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Copyright of Control Theory & Applications / Kongzhi Lilun Yu Yinyong is the property of Editorial Department of Control Theory & Applications and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Computer Measurement & Control is the property of Magazine Agency of Computer Measurement & Control and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Electric Machines & Control / Dianji Yu Kongzhi Xuebao is the property of Electric Machines & Control and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

We analyze the mutation characteristics of multiple differential evolution methods and their respective appropriate search state. In order to enable individual's efficient searching with self-learning and self-regulation, we establish a feedback loop, which can help the population choose mutation strategies dynamically according to its own search conditions. MoreoverCwe also use the conjugate gradient method to find out the optimal search routes in the neighborhood of the best individuals of each generation ,and it is useful for searching locally in the neighborhood of optimal solution. Results of the next generation theoretically prove that the proposed hybrid algorithm converges to the global optimal solution at a probability of 1. Experiments on benchmark functions show that the proposed algorithm can improve the efficiency and precision in searching the optimum value. Applied to tension string design problem, the proposed algorithm is able to achieve good structure parameters. [ABSTRACT FROM AUTHOR]