Grey Model for Stream Flow Prediction
Grey Model for Stream Flow Prediction
复制标题
水流预测的灰色模型
DOI：
10.13170/aijst.1.1.9
复制
发表时间：
2012
影响因子：
--
通讯作者：
P. Syamala
中科院分区：
文献类型：
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作者：
B. Vishnu;P. Syamala
摘要：水资源、灌溉和供水系统的设计、运行和规划都需要估算水流。需要灰色系统或随机方法来处理中长期水流预测的水文复杂性。采用随机方法进行预测，一般需要较长周期的水流记录数据序列。在印度这样的发展中国家，能否获得长期水文记录是个问题。灰色系统理论适用于内部关系不明确、机制不确定、信息不充分、只需要小样本进行参数估计的情况。对印度喀拉拉邦巴拉塔普扎河流域的河流流量记录进行了灰色分析。采用最小二乘法估计模型参数。所建模型的统计指标表明，所建模型能够以合理的精度预测所研究河流的流量。
Abstract – Design, operation and planning of water resources, irrigation and water supply systems require estimation of stream flow. A grey system or stochastic approach is required for dealing with the hydrological complexities of mid and long-term stream flow prediction. Generally relatively long period data series of stream flow records is required for the prediction using stochastic methods. In developing countries like India, availability of long period hydrological records is a problem. Grey system theory is applicable in the case of unclear inner relationship, uncertain mechanisms and insufficient information and requires only small samples for parameter estimation. Stream flow records of Bharathapuzha river basin, Kerala, India is subjected to grey analysis. Model parameters were estimated using leastsquares method. Statistical indices for the developed models indicate their ability to predict stream flow in the river under study with reasonable accuracy.