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The paper presents an evidential reasoning(ER) approach to risk assessment. An ER algorithm is briefly introduced which is used to combine evidences and deal with uncertainties. It is more effective to evaluate the level of risk factors in composite generation and transmission systems on the basis of the Dempster-Shafer's evidence theory and analytic hierarchy process (AHP) are applied to deal with the uncertainty of the risk factors. Firstly, for the rational assignment of conflict information to basic possibility assignment, the conditional combination rule is modified on the basis of the degrees of disorder of each presumption. Secondly, the modified rules is used to combine the evidence bodies formed from data analysis technologies by rough set, fuzzy clustering, artificial neuron network and Bayes theory. The methodology of transferring risk evaluation problem into a multiple-attribute decision-making (MADM) solution under an ER framework is then presented. Two solutions to composite system risk evaluation, using the ER approach, are then illustrated, highlighting the potential of the ER algorithm. Based on the outputs of the ER approach, system operators can obtain an overall risk evaluation of composite system for system maintenance purposes. It can be seen from the results that the ER approach is a suitable solution to tackle the MADM problem of risk assessment.