Abstract
Under the precondition of relatively adequate historical sample data of obtainable software cost, the thesis makes comprehensive analysis of the advantages and disadvantages of complementary neural network and vector machines, and attempts to study the software cost combined estimation based on RBF neural network and RVM and to build combined estimation model, then applies the entropy evaluation method to identify the weight coefficient of this combined estimation model, and finally it adopts the data from COCOMO database to verify this combined estimation as well as the rationality and scientificity of this model.
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