Kohonen Neural Network: A Novel Approach to Search for Bioisosteric Groups

2007 ◽  
pp. 93-106
Author(s):  
Soheila Anzali ◽  
Gerhard Barnickel ◽  
Michael Krug ◽  
Markus Wagener ◽  
Johann Gasteiger
Keyword(s):  
Neural Network ◽  
Kohonen Neural Network ◽  
Novel Approach

A novel identification approach for shearer running status through integration of rough sets and improved wavelet neural network

2016 ◽  
Vol 230 (16) ◽  
pp. 2792-2805 ◽  
Author(s):  
Lei Si ◽  
Zhongbin Wang ◽  
Xinhua Liu
Keyword(s):  
Neural Network ◽  
Genetic Algorithm ◽  
Rough Sets ◽  
Particle Swarm Optimization Algorithm ◽  
Wavelet Neural Network ◽  
Decision Table ◽  
Swarm Optimization ◽  
Novel Approach ◽  
Identification Approach ◽  
Simulation Results

In order to accurately and conveniently identify the shearer running status, a novel approach based on the integration of rough sets (RS) and improved wavelet neural network (WNN) was proposed. The decision table of RS was discretized through genetic algorithm and the attribution reduction was realized by MIBARK algorithm to simply the samples of WNN. Furthermore, an improved particle swarm optimization algorithm was proposed to optimize the parameters of WNN and the flowchart of proposed approach was designed. Then, a simulation example was provided and some comparisons with other methods were carried out. The simulation results indicated that the proposed approach was feasible and outperforming others. Finally, an industrial application example of mining automation production was demonstrated to verify the effect of proposed system.

scholarly journals Prediction of Fouling in Condenser Based on Fuzzy Stage Identification and Chebyshev Neural Network

2013 ◽  
Vol 13 (2) ◽  
pp. 94-99 ◽  
Author(s):  
Shaosheng Fan ◽  
Qingchang Zhong
Keyword(s):  
Neural Network ◽  
Prediction Model ◽  
Parameter Optimization ◽  
Adaptive Algorithm ◽  
External Disturbance ◽  
Operational Parameters ◽  
Chebyshev Neural Network ◽  
Adaptive Parameter ◽  
Novel Approach ◽  
Variation Trends

The prediction of fouling in condenser is heavily influenced by the periodic fouling process and dynamics change of the operational parameters, to deal with this problem, a novel approach based on fuzzy stage identification and Chebyshev neural network is proposed. In the approach, the overall fouling is separated into hard fouling and soft fouling, the variation trends of these two kinds of fouling are approximated by using Chebyshev neural network, respectively, in order to make the prediction model more accurate and robust, a fuzzy stage identification method and adaptive algorithm considering external disturbance are introduced, based on the approach, a prediction model is constructed and experiment on an actual condenser is carried out, the results show the proposed approach is more effective than asymptotic fouling model and adaptive parameter optimization prediction model.

New molecular surface-based 3D-QSAR method using Kohonen neural network and 3-way PLS

2002 ◽  
Vol 26 (6) ◽  
pp. 583-589 ◽  
Author(s):  
Kiyoshi Hasegawa ◽  
Shigeo Matsuoka ◽  
Masamoto Arakawa ◽  
Kimito Funatsu
Keyword(s):  
Neural Network ◽  
3D Qsar ◽  
Molecular Surface ◽  
Kohonen Neural Network
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