Study for Forecasting China’s Shipping Volume of Iron Ore Based on Adaptive Filtering Algorithm

Abstract

In order to effectively analysis of shipping economy and forecast the impact of refining steel on air pollution trends in China, this article's objective was to introduce an adaptive filtering algorithm, it is constructed by using MATLAB simulation model to forecast shipping volume of iron ore in the future, which includes experimental simulation process, technical principle and theoretical model. Results indicate that through the model is set by the small error, select the four weights, and then through the iterative operation to obtain the best weight; through the previous group of data as a weight to build, the last set of data as a weight verification. This article's conclusions indicate that the weights are obtained using the iterative algorithm, the percentage of error is only 0.0149, it illustrates the model can effectively predict the shipping volume of iron ore in subsequent years, a simple forecasting model of shipping volume of iron ore is constructed in the future. And further analysis of the precise optimization of the follow-up model.