Neural Network Studies. 2. Variable Selection

1996 ◽  
Vol 36 (4) ◽  
pp. 794-803 ◽  
Author(s):  
Igor V. Tetko ◽  
Alessandro E. P. Villa ◽  
David J. Livingstone
Keyword(s):  
Neural Network ◽  
Variable Selection ◽  
Network Studies

Neural Network Studies. 3. Variable Selection in the Cascade-Correlation Learning Architecture

1998 ◽  
Vol 38 (4) ◽  
pp. 651-659 ◽  
Author(s):  
Vasyl V. Kovalishyn ◽  
Igor V. Tetko ◽  
Alexander I. Luik ◽  
Vladyslav V. Kholodovych ◽  
Alessandro E. P. Villa ◽  
...  
Keyword(s):  
Neural Network ◽  
Variable Selection ◽  
Cascade Correlation ◽  
Correlation Learning ◽  
Network Studies

Neural Network Studies

1993 ◽  
Author(s):  
Gregg Wilensky ◽  
Narbik Manukian ◽  
Joseph Neuhaus ◽  
Natalie Rivetti
Keyword(s):  
Neural Network ◽  
Network Studies

A Novel Quantum Neural Network Model with Variable Selection for Short Term Load Forecasting

2010 ◽  
Vol 20-23 ◽  
pp. 612-617 ◽  
Author(s):  
Wei Sun ◽  
Yu Jun He ◽  
Ming Meng
Keyword(s):  
Neural Network ◽  
Variable Selection ◽  
Network Model ◽  
Neural Network Model ◽  
Load Forecasting ◽  
Short Term ◽  
Bp Network ◽  
Quantum Neural Network ◽  
Short Term Load Forecasting ◽  
Selection For

The paper presents a novel quantum neural network (QNN) model with variable selection for short term load forecasting. In the proposed QNN model, first, the combiniation of maximum conditonal entropy theory and principal component analysis method is used to select main influential factors with maximum correlation degree to power load index, thus getting effective input variables set. Then the quantum neural network forecating model is constructed. The proposed QNN forecastig model is tested for certain province load data. The experiments and the performance with QNN neural network model are given, and the results showed the method could provide a satisfactory improvement of the forecasting accuracy compared with traditional BP network model.

Neural Network-based Evaluation of the Effect of the Motivation of Hospital Employees on Patients’ Satisfaction

2010 ◽  
Vol 5 (4) ◽  
pp. 1-19 ◽  
Author(s):  
Payam Hanafizadeh ◽  
Neda Rastkhiz Paydar ◽  
Neda Aliabadi
Keyword(s):  
Neural Network ◽  
Organizational Performance ◽  
Back Propagation ◽  
Employee Motivation ◽  
Back Propagation Neural Network ◽  
Distributed Data ◽  
Hospital Employees ◽  
The Neural Network ◽  
Using Data ◽  
Network Studies

This article evaluates the effect of the motivation of employees on organizational performance using a neural network. Studies show that employee motivation influences organizational performance, particularly in organizations providing services. Methods based on statistical computations like regression and correlation analysis were used to measure the mutual effects of these factors. As these statistical methods necessitate the fulfillment of certain requirements like normally distributed data and because they are not able to express non-linear relations and hidden complicated patterns, a back propagation neural network has been used. The neural network was trained by using data from 300 questionnaires answered by hospital employees and 1933 patients hospitalized in a private hospital in Tehran over three successive months.

Neural network studies 2. Use of a neural net to estimate oxidation energies for substituted dihydropyridines and related heterocycles

Tetrahedron ◽  
1992 ◽  
Vol 48 (17) ◽  
pp. 3463-3472 ◽  
Author(s):  
Marcus E. Brewster ◽  
Ming-Ju Huang ◽  
Alan Harget ◽  
Nicholas Bodor
Keyword(s):  
Neural Network ◽  
Neural Net ◽  
Network Studies
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