The Research And Application Of The Information Fusion Algorithm

Multi-source information systems provide a purposeful description of the environment that single source information can't offer Fusing several sources information increases the capability of intelligent system and yields more meaningful information, which is hard to be acquired by a single information source. Multi-source information fusion is a cross-science concerned with information science, computer science and automation science.Multi-source information systems increases the capability of intelligent system and reduces the risks of the decision-making. The situation of information fusion is introduced at the beginning of this paper at first, then the exiting fusion problems based on many references are analysed and future of information fusion is predicted.1.A methods of fusing uncertain information based on fuzzy integral is proposed, an intelligent system is given, which can solve the FEI-DEO and DEI-DEO fusion problems. The problem of model identification for automatic highway operation is also effectively and quickly by applying the intelligent fusion system to combine several feature information. It enhances the capability of handling uncertain information.2.Rough Set (RS) theory has very strong qualitative analysis ability; it doesn't need any preliminary or additional information beyond the data set. It is a new promising tool for dealing with imprecise, incomplete and uncertain data. This paper mainly makes research on attribute reduction algorithms of information systems and its application based on RS theory, and provides two new algorithms.3. Dynamic clustering makes sure the mode of the economic movement. A according to the background of the macroeconomic. The macroeconomic alarming model is established with statistical analysis, at first, the economic situations of economic systems in different periods have been classified into five economic models by statistical analysis, then we have established the boundary cognition functions for each economic model, which provides the direct quantitative limit for the economic alarming.The contributions of this paper :1.The problem of model identification for automatic highway operation is also effectively and quickly by applying the intelligent fusion system to combine several feature information. It enhances the capability of handling uncertain information.2. This essay applies rough sets theory into the alarm of blight in the process of cultivation of vegetables. This bears great significance to the spread of planting knowledge, the production of green vegetables, high yield and bumper harvest, and stabilizing the market.3. The macroeconomic alarming model is established with statistical analysis, which provides the direct quantitative limit for the economic alarming.