Title :
The improvement of Projection Pursuit Classification model and the application in evaluating water resources carrying capacity
Author :
Xiaoyong, Zhao ; Guangbai, Cui
Author_Institution :
Coll. of Hydrol. & Water Resources, Hohai Univ., Nanjing, China
Abstract :
In view of the uncertainty of indexes for evaluating water resources carrying capacity, to resolve the incompatibility of the results of evaluating water resources carrying capacity, and to raise the distinguishment of the model of evaluating water resources carrying capacity, an effective and general model-Projection Pursuit Classification model is suggested. The density window breadth R is the window way radius that solves the partial density, it is determined by the characteristic of the sample datum, and it is mainly determined by trying to calculate or experience, which lacks theoretical basis, this article improves the density window breadth R of the model in theory, it deduces and acquires the empirical formula of calculation, making the model more scientific and stable. It adopts Real Coding based on Accelerating Genetic Algorithm to find the best projective direction, at the same time, uses the datum of the best projective direction to research the level of the influence of each factor to water resources carrying capacity, the classification results which accord with the fact are gained, which provide the decision proof of water resources carrying capacity.
Keywords :
genetic algorithms; pattern classification; water resources; accelerating genetic algorithm; projection pursuit classification model; real coding; water resources carrying capacity evaluation; Entropy; Equations; Indexes; Mathematical model; Rivers; Standards; Water resources; Real Coding based on Accelerating Genetic Algorithm; evaluate; projection pursuit; water resources carrying capacity;
Conference_Titel :
Robotics and Applications (ISRA), 2012 IEEE Symposium on
Conference_Location :
Kuala Lumpur
Print_ISBN :
978-1-4673-2205-8
DOI :
10.1109/ISRA.2012.6219295