Research Of Some Forecasting Methods And Models

Forecasting is the premise of decision and any successful decision can not be separated from the scientific forecasting. There are various forecasting objects and methods, but different methods are suitable to different objects. Therefore the study of forecasting itself is one of important contents in forecasting research. Because of the limitation and inferior precision of the traditional method, pursuing higher precision and broader range of application has become the goal of the modern forecasting technology, especially in the domain we did not carry on forecasting in the past.With the new theories and techniques of the BP neural network, gray systematic theory and the SVM applying to forecasting domain, forecasting technology has greatly developed. After the thoroughly study of the BP neural network, gray systematic theory and SVM, aiming at their insufficiencies, new methods are raised and new forecasting model is created.This paper is divided into nine chapters. Chapter 1,2 and 4 present basic theories and methods. Chapter 3,5,6 and 7 research new forecasting model. In Chapter 8, multi-hierarchical synthetic evaluation model is given and researched. Each chapter has a brief introduction. Chapter 9 uses the factor analysis to analyse and compare the population quality in the western area of China.Chapter 1 introduces forecasting technology which is in common use and current research status in domestic and abroad. This chapter also gives the profile of the whole paper. Chapter 2 introduces the basic model, operation principles and the study course of the manual neural network, emphasizing on the current status and problems in research of BP neural network. In chapter 3 based on neural network toolbox offered by MATLAB, a judging model of three-layered BP neural network is designed, hence a new method of judging and analysis is raised, and a contrast with the traditional Fisher's judging method. Chapter 4 introduces the fundamental theories of the gray system. In...