Parallel Fuzzy Inference Method for Higher Order Takagi–Sugeno Systems

Yershov, Sergey; Ponomarenko, R.М.

doi:10.1007/s10559-018-0103-3

Cited by 3 publications

(2 citation statements)

References 9 publications

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“…The use of mathematical methods for selecting project executors relates mainly to fuzzy mathematics and fuzzy logical output [17]. The task of choosing partners for a virtual enterprise using fuzzy logic is described in study [18].…”

Section: Literature Review and Problem Statementmentioning

confidence: 99%

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Devising an individually oriented method for selection of scientific activity subjects for implementing scientific projects based on scientometric analysis

Kuchansky

Гладка

2021

EEJET

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The main factors influencing the choice of individual subjects of the scientific activity or potential partners and executors for scientific and educational projects were analyzed. The specific features of choosing project executors of different categories were indicated. The functional responsibilities of project participants in accordance with the project structure were described. The individually oriented method for choosing subjects of scientific activity as executors of scientific and educational projects was developed, taking into account the productivity of their scientific activities in the past and considering the structure of projects. To determine the merits of the subjects of scientific activity, which are included in the relevant scientific subject spaces, it is necessary to apply the procedure of their productivity assessment. In addition, it is necessary to predict a change in productivity in the future based on retrospective data for this subject. Next, it is required to solve the multi-criteria problem of the choice among the subjects of scientific activity who are quite productive in the opinion of the project manager. The use of the developed method reduces the subjective impact on making a decision regarding the choice of project executors. This is due to the fact that they are chosen by automated calculation of scientometric indicators of subjects, guided only by open sources of information. The individually oriented method for the selection of subjects of scientific activity was verified on the example of the formation of three applications of research projects. As a result, the average percentage of scientists who meet the requirements of project managers for each scientific subject space was about 46.55 %. The percentage of those involved in the project from those who were selected is about 24.07 %. The probability of cooperation is higher among those who have an average H-index.

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Section: Literature Review and Problem Statementmentioning

confidence: 99%

“…Paper [20] proposes a model for choosing a scientific partner based on multifactor decision-making with the construction of an interval-valued intuitionistic fuzzy set. However, in studies [17][18][19][20], the structure of the project is not taken into consideration when choosing partners.…”

Section: Literature Review and Problem Statementmentioning

confidence: 99%

Devising an individually oriented method for selection of scientific activity subjects for implementing scientific projects based on scientometric analysis

Kuchansky

Гладка

2021

EEJET

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Knowledge Testing System Base on Machine Learning and Fuzzy Systems

Ponomarenko

Bondarenko

2022

2022 International Conference on Smart Information Systems and Technologies (SIST)

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PWM Converter Based on Takagi-Sugeno Fuzzy Logic Inference for Internet of Things Systems

Ponomarenko¹,

Demchuk²

2022

Energy and automation

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The aim of the study is to apply fuzzy logic in IoT systems to estimate various environmental factors such as temperature, humidity, etc., and to convert them using the Takagi-Sugeno algorithm into a pulse-width modulation (PWM) signal to control motor speed, thermal power of heaters and other parameters in an energy efficient way. The paper explores the use of fuzzy data converters based on intelligent fuzzy inference systems in Internet of Things systems. An approach has been developed for converting fuzzified input parameters read from sensors in a PWM signal based on the Takagi-Sugeno fuzzy algorithm. Based on the proposed method, an IT-based smart fan was developed that supports a PWM signal. Therefore, the proposed fuzzy PWM converter method was used to simulate the operation of a fuzzy model using three parameters: temperature, relative humidity, and carbon dioxide (CO2) concentration in relation to the PWM signal. The proposed method demonstrates the ease of training a reasonable fan control system and enables efficient energy consumption.

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Parallel Fuzzy Inference Method for Higher Order Takagi–Sugeno Systems

Cited by 3 publications

References 9 publications

Devising an individually oriented method for selection of scientific activity subjects for implementing scientific projects based on scientometric analysis

Devising an individually oriented method for selection of scientific activity subjects for implementing scientific projects based on scientometric analysis

Knowledge Testing System Base on Machine Learning and Fuzzy Systems

PWM Converter Based on Takagi-Sugeno Fuzzy Logic Inference for Internet of Things Systems

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