Assessment of Pipe Deterioration in Water Distribution Network of Incheon City Using Principal Component Analysis and Artificial Neural Network

Water Distribution ◽

Distribution Network ◽

Principal Component ◽

Water Distribution Network ◽

Component Analysis ◽

Estimation of Leakage Ratio Using Principal Component Analysis and Artificial Neural Network in Water Distribution Systems

Sustainability ◽

10.3390/su10030750 ◽

2018 ◽

Vol 10 (3) ◽

pp. 750 ◽

Cited By ~ 11

Author(s):

◽

Keyword(s):

Neural Network ◽

Distribution Systems ◽

Water Distribution ◽

Water Distribution Systems ◽

Principal Component ◽

Component Analysis ◽

Principal component analysis, hidden Markov model , and artificial neural network inspired techniques to recognize faces

Concurrency and Computation Practice and Experience ◽

10.1002/cpe.6157 ◽

2020 ◽

Author(s):

Akarsh Aggarwal ◽

Mohammed Alshehri ◽

Manoj Kumar ◽

Purushottam Sharma ◽

Osama Alfarraj ◽

...

Keyword(s):

Neural Network ◽

Markov Model ◽

Hidden Markov Model ◽

Hidden Markov ◽

Principal Component ◽

Component Analysis ◽

A Biomedical System Based on Artificial Neural Network and Principal Component Analysis for Diagnosis of the Heart Valve Diseases

Journal of Medical Systems ◽

10.1007/s10916-010-9446-7 ◽

2010 ◽

Vol 36 (1) ◽

pp. 61-72 ◽

Cited By ~ 47

Author(s):

Harun Uğuz

Keyword(s):

Neural Network ◽

Heart Valve ◽

Principal Component ◽

Component Analysis ◽

Heart Valve Diseases ◽

Artificial Neural ◽

Biomedical System ◽

Valve Diseases

Modeling greenhouse air humidity by means of artificial neural network and principal component analysis

Computers and Electronics in Agriculture ◽

10.1016/j.compag.2009.07.011 ◽

2010 ◽

Vol 71 ◽

pp. S19-S23 ◽

Cited By ~ 56

Author(s):

Fen He ◽

Chengwei Ma

Keyword(s):

Neural Network ◽

Principal Component ◽

Component Analysis ◽

Air Humidity ◽

Electroencephalograph based Human Emotion Recognition Using Artificial Neural Network and Principal Component Analysis

IETE Journal of Research ◽

10.1080/03772063.2021.1965044 ◽

2021 ◽

pp. 1-10

Author(s):

Satyanarayana Naga V. Kanuboyina ◽

Shankar T ◽

Rama Raju Venkata Penmetsa

Keyword(s):

Neural Network ◽

Emotion Recognition ◽

Principal Component ◽

Component Analysis ◽

Human Emotion ◽

Investigation of correlation between chemical composition and properties of biodiesel using principal component analysis (PCA) and artificial neural network (ANN)

Renewable Energy ◽

10.1016/j.renene.2020.12.078 ◽

2021 ◽

Vol 168 ◽

pp. 632-646

Author(s):

M.I. Jahirul ◽

M.G. Rasul ◽

R.J. Brown ◽

W. Senadeera ◽

M.A. Hosen ◽

...

Keyword(s):

Neural Network ◽

Chemical Composition ◽

Principal Component ◽

Component Analysis ◽

Artificial Neural ◽

Artificial Neural Network Ann

A novel framework of multivariate modeling of water distribution network through 33 factorial design and artificial neural network

Journal of Environmental Science and Health Part A ◽

10.1080/10934529.2019.1571308 ◽

2019 ◽

Vol 54 (6) ◽

pp. 551-562

Author(s):

Partha S. Ghosal ◽

Ashwini Javaregowda ◽

Ashok K. Gupta ◽

Dineshwar P. Singh

Keyword(s):

Neural Network ◽

Factorial Design ◽

Water Distribution ◽

Distribution Network ◽

Water Distribution Network ◽

Multivariate Modeling ◽

Development of pistachio sorting system using principal component analysis (PCA) assisted artificial neural network (ANN) of impact acoustics

Expert Systems with Applications ◽

10.1016/j.eswa.2010.04.008 ◽

2010 ◽

Vol 37 (10) ◽

pp. 7205-7212 ◽

Cited By ~ 35

Author(s):

Mahmoud Omid ◽

Asghar Mahmoudi ◽

Mohammad H. Omid

Keyword(s):

Neural Network ◽

Principal Component ◽

Component Analysis ◽

Artificial Neural ◽

Artificial Neural Network Ann ◽

Sorting System

Enhanced Artificial Neural Network Models Using Principal Component Analysis for Plants multiclass classification

2018 Tenth International Conference on Advanced Computing (ICoAC) ◽

10.1109/icoac44903.2018.8939105 ◽

2018 ◽

Author(s):

M. Sornam ◽

V. Vanitha

Keyword(s):

Neural Network ◽

Network Models ◽

Principal Component ◽

Component Analysis ◽

Multiclass Classification ◽

Neural Network Models ◽

Artificial Neural ◽

Artificial Neural Network Models

Modeling the Correlation of Composition-Processing-Property for TC11 Titanium Alloy Based on Principal Component Analysis and Artificial Neural Network

Journal of Materials Engineering and Performance ◽

10.1007/s11665-012-0162-y ◽

2012 ◽

Vol 21 (11) ◽

pp. 2231-2237 ◽

Cited By ~ 2

Author(s):

Yu Sun ◽

Weidong Zeng ◽

Yongqing Zhao ◽

Yitao Shao ◽

Yigang Zhou

Keyword(s):

Neural Network ◽

Titanium Alloy ◽

Principal Component ◽

Component Analysis ◽

Processing Property ◽

Artificial Neural ◽

Tc11 Titanium Alloy