Comparison of artificial neural network and coupled simulated annealing based least square support vector regression models for prediction of compressive strength of high-performance concrete

Compressive Strength ◽

Simulated Annealing ◽

Regression Models ◽

High Performance ◽

Least Square ◽

Support Vector ◽

Coupled Simulated Annealing

Incorporation of artificial neural network with principal component analysis and cross-validation technique to predict high-performance concrete compressive strength

Asian Journal of Civil Engineering ◽

10.1007/s42107-021-00362-3 ◽

2021 ◽

Author(s):

Mohammed Majeed Hameed ◽

Mohamed Khalid AlOmar ◽

Wajdi Jaber Baniya ◽

Mohammed Abdulhakim AlSaadi

Keyword(s):

Neural Network ◽

Principal Component Analysis ◽

Compressive Strength ◽

High Performance ◽

Cross Validation ◽

Principal Component ◽

Concrete Compressive Strength ◽

Validation Technique

Prediction of the intermediate block displacement of the dam crest using artificial neural network and support vector regression models

Soft Computing ◽

10.1007/s00500-018-3528-8 ◽

2018 ◽

Vol 23 (19) ◽

pp. 9629-9645 ◽

Cited By ~ 9

Author(s):

Mahmoud Mohammad Rezapour Tabari ◽

Hamed Reza Zarif Sanayei

Keyword(s):

Neural Network ◽

Support Vector Regression ◽

Regression Models ◽

Support Vector ◽

Artificial Neural Network Model for Strength Prediction of Ultra-High-Performance Concrete

ACI Materials Journal ◽

10.14359/51732710 ◽

2021 ◽

Vol 118 (4) ◽

Author(s):

Joaquín Abellán-García

Keyword(s):

Neural Network ◽

Network Model ◽

Neural Network Model ◽

Artificial Neural Network Model ◽

High Performance ◽

Strength Prediction ◽

Ultra High Performance Concrete ◽

Monthly river flow forecasting using artificial neural network and support vector regression models coupled with wavelet transform

Computers & Geosciences ◽

10.1016/j.cageo.2012.11.015 ◽

2013 ◽

Vol 54 ◽

pp. 1-8 ◽

Cited By ~ 103

Author(s):

Aman Mohammad Kalteh

Keyword(s):

Neural Network ◽

Wavelet Transform ◽

Support Vector Regression ◽

Regression Models ◽

River Flow ◽

Support Vector ◽

River Flow Forecasting ◽

Predicting Compressive Strength of High-Performance Concrete Using Metaheuristic-Optimized Least Squares Support Vector Regression

Journal of Computing in Civil Engineering ◽

10.1061/(asce)cp.1943-5487.0000506 ◽

2016 ◽

Vol 30 (3) ◽

pp. 06015002 ◽

Cited By ~ 33

Author(s):

Anh-Duc Pham ◽

Nhat-Duc Hoang ◽

Quang-Trung Nguyen

Keyword(s):

Compressive Strength ◽

Least Squares ◽

Support Vector Regression ◽

High Performance ◽

Support Vector

Comparison of Partial Least Square, Artificial Neural Network and Support Vector Regressions for real time monitoring of CHO cell culture processes using in situ Near Infrared spectroscopy

Biotechnology and Bioengineering ◽

10.1002/bit.27997 ◽

2021 ◽

Author(s):

Daniel Arturo Zavala‐Ortiz ◽

Aurélia Denner ◽

Maria Guadalupe Aguilar‐Uscanga ◽

Annie Marc ◽

Bruno Ebel ◽

...

Keyword(s):

Neural Network ◽

Cell Culture ◽

Infrared Spectroscopy ◽

Near Infrared ◽

Partial Least Square ◽

Least Square ◽

Support Vector ◽

Cho Cell

Proceedings of the 5th ACM COMPUTE Conference on Intelligent & scalable system technologies - COMPUTE '12 ◽

A robust neural network classifier to model the compressive strength of high performance concrete using feature subset selection

10.1145/2459118.2459119 ◽

2012 ◽

Author(s):

M. Venu ◽

R. Uday Kiran ◽

R. Kiranmai

Keyword(s):

Neural Network ◽

Compressive Strength ◽

High Performance ◽

Subset Selection ◽

Feature Subset Selection ◽

Feature Subset ◽

Neural Network Classifier

Artificial Neural Network for Predicting Creep and Shrinkage of High Performance Concrete

Journal of Advanced Concrete Technology ◽

10.3151/jact.6.135 ◽

2008 ◽

Vol 6 (1) ◽

pp. 135-142 ◽

Cited By ~ 7

Author(s):

Jayakumar Karthikeyan ◽

Akhil Upadhyay ◽

Navaratan M. Bhandari

Keyword(s):

Neural Network ◽

High Performance ◽

Artificial Neural ◽

Creep And Shrinkage

Development of multilayer perceptron artificial neural network (MLP-ANN) and least square support vector machine (LSSVM) models to predict Nusselt number and pressure drop of TiO2/water nanofluid flows through non-straight pathways

Numerical Heat Transfer Part A Applications ◽

10.1080/10407782.2018.1523597 ◽

2018 ◽

Vol 74 (4) ◽

pp. 1190-1206 ◽

Cited By ~ 27

Author(s):

Mostafa Kahani ◽

Mohammad Hossein Ahmadi ◽

Afshin Tatar ◽

Milad Sadeghzadeh

Keyword(s):

Neural Network ◽

Support Vector Machine ◽

Nusselt Number ◽

Pressure Drop ◽

Multilayer Perceptron ◽

Least Square ◽

Support Vector ◽

High-performance Concrete Compressive Strength Prediction using Time-Weighted Evolutionary Fuzzy Support Vector Machines Inference Model

Automation in Construction ◽

10.1016/j.autcon.2012.07.004 ◽

2012 ◽

Vol 28 ◽

pp. 106-115 ◽

Cited By ~ 42

Author(s):

Min-Yuan Cheng ◽

Jui-Sheng Chou ◽

Andreas F.V. Roy ◽

Yu-Wei Wu

Keyword(s):

Compressive Strength ◽

Support Vector Machines ◽

High Performance ◽

Strength Prediction ◽

Support Vector ◽

Concrete Compressive Strength ◽

Inference Model ◽

Vector Machines ◽

Fuzzy Support Vector Machines