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1.
神经网络与模糊逻辑   总被引:2,自引:0,他引:2  
本文把神经网络模型理论分为四个部分:①神经元模型及其理论;②单层神经网络;③多层神经网络;④模糊神经网络。并分析了一些重要的神经网络模型的结构、算法及其性能。在此基础上,本文还着重分析了神经网络与模糊逻辑的关系,并指出了它们对新一代计算机的研制有着重要的影响。  相似文献   

2.
模糊ART神经网络在运动目标识别中的应用   总被引:1,自引:0,他引:1  
本文在讨论模糊ART神经网络及其算法的基础上,研究和提出了一种三维运动目标识别方法,利用模糊ART神经网络对运动目标的目标侧面图形进行学习和模式识别。模拟实验表明了该方法的有效性。  相似文献   

3.
一种新型的模糊神经网络及其应用   总被引:8,自引:1,他引:7  
本文提出了一种新型的模糊神经网络,从理论上论证了其推理的合理性和逼近能力,同时应用于系统辩识,取得较好的效果。  相似文献   

4.
基于神经网络的模糊决策方法   总被引:4,自引:0,他引:4  
给出用神经网络去处理模糊决策问题的方法,此方法避免了模糊决策计算量大、计算复杂,隶属函数确定带有主观性等问题。  相似文献   

5.
模糊神经网络在数据融合技术中的应用   总被引:5,自引:0,他引:5  
本文主要阐述了模糊神经网络技术,尤其是模糊联结聚合神经网络技术在数据融合技术中的理论与应用。  相似文献   

6.
软计算中的协作和融合技术综述   总被引:5,自引:0,他引:5  
本文综述了软计算中的协作和融合技术,包括的专题是:模糊系统与遗传算子,模糊系统与神经网络,神经网络与遗传算法。最后探讨了今后的发展趋势。  相似文献   

7.
带阈值的Min—max模糊Hopfield网络的稳定性与容错性分析   总被引:3,自引:0,他引:3  
本文讨论了带阈值的Min-max模糊Hopfield网络的性质,并研究了该网络的一致稳定性与平衡态的Lyapunov稳定性。给出了一个模糊模式成为该网络吸引子的等价条件。然后在一定的条件下,得到了这个网络吸引子的一个非退化的吸引域,从而我们所建立的模糊神经网络模型具有较强的容错性,最后的例子证实了这一点。  相似文献   

8.
本文根据T-S模糊模型提出了一种新的基于神经元的自适应模糊推理网络,给出了连接结构和学习算法,它能自动学习和修正隶属函数及模糊规则,将其用于Box的煤气炉,太阳黑子预报以及降雨量预报等不同类型的复杂系统建模,仿真结果表明,该模糊神经网络具有收敛速度快,辨识精度高,泛化能力强和适应范围广等特点,可当作复杂系统建模的一种有效工具。  相似文献   

9.
基于模糊径向基函数神经网络的模糊数据建模研究   总被引:3,自引:0,他引:3  
提出将模糊径向基函数神经网络(FRBFN)用于模糊数据的建模,并提出融和圆锥模糊向量的聚类方法和模糊线性回归的学习算法。仿真研究表明.FRBFN及其算法在模糊数据建模方面有一定的优势。  相似文献   

10.
基于神经网络的模糊推理   总被引:2,自引:0,他引:2  
为了使模糊推理符合推理原则,目前已定义了10多种模糊关系,但各种模糊关系定义都存在一定的缺陷。本文提出的基于神经网络的模糊推理,能很好地符合模糊推理原则。  相似文献   

11.
In this paper we explore the problem of tracking a near-field moving target using fuzzy neural networks (FNNs). The moving target radiates narrow band waves that impinge on an array of passive sensors. At a particular time instance, the location of the target is estimated by several judiciously constructed FNN-based angle and distance estimators. When the target is moving, its trajectory can be on-line estimated due to the parallel and real-time computational capability of the FNNs. Computer simulation results illustrate the performance of the FNN-based angle estimator, distance estimator, and the near-field moving target tracker.  相似文献   

12.
Recently, Li [16] introduced three kinds of single-hidden layer feed-forward neural networks with optimized piecewise linear activation functions and fixed weights, and obtained the upper and lower bound estimations on the approximation accuracy of the FNNs, for continuous function defined on bounded intervals. In the present paper, we point out that there are some errors both in the definitions of the FNNs and in the proof of the upper estimations in [16]. By using new methods, we also give right approximation rate estimations of the approximation by Li’s neural networks.  相似文献   

13.
本文引进了集值函数的s-可微和模糊值(F值)函数的Fs-可微概念。给出了这两种可微性的几个判别条件。最后研究并得到了一类模糊神经网络(FNN)的Fs-可微性和连续性。  相似文献   

14.
This paper proposes a new interval uncertainty analysis method for structural response bounds with uncertain‑but-bounded parameters by using feedforward neural network (FNN) differentiation. The information of partial derivative may be unavailable analytically for some complicated engineering problems. To overcome this drawback, the FNNs of real structural responses with respect to structure parameters are first constructed in this work. The first-order and second-order partial derivative formulas of FNN are derived via the backward chain rule of partial differentiation, thus the partial derivatives could be determined directly. Especially, the influences of structures of multilayer FNNs on the accuracy of the first-order and second-order partial derivatives are analyzed. A numerical example shows that an FNN with the appropriate structure parameters is capable of approximating the first-order and second-order partial derivatives of an arbitrary function. Based on the parameter perturbation method using these partial derivatives, the extrema of the FNN can be approximated without requiring much computational time. Moreover, the subinterval method is introduced to obtain more accurate and reliable results of structural response with relatively large interval uncertain parameters. Three specific examples, a cantilever tube, a Belleville spring, and a rigid-flexible coupling dynamic model, are employed to show the effectiveness and feasibility of the proposed interval uncertainty analysis method compared with other methods.  相似文献   

15.
This paper presents a type of feedforward neural networks (FNNs), which can be used to approximately interpolate, with arbitrary precision, any set of distinct data in multidimensional Euclidean spaces. They can also uniformly approximate any continuous functions of one variable or two variables. By using the modulus of continuity of function as metric, the rates of convergence of approximate interpolation networks are estimated, and two Jackson-type inequalities are established.  相似文献   

16.
The fuzzy intersection rule for Fréchet normal cones in Asplund spaces was established by Mordukhovich and the author using the extremal principle, which appears more convenient to apply in some applications. In this paper, we present a complete discussion of this rule in various aspects. We show that the fuzzy intersection rule is another characterization of the Asplund property of the space. Various applications are considered as well. In particular, a complete set of fuzzy calculus rules for general lower semicontinuous functions are established.  相似文献   

17.
A genetic algorithm (GA) with varying population size is developed where crossover probability is a function of parents’ age-type (young, middle-aged, old, etc.) and is obtained using a fuzzy rule base and possibility theory. It is an improved GA where a subset of better children is included with the parent population for next generation and size of this subset is a percentage of the size of its parent set. This GA is used to make managerial decision for an inventory model of a newly launched product. It is assumed that lifetime of the product is finite and imprecise (fuzzy) in nature. Here wholesaler/producer offers a delay period of payment to its retailers to capture the market. Due to this facility retailer also offers a fixed credit-period to its customers for some cycles to boost the demand. During these cycles demand of the item increases with time at a decreasing rate depending upon the duration of customers’ credit-period. Models are formulated for both the crisp and fuzzy inventory parameters to maximize the present value of total possible profit from the whole planning horizon under inflation and time value of money. Fuzzy models are transferred to deterministic ones following possibility/necessity measure on fuzzy goal and necessity measure on imprecise constraints. Finally optimal decision is made using above mentioned GA. Performance of the proposed GA on the model with respect to some other GAs are compared.  相似文献   

18.
FuzzySRegularSpacesandSAlmostRegularSpacesFangJinming(DepartmentofAppliedMathematics,OceanUniversityofQingdao,Qingdao,2660...  相似文献   

19.
This note considers a new factorization of a fuzzy weak binary preference relation into its asymmetric and symmetric parts. Arrow’s General Possibility Theorem is then examined within the resulting framework of vague individual and social preferences. The outcome of this exercise is compared with some earlier results available in the literature on the Arrow paradox with fuzzy preferences.  相似文献   

20.
In much of human reasoning, the form of reasoning is approximate rather than exact as in ‘A red apple is ripe and this apple is more or less red. Then this apple is more or less ripe.’L.A. Zadeh and E.H. Mamdani suggested methods for such a fuzzy reasoning as an application of fuzzy set theory. The method involves an inference rule and a conditional proposition which contains fuzzy concepts.In this paper we point out that the consequence inferred by their methods does not always fit our intuitions and we suggest the improved methods which fit our intuitions under several criteria.  相似文献   

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