基于模糊逻辑的智能Agent情感建模

Modeling Emotions for the Intelligent Agent Based on Fuzzy Logic

李太华[1] 马燕[2] 邱玉辉[1]

情感是人类智能中的一个重要表现形式，在人类决策过程中起着重要的作用。认知科学、生理学以及人工智能领域的研究者已提出各类情感模型，但大部分模型都集中于智能agent的反应行为，为此它们通常是根据一些静态的规则或者事先确定的领域知识来生成agent的情感。本文提出了一个新的情感计算模型，并尝试利用模糊逻辑的表征方法建立事件和情感状态间的联系。[著者文摘]

Emotion is an important aspect of human intelligence and has been shown to play a significant role in the human decision making process. Researchers in areas such as cognitive science, physiology, and artificial intelligence have proposed a variety of models of emotions. Most of the previous models focus on an agent＇s reactive behavior, for which they often generate emotions according to static rules or pre-deterrnined domain knowledge. In this paper,we propose a new computational model of emotions that uses a fuzzy logic representation to map events and observations to emotional states.[著者文摘]

动态模糊逻辑程序设计语言探讨

Research on Dynamic Fuzzy Logic Programming Language

赵小芳 王玉玲

动态模糊问题是普遍存在的，但是现存的程序设计语言中适合解决动态模糊问题的极少，本文试图作这方面的研究，设计一种适合解决动态模糊性问题的程序设计语言。本文仿照监督命令的程序结构，给出动态模糊逻辑程序设计语言的一个抽象模型，其内容包括：动态模糊逻辑程序设计语言的抽象语法、动态模糊语义。[著者文摘]

Dynamic fuzzy problems exist extensively. But there is few programming language to solve dynamic fuzzy problems. This paper attempts to design a programming language which can cope with dynamic fuzzy problems, Following the guarded commands, an abstract model of dynamic fuzzy logic programming language is given, which includes the syntax and dynamic fuzzy semantics.[著者文摘]

基于人工智能方法的图像语义检索

Semantic Image Retrieval Based on Artificial Intelligence

王宇娇

根据语义特征进行图像检索是图像检索技术的发展趋势。文章提出了一种基于人工智能以实现图像语义特征提取的方法,即通过模糊逻辑、遗传算法和人工神经网络三者的融合来解决图像语义特征提取这一难题,该方法使图像检索能够满足用户的需求,提高了图像检索的效率和精度。[著者文摘]

To retrieve image in line with semantic feature is the general trend of image retrieval technology. This paper is introduced a new way of semantic feature retrieval based on artificial intelligence .The heart of the feature retrieval can be solved through the integrated use of fuzzy logic,artificial neural network and genetic algorithms. This new way is increased efficiency and precision of image retrieval.[著者文摘]

人工智能技术在电能质量分析中的应用

刘晓芳 刘会金 陈允平

电能质量和人工智能技术都是目前国际电工领域研究的热点，如何将人工智能技术应用于电能质量问题的分析和诊断更是电能质量研究中的重点问题。本文初步介绍了人工智能的主要分支：专家系统、神经网络、模糊逻辑和遗传算法的基本概念及其在电能质量中的独特应用，并对未来的发展趋势做出了展望。

基于模糊逻辑和神经网络的电力负荷预测

ANN and Fuzzy Logic Based Short-term Load Forecasting

王楠[1] 刘晨光[2] 马立肖[1] 赵占芳[1]

设计并实现了神经网络和模糊逻辑相结合的综合预测模型进行短期电力负荷预测。由神经网络和模糊逻辑分别对基本负荷和受天气、节假日影响的负荷进行预测,使其在天气突变等情况下也能达到较高的预测精度。采用此模型对石家庄电力系统负荷进行预测分析,取得了令人满意的结果。[著者文摘]

A hybrid model for short-term load forecasting that integrates artificial neural networks （ANN） and fuzzy expert systems is presented in this paper. ANN and fuzzy logic are separately used to forecast the normal load and the load influenced by temperature and holidays, to improve the forecast precision in those cases. In the test forecasting of Shijiazhuang power system, the proposed model provided good forecasting accuracy.[著者文摘]

基于GIS、模糊逻辑和专家知识的土壤制图及其在中国应用前景

PREDICTIVE SOIL MAPPING BASED ON A GIS, EXPERT KNOWLEDGE, AND FUZZY LOGIC FRAMEWORK AND ITS APPLICATION PROSPECTS IN CHINA

朱阿兴[1,2] 李宝林[1] 杨琳[1] 裴韬[1] 秦承志[1] 张甘霖[3] 蔡强国[1] 周成虎[1]

详细的土壤空间与属性的信息已成为环境模型和土地管理的基本参数，传统的以类别多边形和手工编制为基础的传统土壤制图效率低精度也较差。本文基于GIS、模糊逻辑和专家知识，建立了土壤-环境推理模型（SoLIM），通过基于土壤-环境关系模型的土壤相似度模型与对该模型进行赋值的推理技术来编制土壤图，从而克服了传统土壤制图中的简化。通过两个小区的研究表明，与传统土壤制图相比，通过SoLIM得出的土壤信息在空间详细度和属性精确度都有较大的提高，也能够大量减少调查的时间和经费，从而大大提高土壤调查的效率。SoLIM方法在我国推广十分必要且具有一定的条件，但仍需要进一步完善。[著者文摘]

Detailed soil spatial and attribute information are now basic parameters for environmental modeling and land management applications. The accuracy and efficiency of conventional soil surveys, based on the polygon model and the manual mapping practice, are quite low. A geographical information system （GIS） and expert knowledge based-fuzzy soil inference scheme （soil-land inference model, SoLIM） was developed to overcome the problems faced by the conventional soil survey. The scheme consists of three major components： （i） a model employing a similarity representation of soils, （ii） a set of inference techniques for deriving similarity representation, and （iii） application of the similarity representation. According to case studies conducted in Wisconsin, U. S. A, SoLIM improves the accuracy and efficiency of soil survey. Soil type and properties maps based on SoLIM are better than these based on conventional techniques in term of both spatial detail and attribute accuracy. The accuracy of the soil series maps based on SoLIM is about 80% . Moreover, soil mapping by means of SoLIM is about ten times faster than by conventional ones and saves about 2/3 in cost. However, how the SoLIM works highly depends on the availability and quality of environmental data and the quality of soil, environmental relationship model for the study area. The Second Soil Survey in China was conducted 20 years ago. Recent intensive land use activities may have greatly impacted the soil conditions. It＇s quite necessary to update the soil data in China for agricultural purposes. The SoLIM framework can provide great assistance in updating soil resource inventory. At the same time, the availability of spatial data, spatial information processing technology and human resources related to GPS, GIS and RS also make it possible to apply the SoLIM approach in the Chinese soil survey. However, the degree of success of the SoLIM highly depends on the quality of knowledge on soil environmental relationships in the study area. The knowledg

人工智能技术在国内电厂中的应用研究

An Applicabie and Study on Artificial Intelligent Technology in Thermal Power Plants of China

孙竹梅 张丽香

介绍了专家系统、模糊逻辑、人工神经网络、遗传算法等人工智能技术的特点及其在国内火电厂中的应用现状，分析了它们之间交叉综合后所形成的混合智能技术，指出应用混合智能技术是当前一段时间实现复杂系统优化控制的重要途径。[著者文摘]

A systematic research is made based on the characteristics of general Artificial Intelligent techniques, including Expert System, Fuzzy Logic, Artificial Neural Network, Genetic Algorithms etc. According to the application of these intelligent techniques in Thermal Power Plants of China, it points out in the paper that applying hybrid intelligent techniques will be an important way to control and optimize complex systems in the recent future.

利用地理信息系统与知识推论模式分析崩坍地潜势

Integrate GIS and Knowledge Inference Model in Potential Landslide Hazards Mapping Analysis

林祥伟

人工智能技术适合处理复杂性较高的非线性地理问题,本研究整合地理信息系统、遗传演算、模糊逻辑与类神经网络,建立数据探索型态之知识库分析模式,同时设计新的GIS空间分析工具,让研究者得以具体应用在地理学的研究上,并适当地补强GIS在数据撷取与知识探索的不足.本研究让当前大多停留在理论探讨阶段的人工智能在地理学之应用研究,有了更具体的研究方法、可操作的研究工具、和更具说服力的研究案例,具体之成果包含：①整合人工智能中遗传演算与模糊逻辑的相关技术,建立GIS之空间分析架构;②在这个分析架构下,结合现有的商用GIS软件ArcView,发展人工智能空间信息分析师（Artificaial intelligent Spatial Information Analyst;ASIA）,方便领域专家的直接应用;③以实际崩坍潜势分析案例,证明前述空间分析架构之合理性与正确性.[著者文摘]

Artificial intelligence technology can easily cope with highly complicated and non-linear combined spatial and temporal issues. Therefore this dissertation integrated genetic algorithm, neural network, and fuzzy logic knowledge inference model to build new spatial analysis tools for Geographic Information System （GIS）. This new GIS tools can be readily applied in a practical and appropriate manner in spatial research to patch the gaps in GIS data mining and knowledge discovery functions. The specific achievement here including, firstly the integration of related artificial intelligent technologies to establish a conceptual spatial analysis framework. Secondly by using this framework into GIS software to develop an Artificial intelligent Spatial Information Analyst （ASIA） system which then is fully utilized in the existing GIS package so that it is convenient for the domain experts to work with it and apply it. And thirdly, the studies of potential landslide hazards mapping analysis provide geographical practical cases to prove the rationalization and justness of the conceptual spatial analysis framework.[著者文摘]

智能控制研究动态及展望

The Trends and Prospect of the Research on Intelligent Control

张春美[1] 石川[2] 郭红戈[1]

阐述了智能控制的研究动态及发展方向，提出将粗糙集理论应用于智能控制系统的设想。[著者文摘]

This paper expounds the trends and developing direction the research on intelligent control, and advances the assumption of applying rough set into intelligent control system.[著者文摘]

范例推理（CBR）在气象服务中的应用

Application of the Case-Based Reasoning in Meteorological Service

魏立涛[1] 郭树军[2]

利用基于范例推理的人工智能技术,通过对河北省历史上寒潮和降水天气的处理,建立了一个天气系统智能搜索引擎,改进了寒潮和降水天气过程的服务效果。[著者文摘]

In this reseaech a weather information searching approach,which was based on Case-Based Reasoning,one of artificial intelligence technology was established.This method can search the most useful cases from historical database with high effectiveness in terms of conditions such as influence area, start-time,rainfall degree and others.[著者文摘]