Design and Elucidation of Integrated Forecasting Model for Information Factor Analysis

정보인자분석(情報因子分析)을 위한 통합예측(統合豫測)모델의 설계(設計) 및 해석(解析)

Over the past two decades, forecasting has gained widespread acceptance as an integral part of business planning and decision making. Accurate forecasting is a prerequisite to successful planning. Accordingly, recent advances in forecasting techniques are of exceptional value to corporate planners. But most of forecasting mothods are reveal its limit and problem for precision and reliability duing to each relationship for raw data and possibility of explanation for each variable. Therefore, to construct the Integrated Forecasting Model(IFM) for Information Factor Analysis, it shoud be considered that whether law data has time lag and variables are explained. For this. following several method can be used : Least Square Method, Markov Process, Fibonacci series, Auto-Correlation, Cross-Correlation, Serial Correlation and Random Walk Theory. Thus, the unified property of these several functions scales the safety and growth of the system which may be varied time-to-time.