文档介绍：Improved Grey Model Base on Exponential
Smoothing for River Water Pollution Prediction

XIE Zheng-wen1,2 SU Kai-yu
1. Safety and Environment Institute, China Jiliang University Information center, China Jiliang University
Hangzhou, China Hangzhou, China
2. School of Resources and Safety Engineering,Central South
University Changsha, China

Abstract-The aim of this project is to develop a river water pollution forecasting model to forecast the major pollutant of
pollution predictor. We present an improved Grey-based water quality of Yangtze River in Nanjing extension.
prediction algorithm to forecast the trend of the river water
pollution. We adopted grey prediction as a forecasting means II. General exponential smoothing model
because of its fast calculation with as few as four data inputs Exponential smoothing is usually based on the premise
needed. However, our preliminary study shows that the general
that the level of time series should fluctuate about a constant
Grey model, GM (1, 1) is inadequate to handle a volatile system. [8-9]
The general GM (1, 1) prediction generates the dilemmas of level or change slowly over time . Under such a premise,
dissipation and overshoots. In this study, the prediction is the water pollution time series yt()can be described by
improved significantly by applying the exponential smoothing yt()=+β() t