Gm Food Safety Assessment Basing On Information Fusion

Since the advent of genetically modified food(GM food), global consumption of about200 million people eat several thousand kinds of GM food. As an emerging technology, GMfood safety issues are widespread concerned. Experiments show that some animals eatingGM food will perform abnormal or even die. It becomes a hot academic discussion topic ofwhether GM food is harmful to human.So far, there are a lot of researches about GM food safety, many of which are based ona point of view as a starting point to evaluate GM food safety ,but all of these researchesfailed to combine with the multi-factor features in GM food system to build models based oninformation fusion analyzing platform. Therefore, the establishment of an effective multi-attribute information integration platform for intelligent assessment of China's developmentof GM food has important practical and theoretical value.GM food safety assessment system is a complex system, which involvs many factors,including quantitative statistical data and qualitative indicators composed by fuzzy linguistic.Each factor impacts differently to the overall safety evaluation system of the GM food.This paper aims to establish a multi-property information fusion decision-making modeland then develop an intelligent GM food safety assessment system which is based on theHierarchy Holographic Modeling(HHM) method, Analytic Hierarchy Process(AHP) methodcombined with D-S evidence theory. Specific researches are as follows:(1) Establish GM food safety assessment model. GM food safety is related to manyfactors which are called as indicators in this paper. The impact indicators of those factors areobtained by searching related documents and consulting specific experts.In this paper, the impact indicators are divided into several first level indicators. Eachfirst level indicator is then broken down into multiple second indicators, some secondaryindicators contain third indicators. These indicators include quantitative statistical data andqualitative indicators by expert's fuzzy language judgments. Different levels of indicatorsconstitutes the framework of GM food safety assessment model. (2) Get the indicators's weights in each level by AHP. AHP method is based on the ratioof relative importance to calculate each impact index weight. The safety assessment of GMfood in the target model is split into several multiple hierarchical structures. Experts will beinvited to give indicator's relative importance in each hierarchical structure. Then we willget matrix, eigenvector, weight vector and consistency indicator CR value by calculatingthe matrix. The weights of individual indicators will be got when CR value satisfy theconsistency conditions.(3) Research method how qualitative and quantitative indicators are changed into basicprobability assignment(BPA) of evidence theory. To qualitative indicators, asking relevantexperts give the safety level and their confident to get BPA functions. To quantitative indi-cators, the existing statistical data sample is divided into multiple regions by several cut-offpoints, each region correspond to a safety level of GM food. To a specific data, compared tothe cut-off points, its region will be got resulting in its safety level and BPA function.(4) On the foundation that evidences have con?icts, the methods have advantages anddisadvantages which are used to deal with con?ict evidence. In this paper, Deng Yong'smethod is used to deal with con?ict evidence to get the final BPA function. The biggest BPAfunction is corresponding to GM food's safety.(5) In this paper, we develop an intelligent system to assess GM food safety, based onMatlab programming and graphic user interface(GUI) environment. This system can realizedthe integrated assessment to China's different areas, different years and different types of GMfood as well as its single indicators respectively.