Building Image Feature Kinetics for Cement Hydration using Gene Expression Programming with Similarity Weight Tournament Selection

Created by W.Langdon from gp-bibliography.bib Revision:1.3949

@Article{Wang:2015:ieeeTEC,
  author =       "Lin Wang and Bo Yang and Shoude Wang and 
                 Zhifeng Liang",
  title =        "Building Image Feature Kinetics for Cement Hydration
                 using Gene Expression Programming with Similarity
                 Weight Tournament Selection",
  journal =      "IEEE Transactions on Evolutionary Computation",
  year =         "2015",
  volume =       "19",
  number =       "5",
  pages =        "679--693",
  month =        oct,
  keywords =     "genetic algorithms, genetic programming, gene
                 expression programming, Evolutionary Computation,
                 Similarity Weight Tournament, Reverse Modeling, Cement
                 Hydration Kinetics, image processing, Portland cement",
  ISSN =         "1089-778X",
  URL =          "http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6948258",
  DOI =          "doi:10.1109/TEVC.2014.2367111",
  size =         "15 pages",
  abstract =     "The physical properties of cement are strongly
                 influenced by the development of microstructure and
                 cement hydration. Therefore, the investigation of
                 microstructure for cement paste enables us to
                 understand the hydration process and to predict the
                 physical properties. However, the unreliability of
                 phase classification and segmentation in image affect
                 the description of microstructure, as well as the
                 prediction of properties and the simulation of
                 hydration. This paper studies the dynamic relationship
                 between microstructure and physical properties from the
                 image itself. The relationship between compressive
                 strength and microstructure image features is built as
                 the form of image feature kinetics using gene
                 expression programming from observed microtomography
                 images. A similarity weight tournament selection is
                 also proposed to increase the diversity of population
                 and improve the performance of gene expression
                 programming. Experimental results manifest that the
                 evolved image feature kinetics not only perform well in
                 fitting training data but also exhibit superior
                 generalisation ability.",
  notes =        "Lin Wang is with Shandong Provincial Key Laboratory of
                 Network Based Intelligent Computing, University of
                 Jinan, Jinan, 250022, China.

                 Also known as \cite{6948258}",
}

Genetic Programming entries for Lin Wang Bo Yang Shoude Wang Zhifeng Liang

Citations