Research on Cooperative Design Network Security Based on IP-VPN

As the important method and instrument of agile manufacture,the technology of distributed collaborative design and manufacturing has become the hotspot of manufacturing. The basic concept and key technologies of IP_VPN are introduced in this paper,and a collaborative design network model based on IP_VPN is presented. Distributed collaborative design is a multi_user,multitask involved system, which is consisted of lots of collaborative processs,so the network security is the key of distributed collaborative design. We research on the security of collaborative design network based on IP_VPN, hence get a conclusion:we can construct an economical?practical and secure collaborative design network system by the application of data encryption,user authentication and access control based on the role,etc.     

Expert System for Artificial Intelligence Blast Furnace Smelting Process

In order to upgrade traditional industry and realize the automation of furnace condition judgement and standardization of operation, an expert system for various furnace conditions and breakdown judgement and operation guidance on blast furnace are developed based on the theory of artificial intelligence and knowledge engineering. The system is fulfilled through C++Builder and combined with the actual production picture. The system has efficient and convenient man-machine interface by using menu operation method. The testing and operation of actual production data in simulation system indicate that the system is exact and reliable and can provide both the warning of various furnace breakdown and corresponding operation guidance.     

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.     

Building Enviornmental Monitoring System With COM

This article presents an implement of component using COM technology for collecting environmental monitoring data in environment monitoring system. The component makes the separation of data collection and data analysis available.Simultaneously by using the interface of connectable object in COM,itmakes the cooperation of the environment monitoring software with other parts of fault management software available,and also the seamless connection.It improves the system's performance by adding extensibility and potential cooperatibility.     

An Expert System Approach to the Computer Aided Design of Intelligent Controllers

The idea for an expert system approach to the computer aided design of intelligent controllers (ESCAD1C) is discussed and the idea of two step modelling of an intelligent controller is presented on the basis of emulating human control behaviours to solve complex problems. The structure, functions and characteristics of ESCADTC system , and the design procedures of intelligent controllers are gived. The knowledge base and simulating functions for designing intelligent controllers are also described.     

Distribution Network Structure Planning Based on Improved Immune Genetic Algorithm

Distribution Network Structure planning is a complex combinatorial optimization problem,which is difficult to solve properly by using traditional optimization methods.In order to solve this problem,Improved Immune Genetic Algorithm is introduced to the distribution network optimal planning. Improved Immune Genetic Algorithm draws into the immune diversity and antibody's density mechanism to maintain the individual's diversity and remains evolution algorithm's global stochastic searching ability,so it can promote diversity and the whole optimal-searching ability of genetic algorithm.The optimal module takes the minimum annual cost as its object,and the capacity and voltage drop of feeder and the radiation of distribution network as its restrictions.According to the require of radiation of distribution network,the spanning tree of the alternative network is taken as the initial solution to speed up the calculation.And the branch-exchange method is used in designing crossover operator and mutation operator to avoid the radiation checking and enhance the optimizing ability.This algorithm has been illustrated effectively by examples,at the same time,the calculation example demonstrates that,the algorithm has higher calculation speed than the traditional immune genetic algorithm.     

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.     

Approach for Load State Detection in MIN

Some thoroughly research on the basic method for load state detection in MIN is introduced. Load sources of SCP and SSP in MIN are analyzed in detail after investigating the relationship between inter resource and load state in the system. And load detection parameters and model are presented. Moreover, a novel strategy to detect system load state based on fusion of multi detection data is presented. By some test, the theory and method are proved most feasible. Our research show that load state of MIN can be recognized by detecting utility of internal resource utilizing of single node in MIN, and multi redundant detecting data fusion is effective approach to improve the reliability and trust degree of the result.     

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.