In allusion to the low correctness and efficiency of fault diagnosis for the complex industrial system, rough set theory, particle swarm optimization and back propagation (BP) neural network are introduced to propose a hybrid intelligent fault diagnosis(RPBPNN) method in this paper. In the proposed RPBPNN method, rough set theory as a new mathematical tool is used to process inexact and uncerta...

modeling of stream flow–suspended sediment relationship is one of the most studied topics in hydrology due to itsessential application to water resources management. recently, artificial intelligence has gained much popularity owing toits application in calibrating the nonlinear relationships inherent in the stream flow–suspended sediment relationship. thisstudy made us of adaptive neuro-fuzzy ...

Decision-making process in manufacturing environment is increasingly difficult due to the rapid changes in design and demand of quality products. To make decision making process online, effective and efficient artificial intelligent tools like neural networks are being attempted. This paper proposes the development of neural network models for prediction of weld quality in Submerged Arc Welding...

As science and technology advance, industrial manufacturing processes get more complicated. Back Propagation Neural Network (BPNN) convergence is comparatively slower for processing nonlinear systems. The system used in this study to evaluate the optimization of BPNN based on LM algorithm proved algorithm’s efficacy through a MATLAB simulation analysis. This paper examined application impact en...

This paper presents an ensemble of duo output neural networks (DONN) using bagging technique to solve binary classification problems. DONN is a neural network that is trained to predict a pair of complementary outputs which are the truth and falsity values. Each component in an ensemble contains two DONNs in which the first network is trained to predict the truth and falsity outputs whereas the...

In this paper, a face recognition system for personal identification and verification using Principal Component Analysis (PCA) with Modified Back Propagation Neural Networks (MBPNN) is proposed. The dimensionality of face image is reduced by the PCA and the recognition is done by the MBPNN. The system consists of a database of a set of facial patterns for each individual. The characteristic fea...

Using the theory and method of artificial neural network, this paper established a decision-making model of bid evaluation for engineering projects based on back propagation neural network (BPNN). BP neural network was trained and tested by the learning sample that was attained by using order relation analysis method (G1-method). At the same time, we used the momentum BP algorithm to solve the ...

In the previous study, we have proposed a template design method of cellular neural networks with back propagation algorithm. In that method, template learns by using the average error which corresponds to the difference between the output image and the desired image. In this study, we modify the back propagation algorithm for cellular neural networks template design. We inspect the performance...