基于马尔柯夫模型的黄河三门峡河段水质预测

Prediction of Water Quality in Sanmenxia Reach Based on Markov Model

水质变化趋势预测是维护和管理当前水质状况的重要依据,影响水质的因素有物理、化学、水力学、生物学、气象学以及人类活动等多方面的因素,在时间和空间上存在相当多的影响变量,现有的基于数学表达式水质预测模型很难将这些因素都考虑进去,而且预测的是一个具体的数值.利用马尔柯夫链预测水质所处状态概率,实质上是预测水质指标带有一定置信水平的置信区间,在可以完全满足实际需要的前提下,扩大了预测的范围,相对的提高了预测的精度.文章介绍了马尔柯夫模型的基本原理,并且应用到黄河三门峡河段的水质预测中,总体效果基本满意.

Changes in trends in water quality forecast is to protect and manage the current water situation in the important basis for the impact on water quality factors physics, chemistry, hydraulics, biology, meteorology and human activity, and other factors. In time and space there are a considerable number of variables, based on the existing mathematical expression model for predicting water quality is difficult to consider all these factors into account, and a forecast of a specific numerical value. Markov chain forecast probability of the state of water quality, prediction is essentially water quality indicators have some level of confidence interval, can fully satisfy the actual needs of the premise, the forecast expansion of the scope and relative to improve the prediction accuracy. This paper introduces the Markov model to the basic principles and applied to the section of water enters forecast, basically satisfied with the overall results.