Experimental Examples for Identification of Structural Systems Using Neural Network and DOF-Based Reduction Method

2018 ◽  
pp. 59-62
Author(s):  
Heejun Sung ◽  
Maenghyo Cho
Keyword(s):  
Neural Network ◽  
Reduction Method ◽  
Structural Systems

A Prediction Method of Power Energy Saving Potential Based on Rough Set Neural Network

2010 ◽  
Vol 44-47 ◽  
pp. 3795-3799
Author(s):  
Jin Ying Li ◽  
Ya Jun Wei ◽  
Jin Chao Li ◽  
Yu Zhi Zhao
Keyword(s):  
Neural Network ◽  
Energy Saving ◽  
Rough Set ◽  
Reduction Method ◽  
Prediction Method ◽  
Pollutant Emission ◽  
Resource Saving ◽  
Environment Friendly ◽  
Knowledge Reduction ◽  
Energy Saving Potential

Power industry is the key field of implementing energy saving and pollutant emission reduction in china, strengthen power energy saving is helpful to establish a resource-saving and environment-friendly society and promote a sustainable development of economic society. This paper synchronizes respective advantages of rough set and neural network, puts forward a prediction model-RSBPNN which uses rough set knowledge reduction method to prune the redundant and neural network to build a forecasting model.

An optimization Algorithm of LVQ Neural Network Classification by GA

2013 ◽  
Vol 321-324 ◽  
pp. 2203-2208
Author(s):  
Liang Liu ◽  
Xiao Hong He ◽  
Hao Sun
Keyword(s):  
Neural Network ◽  
Optimization Algorithm ◽  
Input Data ◽  
Reduction Method ◽  
Weight Vector ◽  
Initial Vector ◽  
Data Sets ◽  
Dimension Reduction Method ◽  
Initial Weight ◽  
Neural Network Classification

This paper describes a dimension reduction method of input vector to improve classification efficiency of LVQ neural network, where GA is used to decrease the redundancy of input data. And in order to solve the initial weight vector sensitivity, GA is also employed to optimize the initial vector. The experimental results on the UCI data sets demonstrate that the efficiency and accuracy of our LVQ network by GA is higher than general LVQ neural network classification algorithm.

Wavelength Bands Reduction Method in Near-Infrared Hyperspectral Image based on Deep Neural Network for Tumor Lesion Classification

2021 ◽  
Vol 9 (1) ◽  
Author(s):  
Kohei Akimoto ◽  
Reiichirou Ike ◽  
Kosuke Maeda ◽  
Naoki Hosokawa ◽  
Toshihiro Takamatsu ◽  
...  
Keyword(s):  
Neural Network ◽  
Deep Neural Network ◽  
Near Infrared ◽  
Reduction Method ◽  
Hyperspectral Image ◽  
Tumor Lesion ◽  
Lesion Classification
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