THE CHAOTIC OPTIMIZATION NEURAL NETWORK MODEL OF THE CONCRETE STRENGTH

Because main factors of influencing high strength and high performance concrete strength are considered, BP neural network can deal with non-line problem and forecast concrete strength. To overcome shortage of slow constringency speed and anesthesia phenomenon in conventional BP network, this paper, the back-propagation (BP) network is trained using adaptive variable step-size arithmetic. ABPM neural network model with chaotic optimization is put forward. The forecast result and training effect are analyzed and compared. Its excellence is mainly a good search interface in grads arithmetic using searching characteristic of chaotic motion. Calculating result makes know that this method is used to speed up the convergence and improve the performance.