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中文摘要：
中心引力优化算法（Central Force Optimization）是一种新型的基于天体力学的多维搜索优化算法．这是一种确定性的优化算法，该算法利用一组“质子”在引力作用下的运动，搜索决策空间最优值．但该算法仍然有局部收敛的特点．本文对该算法中质子运动方程做了分析研究，利用天体力学中的摄动理论对算法进行了改进，给出了改进后的新的CFO算法的迭代公式，并且对新的公式进行了分析．最后实验结果表明针对CFO算法的摄动改进可以使得搜索质子跳过CFO空间中的局部解，使得算法收敛精度和速度都有了不同程度的提高．
英文摘要：
Central Force Optimization （CFO）is a new deterministic multi-dimensional search metaheuristic based on the metaphor of gravitational kinematics. CPO is a deterministic algorithm that explores a decision space by＂ flying＂ a group of probes whose trajectories are governed by Newton＇ s laws.But it may be local trapping. This paper makes a thorough research on the probes move governed by the equations of gravitational motion through the Celestial Mechanics, establishing the relationship between CPO algorithm and Celestial Mechanics,using the perturbation theory of Celestial Mechanics to improve CFO algorithms and deducing the new iterative equation. Finally, simulation results show that CTO based on perturbation theory avoids local trap. The enhanced algorithm has great advantage of convergence property and robustness compared to stochastic algorithms.
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Enabling End-to-End Communication Between Wireless Sensor Networks and the Internet Based on 6LoWPAN
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