- 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}",
