scholarly journals An Intelligent Model for the Prediction of Bond Strength of FRP Bars in Concrete: A Soft Computing Approach

Technologies ◽  
2019 ◽  
Vol 7 (2) ◽  
pp. 42 ◽  
Author(s):  
Hamed Bolandi ◽  
Wolfgang Banzhaf ◽  
Nizar Lajnef ◽  
Kaveh Barri ◽  
Amir H. Alavi
Keyword(s):  
Genetic Programming ◽  
Bond Strength ◽  
Soft Computing ◽  
American Concrete Institute ◽  
Test Results ◽  
Experimental Database ◽  
Soft Computing Method ◽  
Intelligent Model ◽  
Computing Method ◽  
Frp Bars

Accurate prediction of bond behavior of fiber reinforcement polymer (FRP) concrete has a pivotal role in the construction industry. This paper presents a soft computing method called multi-gene genetic programming (MGGP) to develop an intelligent prediction model for the bond strength of FRP bars in concrete. The main advantage of the MGGP method over other similar methods is that it can formulate the bond strength by combining the capabilities of both standard genetic programming and classical regression. A number of parameters affecting the bond strength of FRP bars were identified and fed into the MGGP algorithm. The algorithm was trained using an experimental database including 223 test results collected from the literature. The proposed MGGP model accurately predicts the bond strength of FRP bars in concrete. The newly defined predictor variables were found to be efficient in characterizing the bond strength. The derived equation has better performance than the widely-used American Concrete Institute (ACI) model.

scholarly journals Article Commentary: Rough Set Soft Computing Cancer Classification and Network: One Stone, Two Birds

2010 ◽  
Vol 9 ◽  
pp. CIN.S4874 ◽  
Author(s):  
Yue Zhang
Keyword(s):  
Soft Computing ◽  
Gene Regulatory Networks ◽  
Regulatory Networks ◽  
Cancer Classification ◽  
Soft Computing Method ◽  
Direct Gene ◽  
Gene Regulatory ◽  
Variable Precision Rough Sets ◽  
Computing Method ◽  
Selection Of

Gene expression profiling provides tremendous information to help unravel the complexity of cancer. The selection of the most informative genes from huge noise for cancer classification has taken centre stage, along with predicting the function of such identified genes and the construction of direct gene regulatory networks at different system levels with a tuneable parameter. A new study by Wang and Gotoh described a novel Variable Precision Rough Sets-rooted robust soft computing method to successfully address these problems and has yielded some new insights. The significance of this progress and its perspectives will be discussed in this article.

scholarly journals A soft computing method for detecting lifetime building thermal insulation failures

2010 ◽  
Vol 17 (2) ◽  
pp. 103-115 ◽  
Author(s):  
Javier Sedano ◽  
Leticia Curiel ◽  
Emilio Corchado ◽  
Enrique de la Cal ◽  
José R. Villar
Keyword(s):  
Soft Computing ◽  
Thermal Insulation ◽  
Soft Computing Method ◽  
Computing Method

A novel soft computing method for engine RUL prediction

2017 ◽  
Vol 78 (4) ◽  
pp. 4065-4087 ◽  
Author(s):  
Sandip Kumar Singh ◽  
Sandeep Kumar ◽  
J. P. Dwivedi
Keyword(s):  
Soft Computing ◽  
Soft Computing Method ◽  
Computing Method
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