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This paper introduces a novel numerical stochastic optimization algorithm inspired from the behavior of cloud in the natural world, which is designated as Atmosphere Clouds Model Optimization Algorithm (ACMO). And the ACMO algorithm has been tested on a set of benchmark functions in comparison with Particle Swarm Optimization algorithm (PSO) and Genetic Algorithm (GA). The results demonstrate that...
Accurate electricity price forecasting can provide crucial information for electricity market participants to make reasonable competing strategies. Support vector machine (SVM) is a novel algorithm based on statistical learning theory, which has greater generalization ability, and is superior to the empirical risk minimization principle as adopted by traditional neural networks. However, its generalization...
Freight volume forecasting is significant to highway web plan. Here, support vector regression optimized by genetic algorithm (G-SVR) is proposed to forecast freight volume. We adopt genetic algorithm (GA) to seek the optimal parameters of SVR in order to improve the efficiency of prediction. The data of freight volume in a certain port from 1998 to 2007 is used as a case study. The experimental results...
Nowadays, Web services are growing very fast and are usually aggregated into a composite one to satisfy customer's more and more complex requirements. Generally, there may be several different candidate services to carry out one task in a composite service, so a choice needs to be made for helping users select the most suitable one to satisfy their end-to-end constraints. This paper addresses this...
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...
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