Study on Optimization for Electric-Mechanic Transmission Parameters

Based on the optimal design theory, the optimization model for electric-mechanic transmission parameters is established in this paper, and genetic arithmetic is used to solve the optimization model. Comparing the transmission’s performance before optimization with that after optimization, the result shows that the motor design difficulty is reduced and the transmission’s performance is improved after optimaization.

Application of Genetic Arithmetic and Support Vector Machine in Prediction of Compression Index of Clay

The compression index is an important soil property that is essential to many geotechnical designs. As the determination of the compression index from consolidation tests is relatively time-consuming. Support Vector Machine (SVM) is a statistical learning theory based on a structural risk minimization principle that minimizes both error and weight terms. Considering the fact that parameters in SVM model are difficult to be decided, a genetic SVM was presented in which the parameters in SVM method are optimized by Genetic Algorithm (GA). Taking plasticity index, water content, void ration and density of soil as primary influence factors, the prediction model of compression index based on GA-SVM approach was obtained. The results of this study showed that the GA-SVM approach has the potential to be a practical tool for predicting compression index of soil.

The Truss Structural Optimization Design Based on Improved Hybrid Genetic Algorithm

Genetic arithmetic operators in genetic algorithm be improved , and a hybrid genetic algorithm of a gradient algorithm combining with the genetic algorithm be given against to the defects such as premature，slow on convergence rate，weak in the ability of local search ，all these appeared on the progress of genetic algorithm's iteration. Analysis result indicate that not only strong on the local search capacity of gradient algorithm be exhibited but also strong on the general search capacity of genetic algorithm be combined based on the hybrid genetic algorithm ,which make phenomenon of premature avoid, and the rate of convergence be improved greatly. Concrete calculated example indicated that the hybrid genetic algorithm is an effective structural optimization method.