Design and Application of Compensatory Fuzzy Neural Network Based on Adaptive Learning Rate Method

To overcome the disadvantages of general networks such as slow convergence speed and being unable to combine with the expert knowledge etc,the authors introduces compensatory fuzzy neural cells,integrate the powerful knowledge expressiveness of fuzzy system and the excellent self-learning of neural network,and present a novel Compensatory Fuzzy Neural Network(CFNN) based on Adaptive Learning Rate Method which changes the learning rate using Adaptive Learning Rate Method in dynamic way.Finally this method is applied to the actual case.The result proves that it not(only) can adjust parameters properly on line,but also can optimize relevant fuzzy reasoning in dynamic way,fasten training rate.     

A Practical Expert System for Plant of Tomato

Research for expert system of tomato planting, it intents to set up a all around expert decision system combining agriculture knowledge, scientific research production and practical experience with computer technology. This system makes the best of the modern multimedia computer technology, which gathers words, sound and image .It provides visual, intuitive,scientific and convenient environment using. Moreover, it employs theories of Artificial Neural Network and Expert System, combines experience of experts in tomato's field and simulates agricultural experts to guide farmers to plant tomato.     

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.     

Study of Intelligent Fault Diagnostic System for a Kind of Power Plant

Based on the neural networks, object oriented technique, artificial intelligence technique and computer networks, an intelligent fault diagnosis system of the power plant whose need of the operation is presented. The architecture of software system , hardware system and corresponding databases is designed. The software of collecting data is established. The intelligent fault diagnosis system based on neural networks and object oriented technique is also developed. The physical system operation has been shown that the method mentioned above is feasible and effective in practice.     

State and Prospects of Diesel Engine Fault Diagnosis Technique

As a kind of complex power machinery, diesel engine is being paid more and more attention to its condition monitoring and fault diagnosis technology. In the fault diagnosis field of diesel engine, the technique of signal process, character abstraction and identification method have formed a system, but there is a certain distance away from practical. This paper analyzes the common faults and influencing factor of diesel engine. The principle, characteristic and disadvantage of modern fault diagnosis technology, such as various time-frequency methods based on vibration signal, speed fluctuation method, iron content and spectrometry, grey system theoretical diagnosis method, artificial neural network and expert system fault diagnosis method, were reviewed. The difficulties and the development direction of diesel engine fault diagnosis were put forward in the end.     

The Development of Intelligent Fault Diagnosis System Based KBE Graph

Aimed at solving the insufficiency problem in the current intelligent fault diagnosis system, such as lack of development tools, inference oversimplification, and developed a kind of diagnosis system based on network and KBE graph. The system is simple and easy to establish, modify, expand and maintain and does not need further coding. In addition, it can significantly save time and reduce the chance of failure. The integration of expert rules, fuzzy logic and nerve network enables the system to adapt to those complicated systems which involve in multi-variable, multi-parameter, multi-object and multi-process. As an example, an on-line detection system for simulate-on rotor test bench has been established and typical faults were successfully diagnosed through it, which proved the validity and reliability of the system. Furthermore, the system has been declared national invention patent.     

Fault Diagnosis Expert System of Combustion Engine with Rough Set Theory

On the basis of fault diagnosis expert system, the rough set theory is introduced. Knowledge representation system table is taken as a major tool to reduce the rules of expert system in which unnecessary properties are eliminated. The redundancy of fault diagnosis information is revealed. The complexity of fault diagnosis expert system's structure is also reduced. The decision making rules are given finally.     

The Study on the Branched Feedforward Neural Network

Based on the BP algorithm,the Branched Feedforward Neural Network,one ofthe artificial neural network medel used for pattern classification is proposed in this paper, and therelated algorithm is also offered here, Several typical examples of pattern classification are studiedwith computer simulation, The simulation results show that the training time of Branched Feedforward Neural Network is obviously reduced and the classifying effect is much better as compared withgeneral BP Network.     

Parsimonious Covering Probability Model for Turbogenerator Vibration Faulty Diagnosis

The turbogenerator vibration faults have the character of variety. Many faults often occur synchronously. This paper introduces a diagnosing model based on parsimonious covering theory and probability. A model for turtogenerator's fault diagnosis is proposed. The availability of this method is proved by two fault diagnosis examples of turbogenerator. The results show that the model proposed can be used for multi_fault diagnosis together. It may make up shortage for some of expert systems and neural networks in some aspect. From the practice,this model has higher reliability and practicability.     

Research in Automation Process Planning About Sheet Metal

Along with the development and appliance of the artificial intelligence, professional have adopted many kinds of methods such as expert system, NN and so on to explore an innovation type CAPP. The paper gives a brief introduction to the principle and design methods of process planning based on the theory of expert system developing a computer aided process planning system of sheet metal and discusses in detail the system uses the network graph to describe the parts and technology decision-making route, and the methods of separated reasoning and various expressions of knowledge are used to solve the complexity of development in CAPP research. Finally satisfied the requirement of the practicability?opening and intelligence about the system.     

土壤含水率与像素颜色之间关系的BP人工神经网络模型

建立像素颜色RGB值与土壤含水率之间的数学关系,是染色入渗法的应用基础。结合沟灌染色入渗试验。研究了染色入渗过程中土壤含水率与像素颜色分量之间关系的BP人工神经网络模型。分析土壤含水率与像素颜色分量之间的关系,确定BP人工神经网络的拓扑结构,以像素颜色分量的相对值作为输入因子。土壤含水率作为输出因子,建立了包含1个隐层的BP人工神经网络。结果表明,该模型具有较高的拟合精度和验证精度,优于二次多项式模型。     

Organically Combinatorial Inference and Optimization in Intelligence System

The inference algorithm is the most important part in intelligence system because the level of intelligence in the system is decided by it. By means of the mutual benefit for inference algorithm of expert system ,fuzzy logic and neural network ,the combinatorial inference technology which is organically composed of these three parts is put forward for inference mechanism in intelligence system. The optimization decision model is also set up. In order to bring all the advantage of every inference algorithm into play and overcome the disadvantage of single inference algorithm the common expert knowledge base is applied to organic combination and concurrent operation of all inference algorithm. In order to realize knowledge share the inference results are optimized by decision technology optimization. The research results show that the organized combinatorial inference and optimization can be applied in engineering practice effectively and is benefit for raising the inference level.     

Fault Diagnosis in Hydraulic Turbine Governor Based on BP Artificial Neural Network

The governing system of hydraulic turbine generator plays an important role in power system. It is significant to find out the faults of governing system and remove them quickly. This paper sets up a new fault diagnosis model of the hydraulic turbine generator governing system with the advanced ANN (artificial neural net). This 17-in-13-out model consists of three layers. It is proved that this model can find the fault accurately.     

Optimize graphics reasoning technlogy and its application on sheep diseases curing expert system

Expert system is a program system that prossesses special knowledge and esperience, is reasoning solving process which simulates experts according to special konwledge and espericence with artificial intelligence. This paper discusses the decision-making technology and method of expert system based diagram reasoning, the optimized diagram reasoning is also pointed out. The development technology and method of sheep diseases curing system is expatiated.     

Knowledge Representation for Rotative Machine Fault Diagnosis Based on Semantic Net

Aiming at knowledge representation problem of expert system for rotary machinery fault diagnosis, semantic net knowledge representation is discussed. Semantic net to represent expert knowledge of rotary machinery fault diagnosis is explored. Its realizing method is afforded in computer language, in addition, demostrating model is also developed in Visual C++. The result shows good validity of the knowledge representation.     

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.     

Diagnosis Model Based Neutral-network in Galactophore Cancer Cell Identification

To the classified problem of the Galactophore Cancer Cell Identification, the paper researched the classified mechanism and optimized parameter for more-layer radial basis function (RBF) network, adopted the method of gradient descent with momentum and adaptive learned backpropagation, constructed the two-model of the Galactophore Cancer Cell Identification based on BP Neural-Network and RBF Network. Classified principle based on RBF Neural network was also discussed, and the method for data processing was studied. RBF network has more advantage, such as fault tolerance, nonlinear mapping, etc.. Experiment results show that, on the model based RBF Neural Network, performance is steady, training time is short and classified results are good.     

基于PAID的荔枝农业专家系统的开发研究

将计算机网络信息、人工智能、多媒体等技术与农业技术结合起来,研究开发出基于PAID开发平台的荔枝农业专家系统,并根据本地的具体实际进行了软件资源的二次开发,降低了客户端的专业要求,实现了人机操作界面直观、明了。该系统的推广应用,有效地解决了目前中国荔枝生产中普遍存在专家型农业科技人员短缺的问题,为农业科技咨询服务提供了新途径,有利于先进农业技术的普及和推广应用。介绍了荔枝农业专家系统目标、系统结构、系统内容、系统实现及应用示范情况。     

NLPNN Model in Power Systems Reliability Evaluation

The purpose of a power system is to deliver the power the customers require in real time, on demand, within acceptable voltage and frequency limit, and in a reliable and economic manner. Using NLPNN (New Linear Programming Neural Network) model, the behavior analysis of power system under fault conditions is carried through. The stability and convergence theorems are set up to obtain the resolution for the problem of the load curtailment strategy. A new way is open up to evaluate the reliability of power systems and the great progress in calculation analysis model is achieved. The new calculation technique and theory foundation of reliability evaluation are supplied.     

Application and Development of Chemometrics in Ink Analysis

Ink analysis is an important part of material evidence analysis in forensic science. It not only needs to acquire data by precise chemical analysis instruments, but also needs to parse data by the chemometrics methods such as principal component analysis (PCA), cluster analysis (CA), artificial neural networks (ANN) and pattern recognition and so on. The main applications of chemometrics in ink synthesis, including experimental design and optimization, signal processing, multivariate calibration, pattern recognition, database technology and expert system, have been reviewed. Furthermore, future trends of ink analysis are prospected.