Artificial Neural Network Fault Diagnosis System Based on Rough Set Theory

On the basis of fault diagnosis neural network model, in this paper, knowledge representation system of rough set theory is taken as a major tool to delaminate the complex neural network and in which unnecessary properties are eliminated. This method overcomes some shortcomings, such as network scale is too large and the rate of classification is slow. The good effect that reduces the matching quantity of pattern search in classification course is gotten. The structure and algorithm of layered-mining neural network model based on rough set theory are also given. The example shows that this system has higher reference value in practical application.     

The Three-Valued PMC Model Computer System Diagnosis Implemented by Artificial Neural Network

This paper systematically studied how to construct a neural network to realize the three-valued computer system diagnosis problems. Through a lot of simulation it seems effective to solve the computer system diagnosis problems with the help of network. Meanwhile the simulation also reveals the relations among capacity C, resistance R , gain Kand time.     

Calculation Method of Hydraulic Characteristics for Direct-Return Chilled Water System

In order to optimize design and operation, it is necessary to calculate accurately hydraulic characteristics large central air-conditioning systems. Simplified Model can not be applied to hydraulic calculation of large pipe network topological structure for its large calculation error. Taking into account the regulating characteristics of terminal branch temperature regulating valve, a direct-return chilled water system is studied, an accurate mathematical model of pipe network hydraulic characteristics has been established and a computer logic algorithm with virtual flow has been given. A direct-return pipe network with ten AHU branches is used as simulation calculation object, the pipe network supply-return water pressure difference is calculated, and also the temperature regulating valve opening and actual flow of each branch are calculated in the condition of different supply-return water pressure difference. The calculated results accord with the natural characteristics of high pressure difference unbalanced for direct-return pipe network. The calculation method can ensure calculation convergence.     

Network Security Monitor

Illegal traffics on network can be actively detected by network security monitor An advanced system is given which can capture network data stream and intercept malicious attack, so as to alarm or take response action in real-time. The system is composed by sniffer, monitor control center, remote management unit,etc. Attack activities under surveillance can be distinguished by two methods,which are rule based method and statistics based method. Intrusion recognition by sniffer is the key technology of the system. In addition, dilemma between real-time data stream and high inquiry speed, as well as dynamic addition of attack rules contributes to the main concern of system design. Backdoor of The system can be self detected, while intelligent analysis and bi-directional surveillance ability has also been implemented. With all these advance features, the system is presented not only as a strong assistant to traditional network security products, but also an important tool for counter-fighting with rampant network intrusion nowadays.     

Analysis of the Optimal Effect Radius of Regulator Station in Urban Gas Distribution Network with Medium Pressure

In urban gas network with multiple pressure ranges, there is an optimal effect radius, for which the annual calculating cost is minimal. According to the analysis of technology and economy about the gas supply with the medium pressure in urban gas transmission and distribution system, the optimal effect radius of regulator station in medium pressure gas network has been obtained.     

作物非充分灌溉决策指标研究进展

为了有效地进行非充分灌溉,通过不同方面研究土壤和作物水分亏缺的诊断方法,从而制定科学有效的灌水指标。对目前非充分灌溉的土壤、灌溉、作物等指标的研究现状及存在的问题进行了的阐述,讨论了非充分灌溉决策指标今后研究发展的方向。从目前国内外研究情况来看,应用叶水势、茎直径变化、冠层温度等作物指标来精确诊断作物的水分状况,已逐渐成为非充分灌溉研究领域关注的热点,但其基础理论、监测方法及不同作物的应用效果仍需进一步研究完善。因此,单纯从一种灌溉决策指标出发确定灌溉量是不全面的,如何建立非充分灌溉条件下不同地区、作物的灌溉指标体系将是今后中国重要的研究内容。     

Study on the Method of Intelligence Fault Diagnosis System for Drill

It is very difficult to simulate the motion process of drill by accurate mathematics model for the complexity and invisibility of stratum. The fault of drill is usually identified and disposed by personal experience so far. This means it can not estimate the trend of the equipment running good or not and the reason conduced the fault or location and degree of fault by data measured. Farther, it can not give the expert suggestions. Based on the studying of drill fault, artificial intelligence and expert system have been used in the petroleum drilling engineering, the theory and method of fault diagnosis intelligence system for drill have been studied. It also constitutes the expert knowledge database of graphic Fuzzy Neural Network for the familiar fault of drill. The intelligence reasoning machine which consists of expert rule, Fuzzy logic and artificial Neural Network have been bring forward. And the fault diagnosis system it makes for drill can be applied in complex system which includes multi-variable, multi-parameter and multi-process.     

Grey networks: The contradictory dimensions of Australia's immigration detention system

The notion of dark networks has recently received attention in the literature on policy network analysis. Dark networks are defined as illegal and covert, in contrast to bright networks which are legal and overt. In this article, we suggest a third category – grey networks – which are characterised by their use of secrecy and concealment despite their ostensibly legal status. These networks are subject to contradictory imperatives. They employ methods that cannot be openly acknowledged within the larger legal and social framework in which they function. In this article, we illustrate this concept through an interview‐based study of Australia's immigration detention network. This network enacts a deterrence policy which has been widely condemned as breaching Australia's obligations under international law. At the same time, it is required to maintain a façade of lawfulness and respect for human rights.     

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.     

Study on ANN Based Character Recognition

The theory of Artificial Neural Networks and image processing are analyzed. ANN theory is also investigated . A Back Propagation network is used for classification. Based on the ANN and feature extraction, a character recognition and entry system is developed. Its drawbacks are discussed. Some solutions are presented. An odd feature database is constructed to promote the performance for learning. A 3 layer feedforward network has been proved that it has the ability to identify hand written characters.     

Design of networking condition monitoring andfault diagnosis for wind turbine transmission system

In order to solve the incipient fault diagnose problem of the transmission system, a networking condition monitoring and failure diagnosis system based on B/S and C/S hybrid architecture for wind turbine transmission system is designed in the paper. Firstly, the paper analyzes the demands of condition monitoring and fault diagnosis system for wind turbine transmission system, and designs its overall framework and function modules. Then, combining with the data acquisition equipment, by the .NET and SQL Server platform, the paper designs condition monitoring and failure diagnosis system for wind turbine transmission system, which includes the functions of networking data acquisition, remote condition monitoring, signal analysis, fault diagnosis and database as well. The system has been successfully applied to a condition monitoring and fault diagnosis of wind turbine transmission system.     

BP Neural Networks and Its Application in Lung Cancer Intelligent Diagnosis System

The learning algorithm of networks is discussed. The programming example of 3 layer BP networks is given with Visual C++6.0 program langue. Based on this model, a lung cancer intelligent diagnosis system is successfully implemented. Furthermore, the paper introduces network's structure design, preferencesand the source of stylebookdatum in factual applications. The ameliorative arithmetic is applied to the study of networks and BP dynamic evolving process is designed. The experiments indicatecell images are recognized and classified by the trained neural network. The study illustrates the system has feasibility and clinical value in lung cancer diagnosis.     

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.     

两型社会建设背景下长株潭城市群耕地安全性评价

摘要：耕地是一种具有经济、生态和社会价值的重要资源,它的数量、质量和生态状况关乎一个地区资源节约和环境友好型社会的建设。本论文运用长株潭城市群耕地利用历史数据,采取层次分析、障碍度分析等研究方法,以两型社会建设理论为依据,在定性描述耕地资源安全内涵的基础上,从资源节约、环境友好两个方面构建评价指标体系,对长株潭城市群耕地资源安全状况进行了评价和障碍度诊断。研究的主要结论是：（1）耕地资源安全具有系统性特征,其内涵涵盖数量安全、质量安全和生态安全,并成为一个有机整体;（2）研究区耕地安全总体及数量、质量和生态状况差异显著,1990-2007年间长株潭城市群耕地安全的总体状况趋于变坏,安全评估得分值从1990年的2.125降到2007年的0.158,表明该地区耕地资源安全存在制约因素;（3）通过障碍因素分析发现,研究区不同时段障碍因素不同,1990-1995年,耕地安全的障碍因素是城市化和经济的过快发展;1996-2002年,障碍因子则转变为地均粮食单产、地均经济产出等过低,而2003-2007年,则表现为环境污染排放等耕地的生态压力因素加大。     

Study on Network Learning System Based on Fuzzy Mathsmatic

Evaluation of network study result is key job that network teaching and network teaching system developments. Fuzzy comprehensive evaluation method is introduced to analyze the network study based on the network study evaluation system index system combining with the characteristics of the combinative network study. The paper puts forward the model of the fuzzy comprehensive evaluation of network study, it proves the fuzzy comprehensive evaluation method is a kind of valid method than other traditional method in network learning through an experiment.     

Evaluation Method Based on Artificial Neural Network in Contractor Prequalification of Tenderers

Both tenderees and tenderers attach much importance to contractor prequalification before bidding because it plays important roles for both and so far the Score Method has been widely used in our country. But the weights in the method are man-made, which may be affected by personality inevitably. In order to avoid this influence, this thesis will introduce another method based on artificial neural network. This thesis expatiates the principle of artificial neural network, and analyzes the characters of prequalification. Then, the author sets up the mathematics model. In the end, the author analyzes this method by an example.     

美国植物种质资源保护与研究利用

美国不是作物起源中心,但却是世界上保存植物种质资源最多的国家。美国拥有较完善的植物种质资源保护体系,其法律法规、管理制度、种质资源交换与共享政策、资助体系等稳定而灵活,保存设施和信息网络建设稳步发展,在种质资源收集、鉴定评价、新基因发掘、种质创新等方面针对不同作物的需求均取得了很大成效,充分体现出种质资源的基础性和公益性特点。本文在全面评述美国植物种质资源保护与研究利用情况的基础上,对我国种质资源保护、研究和管理提出了建议。     

低功耗粮情测控物联网模型研究

以储粮粮情测控为研究背景,以降低粮情测控系统功耗为目标,提出了一种低成本、低功耗、可扩展的弹性粮情测控物联网模型。粮情测控物联网模型包括三层结构:感知层、传输层和汇聚层。感知层支持多参数粮情数据感知;传输层多跳传输粮情数据;汇聚层兼容GPRS、WIFI、WLAN、3G、Enthernet等通信方式,系统结构灵活,扩展性强。实验验证,该模型相较于传统的WSN至少可以延长粮情测控系统的寿命,粮情感知节点在不更换电源情况下可以工作3~5年。     

Fault diagnosis of rotating machinery based on self-learning fuzzy spiking neural network

For fuzziness classific boundry of fault diagnosis of rotating machinery and traditional neural network algorithms difficulted to solve contradiction between application problems example scale and netwok scale,a methord of self-learning fuzzy spiking neural network is put forward. The methord overcomes unavailability of cluster analysis on classific boundry of fault diagnosis of rotating machinery by species encoding of pulse sequence and unsupervised learning. The method shows that it effectively solves boundary fuzziness problem on fault diagnosis of rotating machinery,and greatly improves efficiency of fault diagnosis.     

The Fuzzy Inputing And Outputing Method in Vibration Fault Diagnosis of Steam Turbine-Generator Set

A fuzzy neural network diagnosis model is established on the basis of the vibration failure features of steam turbine-gernerator set, two kinds of fuzzy inputing method are discussed. At last, the performance of the fuzzy neural network is compared with that of the conventional BP network. The results show that the method presented is suitable for identifying the vibration failure of steam turbine-gernerator set, and it is more efficient in deal with the uncertain data than BP network diagnosis.