MEASUREMENT AND PREDICTION OF KARSTIC SPRING FLOW RATES

IF 1.2 4区 环境科学与生态学 Q4 ENVIRONMENTAL SCIENCES
N. Darivianakis, K. Katsifarakis, M. Vafeiadis
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引用次数: 1

Abstract

This paper deals with prediction of the response of karstic springs by means of artificial neural networks (ANNs). A feed-forward back propagation ANN with three layers has been developed, to predict flow rates of two karstic springs, located at Rouvas area, Crete, Greece, using rainfall data as input. While the number of neurons of the input and output layers was determined by choice of data and desired output respectively, the number of neurons of the hidden layer was decided by means of numerous tests. Data used in ANN training and testing include daily and monthly precipitation depths (from September, 2006 to December, 2010) and measured flow rates of the two springs (from April, 2007 to December, 2010). Results show that the trained artificial neural network performed well, although flow rate measurements were not very regular. Moreover, the possibility of estimating the flow rate of one spring, based on measurements of the other has been investigated. Again the ANN gave satisfactory results. All spring flow rate and rainfall measurements are presented as an appendix, to facilitate further scientific research in the area of ANN application to water resources management.
岩溶泉流量的测量与预测
本文研究了用人工神经网络(ann)预测岩溶弹簧响应的方法。本文开发了一种三层前馈反传播人工神经网络,以降雨数据为输入,预测了位于希腊克里特岛Rouvas地区的两个岩溶泉的流量。输入层和输出层的神经元数量分别通过选择数据和期望输出来确定,而隐藏层的神经元数量则通过大量的测试来确定。人工神经网络训练和测试使用的数据包括日降水深度(2006年9月至2010年12月)和月降水深度(2007年4月至2010年12月)以及两个泉的实测流量(2007年4月至2010年12月)。结果表明,尽管流量测量不太规则,但训练后的人工神经网络性能良好。此外,还研究了在测量另一个弹簧的基础上估计一个弹簧流量的可能性。人工神经网络再次给出了令人满意的结果。为了促进人工神经网络在水资源管理中的应用领域的进一步科学研究,将所有的春季流量和降雨量测量结果作为附录。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Global Nest Journal
Global Nest Journal 环境科学-环境科学
CiteScore
1.50
自引率
9.10%
发文量
100
审稿时长
>12 weeks
期刊介绍: Global Network of Environmental Science and Technology Journal (Global NEST Journal) is a scientific source of information for professionals in a wide range of environmental disciplines. The Journal is published both in print and online. Global NEST Journal constitutes an international effort of scientists, technologists, engineers and other interested groups involved in all scientific and technological aspects of the environment, as well, as in application techniques aiming at the development of sustainable solutions. Its main target is to support and assist the dissemination of information regarding the most contemporary methods for improving quality of life through the development and application of technologies and policies friendly to the environment
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