prediction of cement strength using soft computing techniques
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prediction of cement strength using soft computing techniques.

Prediction of cement strength using soft computing ...

01/11/2004  Therefore, the use of soft computing techniques seems a promising approach to the CCS prediction problem. In this study, such an attempt is made by employing gene expression programming (GEP) and neural networks (NNs) for the prediction of the compressive strength of Portland composite cement (PCC). In addition to these techniques, stepwise regression analysis is also used to have an

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PREDICTION OF CEMENT STRENGTH USING SOFT

The authors also use stepwise regression analysis to understand the predictive power of the soft computing techniques in comparison to classical statistical approach. The application of the genetic programming (GP) technique GEP to the cement strength prediction is shown for the first time in this paper. The data show that soft computing techniques give far better results than the regression ...

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Prediction of cement strength using soft computing techniques

Gene expression programming (GEP) and neural networks (NNs) are the soft computing techniques that are used for the prediction of compressive cement strength (CCS). In addition to these methods, stepwise regression analysis is also used to have an idea about the predictive power of the soft computing techniques in comparison to classical statistical approach. The application of the genetic ...

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(PDF) Prediction of cement strength using soft computing ...

Cement and Concrete Research 34 (2004) 2083 – 2090 Prediction of cement strength using soft computing techniques Adil Baykasog˘lu*, Tu¨rkay Dereli, Serkan Tanısß Department of Industrial Engineering, University of Gaziantep, 27310 Gaziantep, Turkey Received 26 August 2003; accepted 9 March 2004 Abstract In this paper, it is aimed to propose prediction approaches for the 28-day ...

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Prediction of cement strength using soft computing ...

In this paper, it is aimed to propose prediction approaches for the 28-day compressive strength of Portland composite cement (PCC) by using soft computing techniques.

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Prediction of cement strength using soft computing ...

In this paper, it is aimed to propose prediction approaches for the 28-day compressive strength of Portland composite cement (PCC) by using soft computing techniques. Gene expression programming (GEP) and neural networks (NNs) are the soft computing techniques that are used for the prediction of compressive cement strength (CCS). In addition to these methods, stepwise

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Prediction of cement strength using soft computing ...

Gene expression programming (GEP) and neural networks (NNs) are the soft computing techniques that are used for the prediction of compressive cement strength (CCS). In addition to these methods, stepwise regression analysis is also used to have an idea about the predictive power of the soft computing techniques in comparison to classical statistical approach. The application of the genetic ...

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Soft computing techniques for the prediction of concrete ...

Prediction of concrete compressive strength using six widely used soft computing models. • The generated GP expressions can be utilized to estimate concrete compressive strength directly. • Determination of best performing model using a20-index. • Comparative assessment of

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Prediction of cement-based mortars compressive strength ...

23/04/2021  After a preliminary investigation of the available AI and soft computing (SC) techniques, SVM, RF, DT, KNN and AdaBoost were used to estimate the compressive strength of cement-based mortars. Each of these techniques has its own effective parameters and their optimal values needs to be determined. The results show that the highest prediction accuracy was obtained from the AdaBoost

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Prediction of cement strength using soft computing ...

23/07/2021  Prediction of cement strength using soft computing techniques,[*][*][*][*][*]相关检索词相关专家相关机构[*] Mechanical Engineering Department, Izmir Institute of Technology, 35437 Izmir, Turkey[*] Aerospace Engineering, The University of Sheffield, Mappin Street, Sheffield, S1 3JD, UK[*] Mechanical Engineering Department, Izmir Institute of Technology, 35430 Izmir, Turkey ...

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Prediction of cement strength using soft computing techniques

Gene expression programming (GEP) and neural networks (NNs) are the soft computing techniques that are used for the prediction of compressive cement strength (CCS). In addition to these methods, stepwise regression analysis is also used to have an idea about the predictive power of the soft computing techniques in comparison to classical statistical approach. The application of the genetic ...

Get Price

Prediction of cement strength using soft computing ...

In this paper, it is aimed to propose prediction approaches for the 28-day compressive strength of Portland composite cement (PCC) by using soft computing techniques. Gene expression programming (GEP) and neural networks (NNs) are the soft computing techniques that are used for the prediction of compressive cement strength (CCS). In addition to these methods, stepwise

Get Price

Prediction of cement strength using soft computing ...

Gene expression programming (GEP) and neural networks (NNs) are the soft computing techniques that are used for the prediction of compressive cement strength (CCS). In addition to these methods, stepwise regression analysis is also used to have an idea about the predictive power of the soft computing techniques in comparison to classical statistical approach. The application of the genetic ...

Get Price

Prediction of cement strength using soft computing techniques

In this paper, it is aimed to propose prediction approaches for the 28-day compressive strength of Portland composite cement (PCC) by using soft computing techniques. Gene expression programming (GEP) and neural networks (NNs) are the soft computing techniques that are used for the prediction of compressive cement strength (CCS). In addition to these methods, stepwise

Get Price

Prediction of cement-based mortars compressive strength ...

23/04/2021  After a preliminary investigation of the available AI and soft computing (SC) techniques, SVM, RF, DT, KNN and AdaBoost were used to estimate the compressive strength of cement-based mortars. Each of these techniques has its own effective parameters and their optimal values needs to be determined. The results show that the highest prediction accuracy was obtained from the AdaBoost

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Mostafa Jalal* Soft computing techniques for compressive ...

Soft computing techniques for compressive strength prediction of concrete cylinders strengthened by CFRP composites Abstract: This study presents the application of soft com-puting techniques ...

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Predicting concrete compressive strength using hybrid ...

01/07/2021  The use of AB in concrete mixes makes estimation of concrete CS more complex and hence, more advanced computations techniques are required to develop predictive equations [, , , , , , , , , , , , ]. In materials science, for the prediction of the CS and modulus of elasticity of concrete many researchers adopt soft computing techniques such as Artificial Neural Networks (ANNs). Detailed

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Soft computing-based techniques for concrete beams shear ...

01/01/2019  In addition, the use of soft computing techniques has been highlighted in many studies in field of civil engineering (Armaghani et al 2014, 2017, Abad et al 2018, Koopialipoor et al 2018, Pham et al 2017a,b,cd, and Pham et al 2018a,b). Moreover, in the last decades, artificial neural networks have been proposed to estimate the shear strength of reinforced concrete structural elements (Sanad ...

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Prediction of cement strength using soft computing ...

23/07/2021  Prediction of cement strength using soft computing techniques,[*][*][*][*][*]相关检索词相关专家相关机构[*] Mechanical Engineering Department, Izmir Institute of Technology, 35437 Izmir, Turkey[*] Aerospace Engineering, The University of Sheffield, Mappin Street, Sheffield, S1 3JD, UK[*] Mechanical Engineering Department, Izmir Institute of Technology, 35430 Izmir, Turkey ...

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[PDF] Prediction of compressive and tensile strength of ...

Accurate determination of compressive and tensile strength of limestone is an important subject for the design of geotechnical structures. Although there are several classical approaches in the literature for strength prediction their predictive accuracy is generally not satisfactory. The trend in the literature is to apply artificial intelligence based soft computing techniques for complex ...

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Prediction of cement strength using soft computing ...

In this paper, it is aimed to propose prediction approaches for the 28-day compressive strength of Portland composite cement (PCC) by using soft computing techniques. Gene expression programming (GEP) and neural networks (NNs) are the soft computing techniques that are used for the prediction of compressive cement strength (CCS). In addition to these methods, stepwise

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Mostafa Jalal* Soft computing techniques for compressive ...

Soft computing techniques for compressive strength prediction of concrete cylinders strengthened by CFRP composites Abstract: This study presents the application of soft com-puting techniques ...

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Efficient soft computing techniques for the prediction of ...

Efficient soft computing techniques for the prediction of compressive strength of geopolymer concrete Rahul Biswas, Abidhan Bardhan, Pijush Samui, Baboo Rai, Subrata Nayak and Danial Jahed Armaghani : Abstract In the recent year, extensive researches have been done on fly ash-based geopolymer concrete for its similar properties like Portland cement as well as its environmental

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Prediction of cement strength using soft computing ...

23/07/2021  Prediction of cement strength using soft computing techniques,[*][*][*][*][*]相关检索词相关专家相关机构[*] Mechanical Engineering Department, Izmir Institute of Technology, 35437 Izmir, Turkey[*] Aerospace Engineering, The University of Sheffield, Mappin Street, Sheffield, S1 3JD, UK[*] Mechanical Engineering Department, Izmir Institute of Technology, 35430 Izmir, Turkey ...

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Predicting Cement Compressive Strength Using Double-Layer ...

This paper presents a novel algorithm named Double-layer Multi-expression Programming (DMEP). Then DMEP model is applied to the prediction of 28-day Portland cement compressive strength. We compare DMEP model with other four soft computing models, namely Multi-Expression Programming model (MEP), Gene Expression Programming model (GEP), Neural Networks model (NN) and Fuzzy

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Prediction of Compressive Strength of Self-Compacting ...

compressive strength prediction with very acceptable results and a high ... is soft computing techniques developed to mimic the neural system of human being in learning from training patterns or ...

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An Intelligent Model for the Prediction of Bond Strength ...

An Intelligent Model for the Prediction of Bond Strength of FRP Bars in Concrete: A Soft Computing Approach Hamed Bolandi 1, Wolfgang Banzhaf 2, Nizar Lajnef 1, Kaveh Barri 3 and Amir H. Alavi 3 ...

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Compressive strength of natural hydraulic lime mortars ...

01/01/2019  The use of soft computing techniques for the prediction of the compressive strength has already been the center of research for cement mortars, as can be seen in Akkurt et al 2003 and Eskandari-Naddaf and Kazemi 2017, among others, blended cement mortars, as illustrated by Saridemir 2009 and Topcu et al 2008 and concrete materials, as studied by Ozcan at al 2009, Bilim et al 2009

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[PDF] Prediction of compressive and tensile strength of ...

Accurate determination of compressive and tensile strength of limestone is an important subject for the design of geotechnical structures. Although there are several classical approaches in the literature for strength prediction their predictive accuracy is generally not satisfactory. The trend in the literature is to apply artificial intelligence based soft computing techniques for complex ...

Get Price

CEMENT-STRENGTH-PREDICTION[IEEE]外文电子书籍.pdf

CEMENT-STRENGTH-PREDICTION[IEEE]外文电子书籍.pdf,2012 Fourth International Conference on Computational and Information Sciences Predicting Cement Compressive Strength Using Double-layer Multi-Expression Programming Qingke Zhang1,a, Bo Yang1,b*, Lin Wang1,c, Fuxiang Zhu2,d 1. Shandong Province Key L

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