A Classification Method of Projection Pursuit Based on Population Migration Algorithm for Fly Ash

Abstract:

In order to solve the problems of one-sidedness of current researches in classification of fly ash, degree of fineness, vitreous body, ignition loss, K₂O, SO₃ and CaO are chosen as the index properties to analyze projection pursuit classification method after analyzing chemical constituents and physical properties that influence the quality of fly ash. Targeting on the activity characteristics, the thesis establishes a projection pursuit cluster analysis model and makes a program on the basis of MATLAB. Population migration algorithm is adopted to seek an optimal projection direction. Fly ash is classified in accordance with property index value of the projection. Researches have proved that the model overcomes the shortcomings of traditional classification methods and reflects the quality and performance of fly ash in a comprehensive way. The evaluation is simple with accurate results and provides a scientific basis for the comprehensive utilization of fly ash.

• Periodical: Advanced Materials Research (Volumes 1010-1012)
• Pages: 900-905
• DOI: https://doi.org/10.4028/www.scientific.net/AMR.1010-1012.900
• Online since: August 2014
• Authors: Lin Xu, Chong Fang
• Keywords: Cluster Analysis, Concrete, Fly Ash (FA), Population Migration Algorithm, Projection Pursuit Regression

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