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The Improvement of Projection Pursuit Model and the Application in Evaluating Water Conservancy Projects

机译:投影寻踪模型的改进及其在水利工程评价中的应用

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In order to raise the distinguishment of the model of evaluating water conservancy projects, 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 conservancy projects, the classification results which accord with the fact are gained, which provide the decision proof of water conservancy projects.
机译:为了提高水利工程评价模型的辨识性,提出了一种有效而通用的模型-项目追踪分类模型。密度窗宽度R是解决部分密度的窗道半径,它由样本数据的特征决定,并且主要是通过尝试计算或经验确定的,缺乏理论依据,本文对密度窗进行了改进该模型在理论上具有广度R,推导并获得了经验公式,使模型更加科学,稳定。它采用基于加速遗传算法的实数编码来找到最佳的投影方向,同时,利用最佳的投影方向的数据来研究各个因素对水利工程的影响程度,分类结果符合事实得到了证明,为水利工程的决策提供了依据。

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