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DSS
2006
118views more  DSS 2006»
13 years 11 months ago
Part family formation through fuzzy ART2 neural network
In order to overcome some unavoidable factors, like shift of the part, that influence the crisp neural networks' recognition, the present study is dedicated in developing a n...
R. J. Kuo, Y. T. Su, C. Y. Chiu, Kai-Ying Chen, Fa...
BMCBI
2006
169views more  BMCBI 2006»
13 years 11 months ago
Machine learning techniques in disease forecasting: a case study on rice blast prediction
Background: Diverse modeling approaches viz. neural networks and multiple regression have been followed to date for disease prediction in plant populations. However, due to their ...
Rakesh Kaundal, Amar S. Kapoor, Gajendra P. S. Rag...
BMCBI
2006
109views more  BMCBI 2006»
13 years 11 months ago
GPNN: Power studies and applications of a neural network method for detecting gene-gene interactions in studies of human disease
Background: The identification and characterization of genes that influence the risk of common, complex multifactorial disease primarily through interactions with other genes and ...
Alison A. Motsinger, Stephen L. Lee, George Mellic...
ESWA
2008
151views more  ESWA 2008»
13 years 11 months ago
Automated diagnosis of sewer pipe defects based on machine learning approaches
In sewage rehabilitation planning, closed circuit television (CCTV) systems are the widely used inspection tools in assessing sewage structural conditions for non man entry pipes....
Ming-Der Yang, Tung-Ching Su
ESWA
2008
223views more  ESWA 2008»
13 years 11 months ago
Credit risk assessment with a multistage neural network ensemble learning approach
In this study, a multistage neural network ensemble learning model is proposed to evaluate credit risk at the measurement level. The proposed model consists of six stages. In the ...
Lean Yu, Shouyang Wang, Kin Keung Lai
ENVSOFT
2008
115views more  ENVSOFT 2008»
13 years 11 months ago
Adaptive fuzzy modeling versus artificial neural networks
In this paper two areas of soft computing (fuzzy modeling and artificial neural networks) are discussed. Based on the fundamental mathematical similarity of fuzzy technique and ra...
Ralf Wieland, Wilfried Mirschel
ENGL
2008
98views more  ENGL 2008»
13 years 11 months ago
A New Wavelet Back Propagation Neural Networks for Structural Dynamic Analysis
dynamic analysis of structures for earthquake induced loads is very expensive in terms of the computational burden. In this study, to reduce the computational effort a new neural s...
R. Kamyab Moghadas, S. Gholizadeh
ENGL
2008
153views more  ENGL 2008»
13 years 11 months ago
Neural Network NARMA Control of a Gyroscopic Inverted Pendulum
The objective herein is to demonstrate the feasibility of a real-time digital control of an inverted pendulum for modeling and control, with emphasis on nonlinear auto regressive m...
F. Chetouane, S. Darenfed
EAAI
2008
128views more  EAAI 2008»
13 years 11 months ago
Dual heuristic programming based nonlinear optimal control for a synchronous generator
This paper presents the design of an infinite horizon nonlinear optimal neurocontroller that replaces the conventional automatic voltage regulator and the turbine governor (CONVC)...
Jung-Wook Park, Ronald G. Harley, Ganesh K. Venaya...
DSS
2008
91views more  DSS 2008»
13 years 11 months ago
Modeling consumer situational choice of long distance communication with neural networks
This study shows how artificial neural networks can be used to model consumer choice. Our study focuses on two key issues in neural network modeling
Michael Y. Hu, Murali S. Shanker, G. Peter Zhang, ...