A fuzzy-neural system for R&D project termination decisions

In this paper a fuzzy-Neural system for assisting managers in deciding whether to abandon an ongoing research and development (R&D)/innovation project at various stages of R&D is presented. The system is basically a multi-layered fuzzy rule-based neural network which integrates the basic elements and functions of a traditional fuzzy logic inference into a neural network structure. A supervised gradient descent-based back-propagation algorithm is employed to adjust the parameters of the fuzzy neural network by using the training patterns. It has also been shown by the modeling and pattern recognizing results in terms of termination decisions of eleven R&D project that the method possesses reinforcement learning properties and universalized capabilities. With respect to modeling and terminating decision of R&D project, which has the fact that the evaluation criteria are hardly ever determined by conventional approaches such as statistical analysis, the method is available.