Neuro-Fuzzy Supervised Training Algorithm for Varied Chicken Disease Recognition
DOI:
https://doi.org/10.14738/jbemi.16.762Keywords:
chicken disease, Fuzzy set, Fuzzy Logic, Algorithm, Supervised-Neural-NetworkAbstract
Poultry farming is an integral part of human existence. It link or interlink most, if not all of human endeavours which provides food in terms of meat and other proteins ingredients for human consumption and existence. Diseases on the other hand, are usually a resultant of human interaction with the ecosystem which has affected poultry farming for centuries. Most of the approaches applied in chicken disease recognition is subjective (based on the experiences, skills, exposure and talents of a personnel) in nature at best. Fuzzy Supervised Neural Network Training Algorithm has been designed and implemented with Matrix Laboratory (MATLAB) and Hypertext Pre-processor as the simulation tools and language respectively. This paper demonstrates the practical application of algorithm techniques in medicalReferences
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