy support vector machine; sinking probability; support vector data description; Accuracy; Kernel; Marine vehicles; Optimization; Pattern recognition; Support vector machines; Training; FSVM; SVDD; damaged ship; fuzzy membership function; unsinkability classification;
Conference_Titel :
Fuzzy Systems and Knowledge Discovery (FSKD), 2010 Seventh International Conference on
Conference_Location :
Yantai, Shandong
Print_ISBN :
978-1-4244-5931-5
DOI :
10.1109/FSKD.2010.5569336