Using Counter Propagation Neural Network for Building Intellectual Decision Support Systems

Commonly, complex modern manufactures systems’ controlling makes its operators pass important decisions what sometimes is rather difficult when there are many alternatives. Such situation requires developing and involving of automatic intellectual decision support systems (DSS). Different approaches have been already developed in order to help operator with passing correct decisions. Each has its advantages and disadvantages. This work presents a new approach to building decision support systems based on modified counter propagation neural network. Intellectual self-training automatic control systems and intellectual self-training decision support systems allow switching from old subjective methods of manual control to up to date intellectual informational control technologies for badly formalized processes and objects functioning under uncertain conditions. The following main tasks of the presented work have arisen from this assertion.