The whole frame of nature_inspired computation systems is inquired into, the characteristics of machine learning in nature_inspired computation systems are researched, and a particular scheme on machine learning in nature_inspired computation systems is designed with environment being gathered present data; study unit adopting fuzzy optimizatio algorithm based on genetic algorithm; knowledge ba...

Fuzzy Image Regions were proposed recently as an alternative GEOBIA method for conducting qualitative land cover classification. In this paper, these fuzzy segments are applied for estimation of quantitative (i.e. compositional) land cover. The method comprises three main stages: (i) fuzzy segmentation to create segments with indeterminate boundaries and uncertain thematic allocation; (ii) feat...

The defects of BP neural network, such as low convergence speed, falling into local minimum easily, bad generalization ability, can depress the calculation accuracy of BP neural network and damage its practical effect. So the research of improving BP neural network has great theoretical and practical significance. The paper advances a new fuzzy neural network algorithm to overcome the defects o...

This paper presents a novel improved fuzzy particle swarm optimization (IFPSO) algorithm to the intelligent identification and control of a dynamic system. The proposed algorithm estimates optimally the parameters of system and controller by minimizing the mean of squared errors. The particle swarm optimization is enhanced intelligently by using a fuzzy inertia weight to rationally balance the ...

The primary benefit of fuzzy systems theory is to approximate system behavior where analytic functions or numerical relations do not exist. In this paper, heuristic fuzzy rules were used with the intention of improving the performance of optimization models, introducing experiential rules acquired from experts and utilizing recommendations. The aim of this paper was to define soft constraints u...

The development of techniques for lateral and longitudinal control of vehicles has become an important and active research topic in the face of emerging markets for advanced autonomous guided vehicle (AGV). Considering an AGV is nonholonomic dynamic system with inherent nonlinearity, unmodelled disturbance and unstructured unmodelled dynamics, fuzzy logic system based control is appropriate. Th...

An improved fuzzy c-means algorithm is put forward and applied to deal with meteorological data on top of the traditional fuzzy c-means algorithm. The proposed algorithm improves the classical fuzzy c-means algorithm (FCM) by adopting a novel strategy for selecting the initial cluster centers, to solve the problem that the traditional fuzzy c-means (FCM) clustering algorithm has difficulty in s...

To demonstrate the applicability and feasibility of AI technology in nuclear fields in China, a fuzzy controller to control the reactor power of China Advanced Research Reactor (CARR) is designed in this paper. The fuzzy controller uses Mamdani inference system based 2 inputs-power difference and power period, 1 outputvelocity of control rods. To evaluate the performance of the fuzzy controller...

This chapter discusses about a new fuzzy logic and histogram based algorithm for enhancing low contrast color images. The proposed method is computationally fast compared to conventional and other advanced enhancement techniques. The given RGB image is converted into HSV color space to preserve the chromatic information contained in the original image. To enhance the image, only the V component...