Artificial neural networks, genetic algorithms and the ant colony optimization algorithm have become a highly effective tool for solving hard optimization problems. As their popularity has increased, applications of these algorithms have grown in more than equal measure. While many of the books available on these subjects only provide a cursory discussion of theory, the present book gives special emphasis to the theoretical background that is behind these algorithms and their applications. Moreover, this book introduces a novel real time control algorithm, that uses genetic algorithm and ant colony optimization algorithms for optimizing PID controller parameters.

人工神经网络、遗传算法和蚁群优化算法已经成为解决困难优化问题的高效工具。随着这些算法的普及，它们的应用也在不断增长。虽然许多关于这些主题的书籍只提供了一个粗略的理论讨论，但本书特别强调了这些算法及其应用背后的理论背景。此外，本书还介绍了一种新的实时控制算法，该算法使用遗传算法和蚁群优化算法来优化PID控制器参数。