Paper Info
Title
Weighted operation structures to program strengths of concrete-typed specimens using genetic algorithm
Abstract
This study introduces weighted operation structures (WOS) to program engineering problems, in which each WOS adopts a fixed binary tree topology. The first WOS layer serves as the parameter input entrance. The target is produced at the eventual layer using both values and a mathematical formula. Each WOS element is operated by two front nodal inputs, an undetermined function, and two undetermined weights to produce one nodal output. This study proposes the novel concept of introducing weights into a WOS. Doing so provides two unique advantages: (1) achieving a balance between the influences of two front inputs and (2) incorporating weights throughout the generated formulas. Such a formula is composed of a certain quantity of optimized functions and weights. To determine function selections and proper weights, genetic algorithm is employed for optimization. Case studies herein focused on three kinds of concrete-typed specimen strengths: (1) concrete compressive strength, (2) deep beam shear strength, and (3) squat wall shear strength. Results showed that the proposed WOS can provide accurate results that nearly equal the results obtainable using the familiar neural network. The weighted formula, however, offers a distinct advantage in that it can be programmed for practical cases.
Year
DOI
Venue
2011
10.1016/j.eswa.2010.06.034
Expert Syst. Appl.
Keywords
Field
DocType
prediction,proposed wos,concrete compressive strength,genetic programming,concrete-typed specimen strength,genetic algorithm,wos element,weighted operation structure,concrete strength,deep beam shear strength,case study,weighted formula,wos layer,mathematical formula,squat wall shear strength,program strength,shear strength,neural network,compressive strength,binary tree
Shear strength,Compressive strength,Algorithm,Binary tree,Genetic programming,Beam (structure),Artificial neural network,Mathematics,Genetic algorithm,Mathematical formula
Journal
Volume
Issue
ISSN
38
1
Expert Systems With Applications
Citations 
PageRank 
References 
6
0.76
5
Authors
1
Name
Order
Citations
PageRank
Hsing-Chih Tsai119114.26