The Software Implementation of Neural Network Fuzzy Inference Cooperation System

This poper sets up a new Neural Network Fuzzy inference Cooperation system which is based on fuzzy inference principle in Expert Systems,take advantage of the powerful learning function, the little sensitivity to input layer's samples,and the fast convergence and so on in FCBP and take advantage of the good sort property and good suit property to fuzzy value in MFART Network.     

The Inherent Fault Tolerance of Multi-Layer Neural Networks

The inherent fault tolerance of multilayer neural networks (MLNs) is due to thedistributed properties of information processing and information storage in an MLN , and the inher-ent fault-masking capability of every neuron. Also,the concept of inherent fault tolerance of MLNsis formalized, Finally, perceptrons and three-layer nets are shown inherently fault tolerant underreasonable statistical conditions,respectively.     

Automatic Fingerprint Classification by GA-Based Neural Network

Fingerprint classification can provide an important indexing mechanism in a fingerprint database. An accurate and consistent classification can greatly reduce fingerprint matching time for large database. In the paper, by combining genetic algorithm and neural network is presented a fingerprint classification algorithm which is able to achieve an accurate classification. By inputting the global feature represented by directional image to three layer neural network trained by genetic algorithm, the fingerprints were classified into six categories: whorl, right loop, left loop, arch, double loop and undiscerning type successfully.     

A Muti-Objective Network Planning Model for Project

Based on the network planning model developed by the author for an overhaul project of a rolling mill production line in a heavy steel plant, an new multiobjective network planning model is proposed in this paper. The formulations of network time parameters are derived. The optimization problem of multiobjective network planning is also discussed. And it has been found out that the fractional single-objctive network is only one of the cases in this model.     

A MULTI -OBJECTIVE FUZZY DECISION -MAKING APPROACH FOR POWER NETWORK PLANNING UNDER UNCERTAINTY

This paper proposes a multi - objective fuzzy decision - making approach for power network planning under uncertainty ,which simutaneously considers not only the least investment cost,the minimum power loss,the maximum reliability,and the least environmental impacts, but also the uncertainty about the future load growth and the capital investment availability. The validity and effectiveness of the proposed approach is verified with numerical examples.     

The Method of Diagnosing Brain-dysfunction Based on Membership Function and BP Neural Network

Membership functions.formed with the characteristic values obtained by applying the continuous reaction time (CRT) theory from controls and heptic encephalopthy and proposedin this paper.whith these membership functions,the CRT data to be diagnosed are calculated in advance,and then discriminated by BP meural network to differentiate patients with or without braindysfunction.The troubles of low accuracy and efficiency,encountered in training BP network withfuzzy samples.scattered data and extended samples,are solved.     

基于SOFM神经网络的核心种质取样算法

介绍了核心种质和自组织特征映射网络的基本概念，使用自组织特征映射网络的自组织特性对种质性状数据进行了聚类，利用聚类的分组结果，提取核心种质，通过对核心种质的各种参数的检验并与完全随机取样和一般的系统聚类的对比。结果表明，SOFM的取样算法，是一种比较有效快捷的算法，可以在实际中加以应用。     

机械结合面切向接触阻尼的神经网络结构化建模

为了使机械结合面切向接触阻尼实验数据便于在机械结构CAD中应用，本文基于人工神经网络的非线性映射能力，提出了机械结合面切向接触阻尼基础数据的神经网络结构化建模方法，并进行了实例建模。结果表明，该方法实用、有效，建模精度和建模效率较高，而且集传统建模与建库思想于一体，实现了多种结合条件下的机械结合面切向接触阻尼基础数据的统一建模。