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Multimodal optimization aims at locating multiple optima in a run, which has two main advantages over traditional single objective global optimization. First, it would be useful to provide multiple solutions since some solutions may be hard to realize physically. Second, a multimodal algorithm is not so easy to get stuck in a local optimum. In recent years, multi-population evolutionary algorithms...
Firstly, this paper established an optimization model on laying photovoltaic battery with the optimal horizontal obliquity aiming at maximum radiation intensity and the slope obliquity as the decision variable. Then, proposed an “Embedded Search Algorithm” to solve this model. The algorithm not only has high computation efficiency, but also can according to the requirements of the project to achieve...
SVM (Support Vector Machine) based on statistical learning theory and structural risk minimization principle has shown good performance and unique advantages in resolving the non-linear and high dimension problems with limited samples. However, the parameters of SVM have a significant impact on the identifying accuracy and generalization ability of SVM. It is based on the fact that this paper uses...
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