Development of Neuro Fuzzy Based Temperature Control for Egg Hatchery

Neuro fuzzy have been successfully applied to extract knowledge from data in the form of fuzzy rules. This project describes the development of Adaptive Neuro fuzzy system applied to the temperature variable of a thermal system with a range of 35 to 40°C for Egg Hatchery control. The system developed was based on heat transfer based on the principle of radiation to actualize the system. The generation of membership function is a challenging problem for fuzzy systems and the response of fuzzy systems depends mainly on the membership functions. The ANFIS based input output model is used to tune the membership functions in neuro fuzzy system. Experimental results were determiner. Processing the membership function the ANFIS was trained, tested and validated. The neuro fuzzy controller used the neural network learning techniques to tune the membership functions while keeping the semantics of the fuzzy logic controller intact. Both the architecture and the learning algorithm are presented for a general neuro fuzzy controller. In conclusion, a resulting effective system temperature control with energy conservation up to 100 eggs was achieved. The developed system finds application in egg incubation system industry. Elisha Adeleke Joseph | Henry Sunday Okeke | Michael A. Taiwo "Development of Neuro-Fuzzy Based Temperature Control for Egg Hatchery" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-5 | Issue-4 , June 2021, URL: https://www.ijtsrd.compapers/ijtsrd41215.pdf Paper URL: https://www.ijtsrd.comengineering/electrical-engineering/41215/development-of-neurofuzzy-based-temperature-control-for-egg-hatchery/elisha-adeleke-joseph