Open AccessVegetable Grading and Sorting using Artificial Intelligence
Author(s) -
Omer Farooq,
Jasmeen Gill
Publication year - 2022
Publication title -
international journal for research in applied science and engineering technology
Language(s) - English
Resource type - Journals
ISSN - 2321-9653
DOI - 10.22214/ijraset.2022.40407
Subject(s) - artificial neural network , artificial intelligence , computer science , sorting , automation , particle swarm optimization , genetic algorithm , machine learning , pattern recognition (psychology) , engineering , algorithm , mechanical engineering
Abstract: Agriculture and food industry are the backbone of any country. Food industry is the prime contributor in agricultural sector. Thus, automation of vegetable grading and sorting is the need of the hour. Since, artificial neural networks are best suited for automated pattern recognition problems; they are used as a classification tool for this research. Back propagation is the most important algorithm for training neural networks. But, it easily gets trapped in local minima leading to inaccurate solutions. Therefore, some global search and optimization techniques were required to hybridize with artificial neural networks. One such technique is Genetic algorithms that imitate the principle of natural evolution. So, in this article, a hybrid intelligent system is proposed for vegetable grading and sorting in which artificial neural networks are merged with genetic algorithms. Results show that proposed hybrid model outperformed the existing back propagation based system. Keywords: Vegetable grading and sorting; artificial neural networks; Particle Swarm Optimization; Hybrid intelligent system; Pattern recognition