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Attribute reduction is one of important problem of rough set theory. In order to get effectively attribute reduction, we presented an algorithm of attribute reduction of rough set based on improved adaptive genetic algorithm (IAGA). IAGA adjusts the crossover probability and mutation probability of each individual according to individual fitness value. The optimization capability and the convergence...
Dependent tasks scheduling in grid environment is a NP-complete problem. Convergence in the accuracy for conventional GA is better than other scheduling algorithms, but the speed of convergence is too slow in a realistic scheduling. In view of this situation, this paper presents a hybrid adaptive genetic algorithm (HAGA) which can improve the local search ability by adding the adjustment for the specific...
This paper focuses on the discussion about the briefest reduct of Rough Sets which is extracted by genetic algorithm. The fitting function is designed by the combination of the relying degree of RS and sum of seeds which is the attributes of data. Genetic Algorithm operator is applied and the algorithm is tested by UCI database. After the analysis and discussion, RGA and RGA_2 have been proved available...
To handle massive binary-coding infeasible solutions in distribution network reconfiguration, a sequence coding is presented. A loop is a gene and the switch sequence in the loop is the gene value. To resolve mutation probability and slow later-period convergence in clonal genetic algorithm(CGA), particle clonal genetic algorithm(PCGA) is proposed. It builds particle swarm algorithm (PSO) mutation...
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