Using genetic algorithm for extension and fitting of belief measures and plausibility measures

Determining some special types of fuzzy measures is an important topic in systems research. It has wide applications in various areas. Some construction strategies, such as statistics from given input-output data, have been developed recently. This paper investigates another strategy of construction: extending or optimally revising a given set function to be a belief measure or a plausibility measure.