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In this paper a mapped-template logic-based parallel optoelectronic processor is proposed for expert systems in order to achieve high speed and high performance for massively parallel processing of rule-based systems. The proposed system is implemented using two-dimensional space optics symbolic correlator. Also in this paper, an optoelectronic system for a parallel inference engine is presented....
In this paper we perform the analysis of Dempster-Shafer temporalized structure for the construction of more precise decisions based on the expert knowledge valuations. The relation of information precision is defined on the bodies of evidence. Negative inaccuracy is defined as the stream of rational expert knowledge in Dempster-Shafer temporalized structure. The principle of negative inaccuracy is...
Fuzzy rule is the core of fuzzy expert system, which use relational database methods knowledge to build knowledge base, the combination of database and knowledge base is the development trend of the knowledge base. This paper describes the fuzzy rules first, including fuzzy logic, fuzzy production rules, multi-dimensional fuzzy rules; and studies the fuzzy rule representation, including the general...
This paper proposes a novel multiagent system for complex system modeling based on a dynamic fuzzy cognitive map approach. It aims to represent the domain knowledge and carry out the inference process regarding the uncertainty, distribution and dynamism that exist in most of real world problems. The proposed multiagent system architecture is able to model dynamic real world problems that almost contain...
This article re-visits the foundation concepts of Computational Intelligence in relation to the established field of Artificial Intelligence and describes an emerging data technology, Formal Concept Analysis, that can contribute to the topic. Technologies from Artificial Intelligence are briefly considered in relation to the need for improved knowledge representation and accessibility rather than...
The expert system technique is applied for the design synthesis of permanent magnet synchronous motor. The new frame of rule skeleton and rule body is adopted for the knowledge representation that pays equal attention to the symbol reasoning and numerical calculation. The forward inference network is built up on the base of the rule skeleton for the redesign, and the detailed design contents are set...
The problem of integrating multiple-source uncertain information is crucial in many applications. In this paper, we propose an integration method of multiple Qualitative Probabilistic Networks (QPNs). Assuming that each QPN has the same nodes, we integrate the qualitative signs and structure of multiple QPNs based on probabilistic rough sets. Specifically, we first take the probabilistic-rough-set-based...
The following topics are dealt with: Web services; multi-agent system; natural language processing; knowledge discovery; data mining; robotics; evolutionary computation; computer vision; scheduling; planning; ontology; information retrieval; knowledge representation; reasoning; software security; data warehouse; grid computing; and image processing.
Metareasoning is defined as the application of reasoning techniques to the process of reasoning itself. As such, it is not immediately concerned with the particular domain of an application, but with the decision processes and knowledge representations that provide the application functionality. A primary reason to perform metareasoning is the desire to reflect on the application's performance and...
Edwards-Venn Diagrams (EVD) were introduced to facilitate knowledge representation and reasoning in connectionistic approach for modeling industrial systems. Semantic descriptions are seen helpful in solving the challenges of mass customization due to capability to capture knowledge interpretable both for humans and machines. However modern knowledge technologies could not provide required flexibility...
In the paper the study of knowledge hierarchical representation for automated reasoning is presented. The hierarchical knowledge representation is proposed for predictive modeling purpose. It is improved an effective automated reasoning structure for data set analyzes and making decisions based on complex relations between this data. It is important to emphasize that it is not considered a - priori...
Intelligent Systems require the ability to reason with incomplete information, because in the real world complete information is hard to obtain, even in the most controlled situation. In recent years, many formalisms have been proposed tacking the matter of uncertain, incomplete in logic programs and databases. However, qualitative models and qualitative reasoning have been around in Artificial Intelligence...
N this paper, we analyze the causal influence between variables and the transference of causal influence in fuzzy cognitive map with the related knowledge of graph theory. The algorithm of basic causal chain is proposed. Finally, an illustrative example is provided, and its results suggest that the method is very effective.
Qualitative probabilistic networks(QPNs) have been designed for probabilistic reasoning in a qualitative way. As a consequence of their coarse level of representation detail, qualitative probabilistic networks do not provide for resolving trade-offs and typically yield ambiguous results upon inference, especially in large complicated networks, we propose an algorithm for computing more informative...
An object-oriented implementation of an original model of knowledge representation scheme is described in the paper. The model is based on the high-level Fuzzy Petri nets and supports three forms of reasoning: inheritance, recognition and intersection search. The model is suitable for knowledge base and inference machine design in intelligent systems for real-world tasks that deal with fuzzy, vague,...
A fuzzy spatial Petri nets (FSPN) was proposed in order to describe spatial fuzzy knowledge and spatial associated effect between places and transitions. By introducing spatial associated factor, fuzzy Petri nets combined with spatial location was researched in depth to solve uncertainty factor associated with environment area and execute dynamic reasoning. Structure and signification of State associated...
Knowledge mobilisation is a transition from the prevailing knowledge management technology to a new methodology and some innovative methods for knowledge representation, formation and development and for knowledge retrieval and distribution. We show that fuzzy ontology will be useful to represent real world knowledge and that approximate reasoning schemes can give us answers which are sufficiently...
In this paper we address the problem of modeling creativity in Artificial Intelligence using a Genetic or Evolutionary based approach to computing, where the universe of discourse is represented as theories or programs in an extension to the Logic Programming language, which makes possible to handle incomplete or even contradictory information in an evolutionary environment. Indeed, we present a new...
A well constructed ontology plays a crucial role in knowledge description, knowledge query and knowledge reasoning. However the inevitable issue in ontology construction is that ontologies which are developed by different creators are inconsistent. This paper firstly analyzes four reasons why the inconsistencies occur. Then based on the reasons we propose a methodology for ontology construction to...
The essential abilities of text knowledge representation, such as automatic construction, carrying abundant semantics and flexible reasoning, should be held due to the rapid growth of web resources and the requirements of the reasoning-based web services. However, current text knowledge representation models either lose many textual semantics or cannot be constructed automatically. To solve the above...
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