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Identifying fault prone modules at the very early stage of software development life cycle is very much necessary. This helps software developers to concentrate more on quality assurance, use the man power in proper perspective and mainly reduce the fault removal cost to be in-cured for the software system being developed. In literature, it is found that numerous authors have come up with cost based...
Residential loan plays an important role for commercial banks to keep away from credit risks. This paper uses neural networks for residential loan, and trains the networks with two evolutional algorithms-genetic algorithm (GA) and particle swarm optimization (PSO). And a GA neural network and a PSO neural network are constructed respectively. The two neural networks are used to classify the residential...
Personal credit scoring plays an important role for commercial banks to keep away from consumer credit risks. This paper used neural networks for personal credit scoring and used two evolutional algorithms of genetic algorithm (GA) and particle swarm optimization (PSO) to train the networks to construct a GA neural network and a PSO neural network respectively. The two neural networks were used to...
Base stations in wireless local area networks (WLAN) need to provide good link to the backbone of communication system. Generally, problem can be reduced to a given building, where it is needed to determine the number and the positions of base stations in order to cover the building with minimum resources, i.e. proper selection of base station positions is necessary to provide adequate signal coverage...
This paper introduces a new hybrid approach for training the adaptive network based fuzzy inference system (ANFIS). The previous works emphasized on gradient base method or least square (LS) based method. In this study we apply one of the swarm intelligent branches, named particle swarm optimization (PSO). The hybrid method composes PSO with gradient decent (GD) for training. We use PSO with some...
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