物流企业的社会网络特征与企业间信任的构建

第三方物流企业较之其他企业显示出较强的网络特征，企业之间的社会关系网络及其信任构建对企业的生存和发展具有重要意义。本文通过实证研究发现，物流企业信任的形成与企业社会网络的形成过程密切相关，企业组织社会网络的连接对组织信任的构建产生着重要影响。信任加速了企业获取资源的速度和质量，资源获取是企业网际互动的目的和信任的结果。     

LM-BP神经网络水质评价模型应用研究——以新乡市卫河为例

介绍了LM-BP神经网络模型的原理及算法和模型的优点。针对实际水质评价问题,利用随机内插方法在地表水环境质量分级标准阈值间生成训练样本和检验样本,建立了新乡市卫河地面水环境质量综合评价的LM-BP神经网络模型,将模型应用于卫河2011年3月份、9月份的水质评价,并与单因子评价法、模糊综合评价法进行了比较分析。实验结果表明该模型设计合理,泛化能力强,收敛速度快,算法稳定,推导严谨,有较充分的理论依据,应用于水质评价具有其合理性、实用性和有效性,适用于作深入的水环境质量分析。     

Artificial Neural Networks Models for Flow Stress during High Temperature Plastic Deformation of Al-Li Alloy

Using gained experimental data to develop the models of stable flow stresses at high temperature plastic deformation by statistical methods for alloy materials, precision of the models is poor and at the same time the processes of modeling are complicated with great workload. On the basis of the data obtained on Gleeble-1500 Thermal Simulator,the predicting models for the relation between stable flow stress during high temperature plastic deformation and deformation strain, strain rate and temperature for 1420 Al-Li alloy have been developed with BP Artificial Neural Network method. The results show that the model on basis of BPNN is practical and it reflects the real feature of the deforming process. It states that the difference between the real value and the output of the model is in order of 5 percent.     

Multiple Layer BP Neural Network for Fuzzy Calculating

The FCBP(Fuzzy calculating BP) algorithm which is proposed by this paper hasovercome the sensitivity for samples,reduced the number of input layer's samples,lightened the burden of input layer.it is suitable to fuzzy inference and pattern recognition.     

Using BP Neural Network to Determine the Membership Function of the Input of Fuzzy Control System

While design the fuzzy controller, it is very important to determine the membership function of fuzzy variables.The data can be broadly classified as fuzzy sets by using the classification property of the BP neural network. The author selects a BP neural network with one hide layer and uses S function to the input and hide layer, and linear function to the output layer.Advanced BP algorithm isused to train the BP neural network in the environment of MATLAB . The nearer to the target values is the better the last output is.With the trained BP network , the membership values of the inputs can be got ten. This method has high rate and low error.     

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.     

Learning the BN Structure Based on the Sum of Mutual Information

The Crossing Entropy is defined to scale the similar level of two probability distribution. In many papers on learning BN structure,the Crossing Entropy was used as an indicator of measuring the learning accuracy of an algorithm.The known scoring metrics for learning BN structure is analyzed in this paper,then a new scoring metrics Sum of Mutual Information is proposed based on the information theory.At last,two algorithm for learning BN structure by SIM is represented.     

Clustering Routing for Wireless Sensor Networks

In wireless sensor networks that consist of a large number of low-power sensors.Because the sensor's energy is limited,one of the main design is to obtain long system lifetime.The authors firstly analyse LEACH and LEACH-C clustering routing for wireless sensor networks.Aimming at their shortcoming,they present a new routing LEACH-NEW.This routing uses multi ho Pinstead of one hop.At last,they use NS2 to simulate them.Simulation show results that new routing exhibits noticeably longer system lifetime than rouing LEACH and LEACH-C.