基于MMDB的快速混合模型的研究与应用
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摘要
针对专家系统的知识获取及管理困难、推理效率不高、自学习不足等问题，对内存数据库(MMDB)关键技术、基于规则的知识表示及检索、规则匹配算法、神经网络的规则学习算法等方面进行深入的研究和分析，优化相应的算法及结构，提出一种基于内存数据库、专家系统及神经网络的快速混合智能模型，解决在工程控制、快速决策、电信、金融等领域中的时效要求高的智能应用的问题。
由于传统数据库不能满足时间关键型应用对数据处理的实效性的要求，随着内存容量不断的增大及价格的降低，作为实时数据库底层支持的内存数据库应用越来越广泛。针对其数据组织及管理，索引技术和并发控制等关键技术进行研究，提出一种优化的T树索引及其并发控制算法。通过实验表明，改进的算法提高T树及其并发的性能。
研究了基于规则的专家系统的体系结构，扩展的产生式知识表示方法，以及规则匹配算法，推理策略等方面。分析了三种推理的机制以及基于综合函数的冲突消解机制；研究了不确定性推理的技术，以及规则一致性维护的算法；分析了目前使用最广泛的规则匹配算法-RETE算法，介绍RETE快速匹配算法的核心思想及过程，提出了优化的RETE规则匹配算法，降低匹配过程的空间和时间的复杂度，增强推理效率。
研究并提出了一种以基于规则的专家系统为基础，结合内存数据库及神经网络的快速混合智能模型。分析了该模型的结构和原理，以及基于MMDB的混合知识表示法。而在规则匹配过程中，可以结合内存数据库的高效索引HASH和改进的T树等提高知识检索能力。利用BP神经网络对数据进行训练，然后通过剪枝，规则提取等步骤进行知识的学习以及利用决策树算法进行规则的学习，弥补了专家系统的自学习能力不足的问题。
以飞行器试验过程的状态评估为需求，针对飞行器的各类测量种类众多且关系复杂，基于快速混合智能模型，提出一种两阶段评估飞行任务的技术方案。证据获取阶段采用分布式证据获取技术，使得各分系统能够并行获取证据；评估推理阶段使用混合快速智能评估模型，汇集各种证据（遥测，轨道，图像等）推理得出评估结论。通过仿真数据测试表明，该系统可以满足即时评估的需求。
For the problems of difficulties with knowledge acquisition and management,reasoning not quickly and lacking of self-learning in expert system, in-depth analysisand researches for key technologies of Main Memory database (MMDB), rule-basedknowledge representation and retrieval, rule-matching algorithm, learning algorithmbased on artificial neural network. Moreover, the corresponding algorithms andstructures are optimized. A fast hybrid intelligent model based on MMDB, expertsystem and artificial neural networks is and proposed to solve the problem ofintelligence applications timeliness required in the fields of engineering controls, quickdecision-making telecommunications and financial.
Because traditional database can not meet the requirement of effectiveness of dataprocessing in time-critical applications and the memory have increased capacity andlower prices, MMDBs are more and more widely used as foundation of a real-timedatabase. An optimization T-Trees and concurrency control techniques of T-Trees areproposed. Data organization and management, index technologies and concurrencycontrol are analyzed. Some experiments are made to show the higher performance ofoptimized algorithms.
The architecture of a rule-based expert system, the knowledge representationmethods of expansion production, as well as rule matching algorithm and reasoningstrategies are studied. Three reasoning mechanisms and comprehensive function-basedconflict resolution mechanisms is analyzed. Uncertainty reasoning technology, as wellas the rules of consistency maintenance algorithm is studied. The most widely used rulematching algorithm-RETE algorithm is analyzed. The core idea and process of the fastmatching algorithm is introduced. An optimized RETE algorithm is proposed to reducethe space and time complexity of the matching process, enhanced the efficient ofreasoning.
Combined with the rule-based expert system, MMDB and artificial neuralnetworks, a fast hybrid intelligent model is proposed. The structure and principles of themodel and a hybrid knowledge representation are analyzed. Using the hash index andimproved T-tree index in MMDB to improve knowledge retrieval capabilities in processof rule matching. The BP network uses data to training and can be pruned. And then therule can be extracted from the network to make up for the lack of self-learning ability ofthe expert system.
Because there is much kind of data that have complex relationships, a two-stagemission assessment program based, the hybrid intelligent model is proposed to obtainthe status of the aircraft during the aircraft mission. In the evidence acquisition phase,the technology of distributed access to data is used, and then uses different models toobtain evidence. In reasoning stage, it brings a variety of evidence (telemetry, orbit,images, etc.) together and obtains conclusions of the assessment by reasoningcomprehensively with fast hybrid intelligent model. The result of the simulationexperimentation shows that: the system can fulfill the real-time assessment task.
由于传统数据库不能满足时间关键型应用对数据处理的实效性的要求，随着内存容量不断的增大及价格的降低，作为实时数据库底层支持的内存数据库应用越来越广泛。针对其数据组织及管理，索引技术和并发控制等关键技术进行研究，提出一种优化的T树索引及其并发控制算法。通过实验表明，改进的算法提高T树及其并发的性能。
研究了基于规则的专家系统的体系结构，扩展的产生式知识表示方法，以及规则匹配算法，推理策略等方面。分析了三种推理的机制以及基于综合函数的冲突消解机制；研究了不确定性推理的技术，以及规则一致性维护的算法；分析了目前使用最广泛的规则匹配算法-RETE算法，介绍RETE快速匹配算法的核心思想及过程，提出了优化的RETE规则匹配算法，降低匹配过程的空间和时间的复杂度，增强推理效率。
研究并提出了一种以基于规则的专家系统为基础，结合内存数据库及神经网络的快速混合智能模型。分析了该模型的结构和原理，以及基于MMDB的混合知识表示法。而在规则匹配过程中，可以结合内存数据库的高效索引HASH和改进的T树等提高知识检索能力。利用BP神经网络对数据进行训练，然后通过剪枝，规则提取等步骤进行知识的学习以及利用决策树算法进行规则的学习，弥补了专家系统的自学习能力不足的问题。
以飞行器试验过程的状态评估为需求，针对飞行器的各类测量种类众多且关系复杂，基于快速混合智能模型，提出一种两阶段评估飞行任务的技术方案。证据获取阶段采用分布式证据获取技术，使得各分系统能够并行获取证据；评估推理阶段使用混合快速智能评估模型，汇集各种证据（遥测，轨道，图像等）推理得出评估结论。通过仿真数据测试表明，该系统可以满足即时评估的需求。
For the problems of difficulties with knowledge acquisition and management,reasoning not quickly and lacking of self-learning in expert system, in-depth analysisand researches for key technologies of Main Memory database (MMDB), rule-basedknowledge representation and retrieval, rule-matching algorithm, learning algorithmbased on artificial neural network. Moreover, the corresponding algorithms andstructures are optimized. A fast hybrid intelligent model based on MMDB, expertsystem and artificial neural networks is and proposed to solve the problem ofintelligence applications timeliness required in the fields of engineering controls, quickdecision-making telecommunications and financial.
Because traditional database can not meet the requirement of effectiveness of dataprocessing in time-critical applications and the memory have increased capacity andlower prices, MMDBs are more and more widely used as foundation of a real-timedatabase. An optimization T-Trees and concurrency control techniques of T-Trees areproposed. Data organization and management, index technologies and concurrencycontrol are analyzed. Some experiments are made to show the higher performance ofoptimized algorithms.
The architecture of a rule-based expert system, the knowledge representationmethods of expansion production, as well as rule matching algorithm and reasoningstrategies are studied. Three reasoning mechanisms and comprehensive function-basedconflict resolution mechanisms is analyzed. Uncertainty reasoning technology, as wellas the rules of consistency maintenance algorithm is studied. The most widely used rulematching algorithm-RETE algorithm is analyzed. The core idea and process of the fastmatching algorithm is introduced. An optimized RETE algorithm is proposed to reducethe space and time complexity of the matching process, enhanced the efficient ofreasoning.
Combined with the rule-based expert system, MMDB and artificial neuralnetworks, a fast hybrid intelligent model is proposed. The structure and principles of themodel and a hybrid knowledge representation are analyzed. Using the hash index andimproved T-tree index in MMDB to improve knowledge retrieval capabilities in processof rule matching. The BP network uses data to training and can be pruned. And then therule can be extracted from the network to make up for the lack of self-learning ability ofthe expert system.
Because there is much kind of data that have complex relationships, a two-stagemission assessment program based, the hybrid intelligent model is proposed to obtainthe status of the aircraft during the aircraft mission. In the evidence acquisition phase,the technology of distributed access to data is used, and then uses different models toobtain evidence. In reasoning stage, it brings a variety of evidence (telemetry, orbit,images, etc.) together and obtains conclusions of the assessment by reasoningcomprehensively with fast hybrid intelligent model. The result of the simulationexperimentation shows that: the system can fulfill the real-time assessment task.
引文
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