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针对在模量反算中,目标函数在最优值附近表现为大片狭长平坦区域的特点,提出了一类反算新算法——自适应信息遗传算法,新算法的优点是根据信息量大小来进行自适应细分模量解空间,从而节约大量的计算时间。改进了实数交叉算子,使用了新的探险策略,从而加强了新算法后期的局部搜索能力。随后的工程实例表明,这种新机制、新策略的引入,能够在保持较高反算精度的前提条件下,大大提高模量反算的求解效率,这意味着新算法能够更好地满足工程实际应用需要。
Aimed at the feature that the objective function appears as large and narrow flat area near the optimal value in the modulus inverse calculation, a new kind of inverse arithmetic - adaptive genetic algorithm is proposed. The advantage of the new algorithm is that according to the amount of information Adaptive subdivision modulus solution space, thus saving a lot of computing time. Improved real number crossover operator, using a new adventure strategy, thus strengthening the latter part of the new algorithm of local search capabilities. Subsequent engineering examples show that the introduction of this new mechanism and new strategy can greatly improve the efficiency of modulus back-calculation under the premise of maintaining a high accuracy of back-calculation, which means that the new algorithm can better meet the needs of engineering Practical needs.