一种基于支持向量回归和动态特征选择的梨黑星病预测方法

当前作物病害预测方法存在时效性差、预测结果拟合度较低的问题.提出一种基于回归的预测方法框架,用SVM对数据向量特征进行约简,它可以重复选择密切相连的特征和构建可动态优化自身参数.用本方法对黄河故道览地区砀山酥梨黑星病为例进行预测测试,与现有方法以及实测数据进行相关性统计分析.结果表明在对酥梨的黑星病预测上提出的方法,在拟合度、推理效率和准确率上具有显著的优势.     

梨黑星病流行时间动态分析

用不同的流行学模型拟合2002年和2003年莱阳地区梨黑星病（Venturia nashicola）的系统监测数据，结果表明：Logistic模型能较好地描述梨黑星病病叶率随时间的变化动态；Gompertz模型能较好地描述平均病斑数随时间的变化动态。根据Logistic模型。梨黑星病的最佳防治时期是在梨树初花期后的60d内。     

基于高光谱的砀山酥梨炭疽病害等级分类研究

为了检测病害的不同程度等级,以接种炭疽病的砀山酥梨为研究对象,利用高光谱成像技术对病害进行建模分类。在400～1000nm光谱区域采集砀山酥梨样本接种炭疽病初期到发病、直至腐烂整个过程的时序高光谱图像;采用阈值分割法对图像进行背景分割,并基于有效的光谱区域做主成分分析,选取第二主成分(PC2)提取染病的感兴趣区域,并对感兴趣区域用权重系数法作特征值提取;采用非监督的分类算法对特征值进行聚类分析。通过对210个样本集进行观察分析发现,样本分类的有效程度为98.41%。实验结果表明,采用高光谱成像无损检测技术对砀山酥梨炭疽病不同程度的分类是有效的。     

梨黑星病分生孢子相对侵染量动态预测模型的研制

采用“闷罐车”技术,组建了梨黑星病分生孢子侵染动态预测模型(PSCIM)。PSCIM能以3min为一个步长计算梨黑星病菌分生孢子的侵染量,可以预测梨黑星病菌分生孢子在一个降雨过程中的相对侵染量。PSCIM采用了面向对象的程序设计方法,程序包括主窗体、驱动变量输入窗体和计算单元3个模块,能以图形和数据列表两种方式显示结果。PSCIM在Delphi 6.0实现编译,程序的结构清新自然,能较好地再现梨黑星病分生孢子的侵染过程。     

天津研发成功农技信息推广平台

日前,由天津市农业技术推广站开发的“天津农技推广信息服务平台”触摸屏终端投入使用。该平台以地理信息系统、遥感、专家系统和网络技术为核心,整合全市耕地土壤、气象、市场、科技人才、村镇政务等农业资源信息构建．包括测土配方施肥系统、专家系统、远程专家会诊系统、市场交易信息系统和政务公开系统5个子系统。测土配方施肥系统主要使用GIS地图展示地块,     

河套灌区秋浇管理决策专家系统的开发

在对试验资料的定量分析和系统总结的基础上，利用“雄风”4．1专家系统工具，建立了河套灌区秋浇管理决策专家系统，包括早秋浇的原因和优点、秋浇决策预报、保墒调墒措施方案的确定及地下水位动态预报四个子系统。对提高灌区管理的现代化、科学化及推广该项技术有重要意义和实用价值。     

河套灌区秋浇管理决策专家系统的开发

在对试验资料的定量分析和系统总结的基础上,利用“雄风“4.1专家系统工具,建立了河套灌区秋浇管理决策专家系统,包括早秋浇的原因和优点、秋浇决策预报、保墒调墒措施方案的确定及地下水位动态预报四个子系统.对提高灌区管理的现代化、科学化及推广该项技术有重要意义和实用价值.     

基于图像内容检索的作物病害识别数据库系统研究

针对作物病害诊断专家系统存在不足,提出基于图像检索的方式诊断病害.通过病害图像建立特征库、知识库、图像库等数据库,诊断时提取检索图像特征,求特征与特征库中特征的相似度距离,按距离大小返回相似图像,依据返回结果获取病害的描述及防治措施.为提高检索的查准率和查全率,重点探索了病害图像数据库创建中特征库信息的获取和检索算法的设计.以烟草病害图像为例,采用基于支持向量机与多特征选择检测彩色病斑边缘的方式分割病斑,提取病斑特征25个,利用双编码遗传算法和支持向量机对特征降维,以获取表征病害的有效特征17个及对应权重,对特征归一化处理后建立数据库,并设计检索算法.实验结果表明,构建的图像数据库系统具有较高的查准率和查全率,其中融合病斑的多个特征检索的查准率比单一特征高.用这种方式诊断病害,除有较高的病害识别率外,还有诊断结果的可视化,将其用于作物病害诊断专家系统中,将提高系统的鲁棒性,为实现病害的远程在线诊断提供了条件.     

集控式足球机器人决策与控制系统设计与开发

构建了由视觉子系统、决策子系统、无线通信子系统、机器人小车子系统和总控子系统组成的集控式足球机器人系统．总结了具有集中视觉、决策与控制的集控式足球机器人系统的控制问题．设计了基于分层递阶控制结构的足球机器人决策子系统．小车控制器构成“无脑”的执行器,运动控制器中集成了各种各样的动作函数,组织层则融合了不同的决策方案．长期的开发实践和实战成绩都表明,该系统具有良好的结构和优异的性能．     

基于.NET的对虾病害防治专家系统的设计与实现

针对我国对虾养殖存在的问题,采用ASP.NET技术设计实现了基于B/S结构的对虾增养殖及病害防治专家系统.该系统运用多种知识表示方法将对虾养殖、疾病诊断与防治等经验性、科普性知识进行了集成表达,采用基于规则的模糊化混合推理策略,实现了对虾养殖的咨询与决策,疾病诊断与防治、专家会诊及网上学习等功能.经实践验证和专家评测,该系统界面友好,操作简单实用,维护方便等特点,具有一定的推广价值.     

Minimizing maintenance anomalies in expert systems

Expert systems are emerging as a powerful technology for solving many problems previously requiring human experts. However, maintenance has been identified as a major difficulty in expert system implementations. Surprisingly, the problem of maintenance has only recently begun to receive attention in expert systems research, though it has long been an issue in databases. Databases are in a constant state of change, and the prevention of maintenance anomalies is essential. As similar maintenance operations are performed on rule bases, this paper investigates techniques to avoid maintenance anomalies in expert system rule bases. The result is an expert system rule base structure that is appropriate for volatile production use. In addition to lower maintenance demands, this approach favorably impacts on verification, computational efficiency, and storage requirements.     

MINE VENTILATION EXPERT SYSTEM

A growing trend in the area of artificial intelligence is the development of software that simulates the decision-making process of human experts. The purpose of this paper is to advance the use of available tools from the area of artificial intelligence, and in particular expert systems, into the field of mine ventilation management. The authors have developed an expert system (i.e., a smart manager) that controls the operation of a mine ventilation network. The expert system is rule based and hence can be (independently) enhanced in an incremental fashion. It serves as a smart interface between the monitoring and control components of a mine ventilation system.     

An approach to expert recommendation based on fuzzy linguistic method and fuzzy text classification in knowledge management systems

Since organizational tacit knowledge such as know-how and experiences usually resides in the owner’s brain, consulting the expert is an effective and efficient way to utilize this type of knowledge. However, users are no longer able to effectively find the appropriate experts in the knowledge management system due to the complexity and diversity of the expertise and the knowledge needs. In this paper, an approach to expert recommendation is proposed to assist the user to find the required experts. The method adopts the fuzzy linguistic method to construct the expert profile, that is, to model expert’s expertise. In addition, the fuzzy text classifier is used to get the relevant degree of the document to each knowledge area when the document is registered, which is the base of the following user profile construction. Then, the user profile consisting of the time and the relevance factors of the rated documents is constructed to derive the overall knowledge needs level of the user. Consequently, the expert that fulfills the knowledge needs most is recommended based on the similarity between the derived expert profile and the user profile. The developed prototype system, “knowledge management system in aircraft industry company”, is introduced and the experimental results show the proposed approach is feasible and effective.     

Selection of knowledge acquisition techniques based upon the problem domain characteristics of production and operations management expert systems

The application of expert systems to various problem domains in business has grown steadily since their introduction. Regardless of the chosen method of development, the most commonly cited problems in developing these systems are the unavailability of both the experts and knowledge engineers and difficulties with the process of acquiring knowledge from domain experts. Within the field of artificial intelligence, this has been called the 'knowledge acquisition' problem and has been identified as the greatest bottleneck in the expert system development process. Simply stated, the problem is how to acquire the specific knowledge for a well-defined problem domain efficiently from one or more experts and represent it in the appropriate computer format. Given the 'paradox of expertise', the experts have often proceduralized their knowledge to the point that they have difficulty in explaining exactly what they know and how they know it. However, empirical research in the field of expert systems reveals that certain knowledge acquisition techniques are significantly more efficient than others in helping to extract certain types of knowledge within specific problem domains. In this paper we present a mapping between these empirical studies and a generic taxonomy of expert system problem domains. In so doing, certain knowledge acquisition techniques can be prescribed based on the problem domain characteristics. With the production and operations management (P/OM) field as the pilot area for the current study, we first examine the range of problem domains and suggest a mapping of P/OM tasks to a generic taxonomy of problem domains. We then describe the most prominent knowledge acquisition techniques. Based on the examination of the existing empirical knowledge acquisition research, we present how the empirical work can be used to provide guidance to developers of expert systems in the field of P/OM.     

A hierarchical expert system for computer process control

This paper reports on the design and implementation of an expert system for computer process control (HESCPC). The complexity of the expertise necessary for computer process control applications requires that the expert system architecture be structured into a hierarchy of classes of specialized experts. The architecture of HESCPC integrates four classes of expert systems: operator/manager companion expert class, control system algorithm design expert class, hardware expert class, and software expert class. The paper is concerned with the design and implementation of the general system architecture, an operator adviser expert for a nuclear power plant and a control system designer expert using a state space feedback approach. Although the design and implementation aspects of all experts are discussed, the emphasis is on the latter.

At this stage of the HESCPC development, the declarative knowledge represented by 423 metarules and 1261 rules is distributed on a hierarchical structure among 20 experts on different levels of the hierarchy which are able to communicate among themselves to solve difficult control problems.

Examples of control system design sessions of linear mono and multivariable systems using feedback state space approach are given. A run time of an operator-adviser data-driven expert system for a nuclear plant is also presented.     

压力容器焊接专家系统设计与实现

基于商品化软件“压力容器焊接专家系统”的开发经验，本文从系统实现角度提出专家系统的设计方法，在获取大量专家知识和经验的基础上，对专家知识进行分类研究并提出相应的表示方法，同时设计了可动态更新的知识库系统，本文还进一步探讨了专家知识的存储和管理机制。     

Design and validation of a knowledge-based system for screeningproduct innovations

The authors' research goal is to develop and validate an expert system that screens innovations prior to commercialization. This is an important research issue because business corporations are highly dependent on innovations for their growth and profitability, yet most corporations suffer from a high rate of new product failure. Few of the existing decision support systems have alleviated this problem, partly because of their inability to deal with nonmathematical (logical) relationships. An expert system for new product planning could save organizations tremendous amounts of resources (such as dollars, time and scientific talent) spent on product failures. The design of the proposed knowledge-based system is built upon the authors' earlier work in this area. The authors have addressed several critical research issues in the development of such a system: choice of the appropriate sources of knowledge, resolution of conflict among human experts chosen for knowledge acquisition, use of knowledge programming techniques that can accommodate uncertainty, and multiple methods of system validation. The research makes several contributions to marketing theory and practice. Most notably, the development of such systems contributes to effective product planning in organizations and enhances resource efficiency. Further, it generates guidelines for capturing and using expertise in highly unstructured decision-making situations such as product management     

POMME: a computer-based consultation system for apple orchard management using Prolog

Abstract: Direct dissemination of expert knowledge to agricultural producers through computer programs will increase product quality as well as the profit margin. The construction of an expert system, called POMME, to help farmers manage apple orchards is reported here. The system provides advice regarding specific pest management, treatment of winter injuries, drought control and general pesticide selection. A sample interaction is provided, and the knowledge structures employed in the construction of the system are explained. A model of the apple scab disease cycle is incorporated into POMME to give the system a more fundamental reasoning capability than available from typical rule-based systems.