Boiculese L
Department of Computer Science, Faculty of Medicine, University of Medicine and Pharmacy Gr. T. Popa, Iaşi.
Rev Med Chir Soc Med Nat Iasi. 1999 Jan-Jun;103(1-2):176-81.
Genetic algorithm (GA) represents an exploratory search mathematical technique, which uses statistical methods of selection. They are named blind search technique as they usually operate without knowledge of the task domain. GA is inspired from the evolutionary features of biological systems. The natural individual selection of offspring that are better adapted will resist in time (3). The pioneer worker in this field was John Holland and the University of Michigan staff from 1975. The beginning study was in natural adaptive process explanation and continues with computed artificial systems developing that exploit the evolution natural principles. A GA technique was applied for a controller parameter optimization that regulates the mean blood pressure. The intelligent system adjusts the anesthetic agent in order to maintain the pressure constant with small variations from a desired set value. This is usually necessary for anesthesia control (mathematical model from 11, 12). Such a system was developed and tested using computer simulations. This paper describes some aspects about the GA mathematical method and finally the results of the controller implementation are presented.
遗传算法（GA）是一种探索性搜索数学技术，它使用统计选择方法。它们被称为盲目搜索技术，因为它们通常在不了解任务领域的情况下运行。遗传算法的灵感来自生物系统的进化特征。适应性更强的后代的自然个体选择将及时保留下来（3）。该领域的先驱者是约翰·霍兰德以及1975年来自密歇根大学的工作人员。最初的研究是关于自然适应性过程的解释，并随着利用进化自然原理的计算人工系统的发展而继续。一种遗传算法技术被应用于调节平均血压的控制器参数优化。智能系统调整麻醉剂，以便将压力保持在恒定状态，与期望设定值的偏差很小。这对于麻醉控制通常是必要的（来自参考文献11、12的数学模型）。这样一个系统通过计算机模拟进行了开发和测试。本文描述了遗传算法数学方法的一些方面，最后给出了控制器实现的结果。
