基于模糊神经网络的机动车驾驶教练员职业适宜性研究

提出应用模糊神经网络系统,建构教练员职业适宜性的3个要素(即心理素质、驾驶技能和知识的表达阐述能力)的学习样本,分析"三要素"的8项特征参数指标——场依存性、速度估计能力、交通安全意识、简单反应、选择反应、跟踪能力、行车注意力、表达阐述能力等,使用K-均值法对实验样本进行初始分类,形成标准学习样本,使用该样本对所构建系统进行训练和调试。利用经调试训练后的系统,依据所测教练员的心理、心理参数对其职业适宜性进行评价。试验表明:建立的教练员职业适宜性仿真模型能取得很好的评价效果。

Study on Driver Trainer's Occupational Suitability Based on Fuzzy Neural Network

A comprehensive evaluation expert system of driver trainer's professional suitability is established.This system includes a network,a fuzzy inferring engine and a knowledge library.Eight index values(which are field dependence,speed anticipation ability,sense of traffic safety,simple response,selective response,tracking,attention and expression)are used as characteristic parameters to form the testing samples.The samples are initially classified with k-means method so as to form standard learning samples,with which the expert system are trained and adjusted.The experiments prove that the evaluation results are satisfying when the trained system is used to evaluate the driver trainer's professional suitability according to their mental and physical parameters.