Predicting airline passengers’ loyalty using artificial neural network theory

Based on MATLAB, the article apply BP artificial neural network theory on the forecasting problem of time sequence in geotechnical engineering, and find it is an effecting way to solve the forecasting problem of time sequence in geotechnical engineering.

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Fault predictive diagnosis of wind turbine based on LM arithmetic of Artificial Neural Network theory

2011 Seventh International Conference on Natural Computation ◽

10.1109/icnc.2011.6021921 ◽

2011 ◽

Cited By ~ 3

Author(s):

Lincang Ju ◽

Dekuan Song ◽

Beibei Shi ◽

Qiang Zhao

Keyword(s):

Neural Network ◽

Artificial Neural Network ◽

Wind Turbine ◽

Network Theory ◽

Predictive Diagnosis ◽

Artificial Neural ◽

Neural Network Theory

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Part 1: Artificial neural network theory / Partie 1 : la théorie des réseaux neuronaux artificiels

Journal of Environmental Engineering and Science ◽

10.1139/part1 ◽

2004 ◽

Vol 3 (S1) ◽

Keyword(s):

Neural Network ◽

Artificial Neural Network ◽

Network Theory ◽

Artificial Neural ◽

Neural Network Theory

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Study on Hairiness of Polyester/Cotton Blended Yarn in Rotor Spinning Via Artificial Neural Network Theory

Lecture Notes in Electrical Engineering - Proceedings of the International Conference on Information Engineering and Applications (IEA) 2012 ◽

10.1007/978-1-4471-4853-1_61 ◽

2013 ◽

pp. 487-494

Author(s):

Bo Zhao

Keyword(s):

Neural Network ◽

Artificial Neural Network ◽

Network Theory ◽

Rotor Spinning ◽

Blended Yarn ◽

Artificial Neural ◽

Neural Network Theory

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BP Neural Network Model on Choice of Project Manager for Highway Slope Treatment

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.505-506.274 ◽

2014 ◽

Vol 505-506 ◽

pp. 274-277

Author(s):

Bin Wang ◽

Yong Tao Gao

Keyword(s):

Neural Network ◽

Artificial Neural Network ◽

Neural Network Model ◽

Bp Neural Network ◽

Network Theory ◽

Influence Factors ◽

Project Manager ◽

Slope Treatment ◽

Neural Network Theory ◽

Bp Neural Network Model

To get the quantified indexes of comprehensive capacity about project manager, based on the modal on artificial neural network theory, different influence factors about choice of project manager for highway slope treatment were analyzed , identified, quantified and evaluated , then comprehensive capacity of the manager were analyzed. Such procedure provided a new method for choice of project manager for highway slope treatment.

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ORDINATION ANALYSIS OF TAXUS CHINENSIS VAR. MAIREI FORESTS BASED ON ARTIFICIAL NEURAL NETWORK THEORY

International Journal of Biomathematics ◽

10.1142/s1793524510000854 ◽

2010 ◽

Vol 03 (01) ◽

pp. 69-78 ◽

Cited By ~ 2

Author(s):

JIN-TUN ZHANG ◽

WENMING RU

Keyword(s):

Neural Network ◽

Artificial Neural Network ◽

Data Matrix ◽

Shanxi Province ◽

Taxus Chinensis ◽

Forest Types ◽

Soil Variables ◽

Topographical Factors ◽

Artificial Neural ◽

Neural Network Theory

The artificial neural network is attractive for ecological studies for its power in analyzing and solving complicated and nonlinear matters. The Self-Organizing Feature Map (SOFM) ordination were described and applied to the analysis of Taxus chinensis var. mairei forests in Shanxi province of China in this paper. The data matrix is the important values of 128 species in 95 quadrats. The results showed that SOFM ordination displayed forest communities in species space which reflected ecological gradients successfully. Its first axis is comprehensive gradient of topographical factors and its second axis is a comprehensive gradient of soil variables. SOFM ordination also distinguished 95 quadrats into eight forest types. SOFM ordination made the interpretation of relationships between communities, species, and environments easier.

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