Inventory Demand Forecasting Based On Time Series Analysis, Research And Application Of Computing Systems

How to scientifically make inventory decision is an important problem during enterprises'production management. The best way to solve raw material shortage and surplus is to make accurate and comprehensive inventory plan according to enterprises'various demands. By the implementation of inventory plan, enterprises can improve inventory turnover rate, lower inventory level and reduce idle operation capital on the basis of ensuring the production schedule, so as to improve demand satisfaction rate and profit.To settle problem above, this article is going to take qualitative forecasting method as study objective. On the basis of deep analysis of time serious method and by using historical demand data, it will analyze and determine the characteristics of enterprises'raw material demand, such as seasonal nature, periodicity and tendency. Then it is going to provide and systematize a comprehensive prediction algorithm to help enterprises'to solve a serious of problems brought by highly non-determinacy of raw material demand and make scientific inventory decision.Mainly include:(1) Detailed study of the principle, application conditions and scopes of several common forecasting models(Moving Average, Weighted Moving Average, Simple Exponential Smoothing, Double Exponential Smoothing, Triple Exponential Smoothing, Linear Regression, Multiple Linear Regression)in time serious analysis.(2) Detailed study of the best forecasting method and selective process of above forecasting models.(3) Detailed study of the mathematical formula and calculation method of above forecasting models, including the realization mode in Eclipse JAVA.(4) Study of the specific application mode of the best forecasting model.