Title :
Multi-objective particle swarm optimization algorithm and its application to the fuzzy rule based classifier design problem with the order based semantics of linguistic terms
Author :
Phong Pham Dinh ; Ho Nguyen Cat ; Thuy Nguyen Thanh
Author_Institution :
Inf. Technol. Dept., Prevoir Vietnam, Ha Noi, Vietnam
Abstract :
A method of designing fuzzy rule based classification systems (FRBCSs) using multi-objective optimization evolutionary algorithms (MOEAs) clearly depends on evolutionary quality. There are two types of such algorithms: Genetic Algorithms (GAs) and Swarm Intelligence (SI). Naturally arises a question how strongly utilized evolutionary algorithms influence on the efficiency of a method of designing FRBCS making this better than another. Particle swarm optimization (PSO) algorithm [13, 14] is among SI series. This paper represents an application of the multi-objective PSO algorithm with fitness sharing (MO-PSO) proposed in [8] to optimize the semantic parameters of linguistic variables and fuzzy rule selection in designing FRBCSs based on hedge algebras proposed as in [7] (using GSA-genetic simulated annealing algorithm). By simulation, MO-PSO is shown to be more efficient and produces better results than GSA-algorithm. That is to show a method of the FRBCS design is better than another one using MOEA, the same MOEA must be used.
Keywords :
computational linguistics; fuzzy set theory; genetic algorithms; knowledge based systems; particle swarm optimisation; pattern classification; simulated annealing; swarm intelligence; FRBCS; GSA; MO-PSO; MOEA; SI; evolutionary quality; fitness sharing; fuzzy rule based classification systems; fuzzy rule based classifier design problem; fuzzy rule selection; genetic simulated annealing algorithm; hedge algebra; linguistic terms; linguistic variable semantic parameters; multiobjective PSO algorithm; multiobjective optimization evolutionary algorithm; multiobjective particle swarm optimization algorithm; order based semantics; swarm intelligence; Algorithm design and analysis; Classification algorithms; Fuzzy sets; Optimization; Pragmatics; Semantics; Fuzzy Classification System; Hedge Algebras; PSO; Particle Swarm Optimization;
Conference_Titel :
Computing and Communication Technologies, Research, Innovation, and Vision for the Future (RIVF), 2013 IEEE RIVF International Conference on
Conference_Location :
Hanoi
Print_ISBN :
978-1-4799-1349-7
DOI :
10.1109/RIVF.2013.6719858