Fundamentals of creating MIVAR expert systems

2021 ◽  
Author(s):  
Oleg Varlamov
Keyword(s):  
Artificial Intelligence ◽  
Decision Support ◽  
Expert System ◽  
Expert Systems ◽  
Decision Support Systems ◽  
Intelligent Systems ◽  
Autonomous Robots ◽  
Support Systems ◽  
Knowledge Bases ◽  
Computer Engineering

Methodological and applied issues of the basics of creating knowledge bases and expert systems of logical artificial intelligence are considered. The software package "MIV Expert Systems Designer" (KESMI) Wi!Mi RAZUMATOR" (version 2.1), which is a convenient tool for the development of intelligent information systems. Examples of creating mivar expert systems and several laboratory works are given. The reader, having studied this tutorial, will be able to independently create expert systems based on KESMI. The textbook in the field of training "Computer Science and Computer Engineering" is intended for students, bachelors, undergraduates, postgraduates studying artificial intelligence methods used in information processing and management systems, as well as for users and specialists who create mivar knowledge models, expert systems, automated control systems and decision support systems. Keywords: cybernetics, artificial intelligence, mivar, mivar networks, databases, data models, expert system, intelligent systems, multidimensional open epistemological active network, MOGAN, MIPRA, KESMI, Wi!Mi, Razumator, knowledge bases, knowledge graphs, knowledge networks, Big knowledge, products, logical inference, decision support systems, decision-making systems, autonomous robots, recommendation systems, universal knowledge tools, expert system designers, logical artificial intelligence.

Mivar databases and rules

2021 ◽  
Author(s):  
Oleg Varlamov
Keyword(s):  
Artificial Intelligence ◽  
Decision Support ◽  
Expert System ◽  
Expert Systems ◽  
Decision Support Systems ◽  
Support Systems ◽  
Knowledge Bases ◽  
Data Models ◽  
Active Network ◽  
New Model

The multidimensional open epistemological active network MOGAN is the basis for the transition to a qualitatively new level of creating logical artificial intelligence. Mivar databases and rules became the foundation for the creation of MOGAN. The results of the analysis and generalization of data representation structures of various data models are presented: from relational to "Entity — Relationship" (ER-model). On the basis of this generalization, a new model of data and rules is created: the mivar information space "Thing-Property-Relation". The logic-computational processing of data in this new model of data and rules is shown, which has linear computational complexity relative to the number of rules. MOGAN is a development of Rule - Based Systems and allows you to quickly and easily design algorithms and work with logical reasoning in the "If..., Then..." format. An example of creating a mivar expert system for solving problems in the model area "Geometry"is given. Mivar databases and rules can be used to model cause-and-effect relationships in different subject areas and to create knowledge bases of new-generation applied artificial intelligence systems and real-time mivar expert systems with the transition to"Big Knowledge". The textbook in the field of training "Computer Science and Computer Engineering" is intended for students, bachelors, undergraduates, postgraduates studying artificial intelligence methods used in information processing and management systems, as well as for users and specialists who create mivar knowledge models, expert systems, automated control systems and decision support systems. Keywords: cybernetics, artificial intelligence, mivar, mivar networks, databases, data models, expert system, intelligent systems, multidimensional open epistemological active network, MOGAN, MIPRA, KESMI, Wi!Mi, Razumator, knowledge bases, knowledge graphs, knowledge networks, Big knowledge, products, logical inference, decision support systems, decision-making systems, autonomous robots, recommendation systems, universal knowledge tools, expert system designers, logical artificial intelligence.

Expert Systems and Artificial Intelligence in Decision Support Systems.

1988 ◽  
Vol 37 (3) ◽  
pp. 348
Author(s):  
Paul Waller ◽  
H. G. Sol ◽  
C. A. T. Takkenberg ◽  
P. F. De Vries Robbe
Keyword(s):  
Artificial Intelligence ◽  
Decision Support ◽  
Expert Systems ◽  
Decision Support Systems ◽  
Support Systems

scholarly journals Analysis of the methods of automated control over multidimensional objects on the basis of intelligent systems

2018 ◽  
pp. 42-49
Author(s):  
L. Ya. Chуhur
Keyword(s):  
Information Technology ◽  
Decision Support ◽  
Expert Systems ◽  
Decision Support Systems ◽  
Intelligent Systems ◽  
Support Systems ◽  
Software Environment ◽  
Automated Control ◽  
Multidimensional Objects ◽  
Concept Of Information

The paper deals with the analysis of automated control over multidimensional objects based on the principles of intelligent systems. At present such systems include decision support systems and expert systems. The main feature of information technology of decision support is a qualitatively new method of organizing the interaction between a man and a computer. The development of solutions is the main purpose of this technology. The similarity of automated control methods based on information technology used in expert systems and decision support systems is that they both provide a high level of decision support. However, in practice, there are significant differences. One of them is that solving a problem in decision support systems reflects the level of its understanding by the user and his ability to get and understand the solution. Another one is in the ability of expert systems to explain this solution and to use the concept of information technology as knowledge. From the perspective of the above features of these systems, we have made a conclusion about the practicability of using expert systems, namely, dynamic, working in real time that allow to quickly and qualitatively carry out automated control in the production. They enable the expert to make the best decision, even if knowledge of the situation goes beyond his competence. An important role in the expert systems development is played by the software environment that is used during its implementation. The article also deals with the functioning and connection of the software product with the outside world - the object-oriented integrated environment G2, on the basis of which many modern expert systems are built. The areas of application of such intelligent systems are determined and some of the tasks that they are solving are outlined.

https://journals.vgtu.lt/index.php/MMA/article/download/9887/8590

2001 ◽  
Vol 6 (1) ◽  
pp. 97-105
Author(s):  
A. Kolesnikov ◽  
A. Yashin
Keyword(s):  
Artificial Intelligence ◽  
Decision Support ◽  
Decision Support Systems ◽  
Intelligent Systems ◽  
Support Systems ◽  
Hybrid Intelligent Systems ◽  
The World ◽  
Human Intellect ◽  
Modelling Approaches

The paper studies the basic problems of Artificial Intelligence, such as integration of difference attributes of human intellect. For this purpose we have been created synergetic systems that are hybrid intelligent systems (HYIS). The paper shows the world of decision support problems and the world of modelling approaches evolution. The term ‘heterogeneous problem’ for decision support systems is discussed. Two models of interaction between the problems world and the methods world also the results of HYIS creating are discussed. The formalism of HYIS is introduced.

The Role of Artificial Intelligence in Clinical Decision Support Systems and a Classification Framework

2018 ◽  
Vol 3 (2) ◽  
pp. 31-47 ◽  
Author(s):  
Steven Walczak
Keyword(s):  
Artificial Intelligence ◽  
Decision Making ◽  
Decision Support ◽  
Decision Support Systems ◽  
Clinical Decision Support ◽  
Intelligent Systems ◽  
Clinical Decision Making ◽  
Support Systems ◽  
Clinical Decision Support Systems ◽  
Clinical Decision

Clinical decision support systems are meant to improve the quality of decision-making in healthcare. Artificial intelligence is the science of creating intelligent systems that solve complex problems at the level of or better than human experts. Combining artificial intelligence methods into clinical decision support will enable the utilization of large quantities of data to produce relevant decision-making information to practitioners. This article examines various artificial intelligence methodologies and shows how they may be incorporated into clinical decision-making systems. A framework for describing artificial intelligence applications in clinical decision support systems is presented.

scholarly journals HYBRID MODELLING IN STRATIFIED DECISION SUPPORT SYSTEMS. I

2000 ◽  
Vol 5 (1) ◽  
pp. 108-118
Author(s):  
A. Kolesnikov ◽  
A. Yashin
Keyword(s):  
Artificial Intelligence ◽  
Decision Support ◽  
Decision Support Systems ◽  
Intelligent Systems ◽  
Support Systems ◽  
Hybrid Modelling ◽  
Hybrid Intelligent Systems ◽  
The World ◽  
Human Intellect ◽  
Modelling Approaches

The paper studies the basic problems of Artificial Intelligence, such as integration of difference attributes of human intellect. For this purpose we have been created synergetic systems that are hybrid intelligent systems (HYIS). The paper shows the world of decision support problems and the world of modelling approaches evolution. The term ‘heterogeneous problem’ for decision support systems is discussed. Two models of interaction between the problems world and the methods world also the results of HYIS creating are discussed. The formalism of HYIS is introduced.

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