APA 6th Edition Bonato, J., Mrak, Z. i Badurina, M. (2015). Speed regulation in fan rotation using fuzzy inference system. Pomorstvo, 29 (1), 58-63. Preuzeto s https://hrcak.srce.hr/140236
MLA 8th Edition Bonato, Jasminka, et al. "Speed regulation in fan rotation using fuzzy inference system." Pomorstvo, vol. 29, br. 1, 2015, str. 58-63. https://hrcak.srce.hr/140236. Citirano 17.02.2020.
Chicago 17th Edition Bonato, Jasminka, Zoran Mrak i Martina Badurina. "Speed regulation in fan rotation using fuzzy inference system." Pomorstvo 29, br. 1 (2015): 58-63. https://hrcak.srce.hr/140236
Harvard Bonato, J., Mrak, Z., i Badurina, M. (2015). 'Speed regulation in fan rotation using fuzzy inference system', Pomorstvo, 29(1), str. 58-63. Preuzeto s: https://hrcak.srce.hr/140236 (Datum pristupa: 17.02.2020.)
Vancouver Bonato J, Mrak Z, Badurina M. Speed regulation in fan rotation using fuzzy inference system. Pomorstvo [Internet]. 2015 [pristupljeno 17.02.2020.];29(1):58-63. Dostupno na: https://hrcak.srce.hr/140236
IEEE J. Bonato, Z. Mrak i M. Badurina, "Speed regulation in fan rotation using fuzzy inference system", Pomorstvo, vol.29, br. 1, str. 58-63, 2015. [Online]. Dostupno na: https://hrcak.srce.hr/140236. [Citirano: 17.02.2020.]
Sažetak Fuzzy logic, being one of the methods of artificial intelligence, converts human way of thinking into an algorithm, using certain mathematical methods. Logic based on a fuzzy set is polyvalent, each statement is associated with a degree of authenticity – the value of membership function. Fuzzy logic is used in cases in which knowledge is mostly experiential and expressed through words. This work presents the application of fuzzy logic in fan speed regulation. The main goal of this work was establishing an expert system that would incorporate the aforementioned method of artificial intelligence into inference mechanism. The advantages of fuzzy logic are: wide use and flexibility, tolerance to data imprecision, applicability in classic control problems and its linguistic variables based approach.
The assumption is the following: collecting of a large number of input and output data sets of greater quality which are necessary for deduction mechanism of fuzzy logic, will enlarge the possibilities of further researches and application of fuzzy logic.