| 董艳慧,周维博,赵平歌.基于W-F定律和PNN模型的西安市潜水脆弱性评价[J].干旱地区农业研究,2013,31(2):209~213 |
| 基于W-F定律和PNN模型的西安市潜水脆弱性评价 |
| Unconfined water vulnerability evaluation based on Weber-Fechner law and Probabilistic Neural Network |
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| DOI：10.7606/j.issn.1000-7601.2013.02.38 |
| 中文关键词: W-F拓广定律 概率神经网络 潜水 水质 水量 地下水脆弱性评价 |
| 英文关键词:Weber-Fechner expand law Probabilistic Neural Network unconfined water water quality water quantity groundwater vulnerability evaluation |
| 基金项目:西安工业大学校长科研基金（XAGDXJJ1123）；西安市水务局资助项目 |
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| 中文摘要: |
| 鉴于现有的地下水脆弱性评价方法存在主观性大和不能评价水量脆弱性等问题，将心理物理学中的韦伯费希纳（W-F）定律拓广，并与概率神经网络法（PNN）相结合，提出了一种可
以评价水量和水质脆弱性的方法——基于W F拓广定律的概率神经网络法。利用该方法评价了2005年西安市潜水水质及水量的脆弱性，结果表明基于W-F拓广定律的概率神经网络法能避免传统方法的主观性和局限性，评价结果合理、可靠，评价范围更广，可推广应用。 |
| 英文摘要: |
| As the present groundwater vulnerability evaluation methods were more subjective, and could not evaluate the vulnerability of water quantity, this paper combined the Weber-Fechner expand law(a psychophysics’ principle) and Probabilistic Neural Network to put forward a new groundwater vulnerability evaluation method—W-F and PNN method, which could evaluate the quality and quantity vulnerability of groundwater. The new method was used to evaluate the unconfined water quality and quantity vulnerability of Xi’an for the year 2005. The result shows that the W-F and PNN method can avoid the influenc
e of subjection and limitation of traditional methods, the evaluation result was reasonable and reliable, and the method has wider evaluation scope and was valuable to be widely used. |
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