Dynamic selection of composite Web services based on a genetic algorithm optimized new structured neural network

In order to realize a high-quality and good-performance service composition, based on current approach, we propose a new QoS-driven dynamic selection of composite Web services, which takes account of both the QoS properties and interface parameters matching degree. When doing the selection, we aware that the task is more or less a multistage decision-making process. Motivated by neural networks' high parallel performance and genetic algorithm's powerful computation ability, a genetic algorithm optimized neural network algorithm is proposed in this paper for such task. In order to make this algorithm more adaptable for multistage decision-making problem, we propose a new structured neural network to express the composed service instead of using the traditional neural networks, which minimizes the neurons involved and shows high performance than the earlier ones. Finally, through experimentation one can find that method proposed in this paper is more practical and effective than others