求翻译：本算法中，设置种群个体的染色体长度h=4，交叉概率p=0.7，变异概率q=0.4。最大迭代次数为max=150。分别通过遗传算法和最大阈值方法获得的阈值求均值作为函数的最佳阈值，然后进行阈值分割。本文结合C-V算法[10]和改进遗传算法进行运行时间和熵信息比较。是什么意思？

This algorithm, the set of individuals in a population chromosome length h = 4, crossover probability p = 0.7, mutation probability q = 0.4. The maximum number of iterations max = 150. Average as the optimal threshold function obtained by the genetic algorithm and maximum threshold threshold and thr

In this algorithm, stocks of individual chromosome length H = 4, P=0.7 cross-probability and mutation probability Q = 0.4 . The maximum number of iterations to max=150. Through genetic algorithm and the maximum threshold method to get the threshold values for all as a function of the best threshold

In this algorithm, establishment population individual chromosome length h=4, overlapping probability p=0.7, variation probability q=0.4.The biggest iterative number of times is max=150.Separately the threshold value which and the biggest threshold value method obtains through the genetic algorithm

In this algorithm, set the stocks individual chromosome length h=4, crossover probability p=0.7, mutation probability q=0.4. Maximum number of iterations for Max=150. Respectively by genetic algorithm and maximum thresholds thresholds averages as a function of the method to obtain the optimal thresh

正在翻译，请等待...