In order to study the prediction ability of combined model based on BP neural network, the information is gathered to established BP neural network model. The BP neural network model is built between the incidence seniority and the influencing factors and whose prediction performance is compared with the traditional model of multivariate and linear regression. Based on this we can set up linear...

This paper presents a constraint satisfaction adaptive neural network, together with several heuristics, to solve the generalized job-shop scheduling problem, one of NP-complete constraint satisfaction problems. The proposed neural network can be easily constructed and can adaptively adjust its weights of connections and biases of units based on the sequence and resource constraints of the job-...

geological facies interpretation is essential for reservoir studying. the method of classification and identification seismic traces is a powerful approach for geological facies classification and distinction. use of neural networks as classifiers is increasing in different sciences like seismic. they are computer efficient and ideal for patterns identification. they can simply learn new algori...

In this paper, Segmented Cellular Neural Network-Cellular Neural Network Combined Trellis Coded Quantization/Modulation (SCNN-CNN CTCQ/TCM) scheme is introduced. Here, a gray scaled image is lowered to 3 bit using our proposed Segmented Cellular Neural Network approach (SCNN) and then passed through a new CNN based structure which models combined trellis coded quantization / modulation. The per...

this paper addresses a nonlinear observer based control scheme to synchronize chaotic systems subject to uncertainties and external disturbances. it is assumed that the dynamic of slave system is not completely known. in order to compensate for the system perturbation resulting from parameter variations and mismodeling phenomena, an adaptive neural network observer is employed to handle this pr...