A Model for Assessing the Rating of Higher Education School Academic Staff Members Based on the Fuzzy Inference System

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F44555601%3A13440%2F22%3A43897027" target="_blank" >RIV/44555601:13440/22:43897027 - isvavai.cz</a>

Výsledek na webu

<a href="https://www.scopus.com/record/display.uri?eid=2-s2.0-85112640977&origin=resultslist&sort=plf-f" target="_blank" >https://www.scopus.com/record/display.uri?eid=2-s2.0-85112640977&origin=resultslist&sort=plf-f</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1007/978-3-030-82014-5_30" target="_blank" >10.1007/978-3-030-82014-5_30</a>

Jazyk výsledku

angličtina

Název v původním jazyce

A Model for Assessing the Rating of Higher Education School Academic Staff Members Based on the Fuzzy Inference System

Popis výsledku v původním jazyce

In this paper, we present the model of assessment of higher education school academic staff members rating based on the complex use of Harrington?s desirability function and a fuzzy inference system. Four main directions of activity were evaluated within the framework of the proposed model: pedagogical activity; science and research; organization activity and other activity types. Each of the proposed types of activities was assessed separately using the Harrington desirability function based on prior determined scores, where the general activity index of the appropriate score was calculated as the weighted average of the private desirability values. The Mamdani inference algorithm with triangular and trapezoidal membership functions was used within the framework of the fuzzy inference process implementation to evaluate the general rating score of the appropriate academic staff member. The base of rules was proposed to form the output for general rating scores calculated based on the individual rating scores. The output of the system was presented for each of the appropriate activity types separately and based on the assessment of the general rating score that contained the separate rating scores as the components. To our best mind, the proposed model can help us to optimize the functional possibilities of higher school system operation

Název v anglickém jazyce

A Model for Assessing the Rating of Higher Education School Academic Staff Members Based on the Fuzzy Inference System

Popis výsledku anglicky

In this paper, we present the model of assessment of higher education school academic staff members rating based on the complex use of Harrington?s desirability function and a fuzzy inference system. Four main directions of activity were evaluated within the framework of the proposed model: pedagogical activity; science and research; organization activity and other activity types. Each of the proposed types of activities was assessed separately using the Harrington desirability function based on prior determined scores, where the general activity index of the appropriate score was calculated as the weighted average of the private desirability values. The Mamdani inference algorithm with triangular and trapezoidal membership functions was used within the framework of the fuzzy inference process implementation to evaluate the general rating score of the appropriate academic staff member. The base of rules was proposed to form the output for general rating scores calculated based on the individual rating scores. The output of the system was presented for each of the appropriate activity types separately and based on the assessment of the general rating score that contained the separate rating scores as the components. To our best mind, the proposed model can help us to optimize the functional possibilities of higher school system operation

Druh

D - Stať ve sborníku

CEP obor

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OECD FORD obor

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Projekt

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Návaznosti

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Rok uplatnění

2022

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

Lecture Notes on Data Engineering and Communications Technologies

ISBN

978-3-030-82013-8

ISSN

—

e-ISSN

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Počet stran výsledku

15

Strana od-do

449-463

Název nakladatele

Springer Nature

Místo vydání

Basel

Místo konání akce

Kherson

Datum konání akce

24. 5. 2021

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

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