Papers by Keyword: Fuzzy Arithmetic

Abstract: This paper transforms a common conjugate gradient algorithm, based on the fuzzy neural network for line. This thesis systematically studies the performances and learning algorithms of two FNN models, monolithic FNN and polygonal FNN, based on the past progress of FNN theory and application. The major issues in the thesis are the perturbation of monolithic FNN, the learning algorithms and universal approximation of polygonal FNN and the achievements obtained here are applied to fuzzy control area.

Abstract: In the proceeding of the CNC system, it is a valuable subject that how to locate the fault based on the function of the CNC system. To solve this problem, the method of searching in divided execution trace was introduced into the fault localization of the CNC system. This method divided the execution trace into two segments, searching the statements continually. At the same time, the Fuzzy Arithmetic was used to calculate the suspiciousness of the statements executed by these traces. After the integrated analysis, we could locate the faulty statements of the program. The experiment results indicated that this method was effective in locating the fault of the CNC system software.

Abstract: This paper studies mainly apples non-destructive selection technology, and presents the principle and implementation of non-destructive selection system for apple quality based on the theory of the fuzzy and neural network. Firstly, we can differentiate the kinds of apples by neural network theory. Then, the apple’s quality greatly depends on its size, shape, and color, which are considered as three input parameters in selection system. The pick-up of three character parameters is handled by computer image processing. Only one output parameter is apple rating, which is fall into three grades: A, B and C. Regarding three character parameters as input, we obtain the apple grade based on fuzzy arithmetic. Finally, we set forth the archetypal non-destructive selection system, which includes robot, AGV, conveyor, sensors and etc. Results of experiments show that this method can distinguish the apple’s quality as well as we set before the experiments, and the non-destructive system is feasible.