Application of firefly algorithm and ANFIS for optimisation of functionally graded beams

Autor:	M H Yas, S. Kamarian, Amin Pourasghar, M. Daghagh
Rok vydání:	2013
Předmět:	Vibration Mathematical optimization Adaptive neuro fuzzy inference system Artificial neural network Artificial Intelligence Computer science Genetic algorithm Process (computing) Imperialist competitive algorithm Firefly algorithm Natural frequency Software Theoretical Computer Science
Zdroj:	Journal of Experimental & Theoretical Artificial Intelligence. 26:197-209
ISSN:	1362-3079 0952-813X
DOI:	10.1080/0952813x.2013.813978
Popis:	Volume fraction optimisation of functionally graded beams is studied for maximising the fundamental natural frequency by applying a new meta-heuristic nature-inspired algorithm called firefly algorithm (FA) which is based on the flashing behaviour of fireflies. Nature-inspired algorithms are among the most powerful algorithms for optimisation of engineering problems. The primary optimisation variables are the three parameters in the power-law distribution. Since the search space is large, the optimisation processes becomes so complicated and too much time consuming. Thus, a suitable Adaptive Neuro-Fuzzy Inference System (ANFIS) that is based on Takagi–Sugeno fuzzy inference system is combined with FA to reproduce the behaviour of the structure in free vibration. The ANFIS improves the speed of optimisation process by a considerable amount. The results are compared with those obtained by imperialist competitive algorithm, genetic algorithm and Artificial Neural Networks proposed in our previous work. Resul...
Databáze:	OpenAIRE
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