| Summary: | 碩士 === 南台科技大學 === 電機工程系 === 101 === This thesis presents artificial immune system (AIS) as the main to solve multi-objective optimization problem, based on simulated the organism's immune system and focused on the behaviors between antigen and antibody. First, calculating the affinities and concentrations between antigen vs. antibody, antibody vs. antibody, and making memories and inhibitions. In the fitness function by the limit conditions to achieve the matching state. But Immune Algorithm was still unfamiliar and incomplete in the optimization, so we tried to combine with Genetic Algorithm (GA) and Particle Swarm Algorithm (PSO) to rapidly converge and find the approximate global optimum for the system. Finally, we used this method and fuzzy control theory to the motorists handling and the ride comfort for the vehicle suspension system, such as multi-objective optimization problem to permit its results.
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