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APPLICATION OF GENETIC-BASED FUZZY INFERENCE TO FUZZY CONTROL
Park, Daihee,Kandel, Abraham,Langholz, Gideon Korean Institute of Intelligent Systems 1992 한국지능시스템학회논문지 Vol.2 No.2
The successful application of fuzzy reasoning models to fuzzy control systems depends on a number of parameters, such as fuzzy membership functions, that are usually decided upon subjectively. It is shown ill this paper that the performance of fuzzy control systems call be improved if the fuzzy reasoning model is supplemented by a genetic-based learning mechanism. The genetic algorithm enables us to generate all optimal set of parameters for the fuzzy reasoning model based either on their initial subjective selection or on a random selection. It is shown that if knowledge of the domain is available, it is exploited by the genetic algorithm leading to an even better performance of the fuzzy controller.
Waritthitham, A.,Lambertz, C.,Langholz, H.-J.,Wicke, M.,Gauly, M. Asian Australasian Association of Animal Productio 2010 Animal Bioscience Vol.23 No.5
Muscle fiber characteristics and their relationship to water-holding capacity of longissimus dorsi (ld) muscle were studied in Brahman (BRA) and Charolais (CHA) crossbred bulls fattened under practical farm conditions. Thirty-four BRA and 34 CHA bulls were randomly selected and slaughtered at 500, 550 and 600 kg live weight. Parameters of water-holding capacity such as drip, ageing, thawing, cooking and grilling loss were determined. Muscle fiber characteristics were conducted for muscle fiber type percentage and cross-sectional areas of slow- and fast-twitch fiber types, and correlation coefficients to water-holding capacity parameters were calculated. Results showed that CHA meat had a better water-holding capacity (less ageing, thawing and grilling loss) when compared with BRA, whereas slaughter weights had no significant effects on these parameters. Furthermore, there were no significant differences between genotypes and slaughter weights in muscle fiber type percentage and cross-sectional areas of ld muscle. Slow- and fast-twitch fiber types of all experimental groups averaged 24.4 and 75.6%, respectively. Cross-sectional areas of fast-twitch fibers had almost twice the size of slow-twitch fibers (6,721 and 3,713 ${\mu}m^2$, respectively). The correlation between muscle fiber area and water-holding capacity indicated that muscles with larger fiber areas had a lower drip and ageing loss but a higher cooking and grilling loss.