Aimed at the type recognition problem in which the characteristic values of object types and observations of sensors are in the form of triangular fuzzy numbers, a new fusion method from the viewpoint of decision making theory is proposed. The method transforms the triangular fuzzy numbers elements of decision matrix into the expected value elements. After solving the optimization problem of minimizing the maximum deviation between the object types and the unknown object, the weights of the attributes are obtained. The result of recognition for the unknown object is given by the comprehensive attribute expected values. This method can avoid the subjectivity of selecting attributes weights. It is straightforward and can be performed on computer easily. Finally, a simulated example is given to demonstrate the feasibility and practicability of the proposed method.
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