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- 저자 : B. B. Orazbayev (검색결과 2 건)
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Control of Fuzzy Technological Objects Based on Mathematical Models
Y.A. Ospanov,B.B. Orazbayev,K.N. Orazbayeva,T. Gancarczyk,A.K. Shaikhanova 제어로봇시스템학회 2016 제어로봇시스템학회 국제학술대회 논문집 Vol.2016 No.10
This paper proposes methods for the development of mathematical models and for the control of operation modes of technological objects in oil refinery in face of uncertainty based on fuzzy information. The mathematical formulation of the problem of decision-making on controlling modes, which are solved on the basis of mathematical modeling, is formalized and obtained. By using the example of the problem of decision-making on optimal operation modes of technological complex for the benzene production and based on the methods of fuzzy mathematics an algorithm of its solution is developed. The initial problem is formalized as a problem of decision-making in the fuzzy environment, since the investigated object is characterized by multicriteriality and frequently functions in a fuzzy environment. The mathematical formulation of the problem of object’s mode selection in the fuzzy environment and the heuristic algorithm of its solution is obtained by modifying various optimality principles based on methods of the fuzzy sets theory.
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Development and Analysis of Models for Assessing Predicted Mean Vote Using Intelligent Technologies
L. Zh. Sansyzbay,B. B. Orazbayev,W. Wojcik 한국지능시스템학회 2020 INTERNATIONAL JOURNAL of FUZZY LOGIC and INTELLIGE Vol.20 No.4
One of the approaches toward determining the degree of microclimate comfort is measuring its individual components: temperature, air velocity, relative humidity, and air quality. A significant disadvantage of this approach is the neglect of the mutual influence of microclimate parameters on each other. To improve the accuracy of determining microclimate comfort, it is necessary to use a complex predicted mean vote (PMV) indicator. The PMV equation is complex and computationally consuming; simplified solutions can be obtained using Fanger’s diagrams, Excel calculation programs, and specialized computer applications. With the development of technology, intelligent microclimate systems are gaining popularity. In this article, for selecting one of the most effective intelligent technologies, models have been developed for assessing the PMV indicator using the frameworks of fuzzy logic and neural networks. The data obtained using the calculation program of the researchers of the Federal State Unitary Enterprise Research Institute (Russia) were used as input parameters for the models’ development. The program’s performance was validated against the PMV parameter values in the ISO 7730:2005 standard, and a good agreement was found. The PMV index values produced by the considered models were compared to the values calculated using the program, to determine the operability and efficiency of the developed models. Our analysis suggests that neural networks perform better on the assessment of thermal comfort, compared with fuzzy systems.
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