Weighted operation structures to program strengths of concrete-typed specimens using genetic algorithm
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- @Article{Tsai2011161,
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author = "Hsing-Chih Tsai",
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title = "Weighted operation structures to program strengths of
concrete-typed specimens using genetic algorithm",
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journal = "Expert Systems with Applications",
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volume = "38",
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number = "1",
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pages = "161--168",
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year = "2011",
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ISSN = "0957-4174",
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DOI = "doi:10.1016/j.eswa.2010.06.034",
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URL = "http://www.sciencedirect.com/science/article/pii/S0957417410005385",
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keywords = "genetic algorithms, genetic programming, Weighted
formula, Prediction, Concrete strength",
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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 formulae. Such a
formula is composed of a certain quantity of optimised
functions and weights. To determine function selections
and proper weights, genetic algorithm is employed for
optimisation. 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.",
- }
Genetic Programming entries for
Hsing-Chih Tsai
Citations