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  • 标题:A Hybrid Intelligent System for Fruit Grading and Sorting
  • 本地全文:下载
  • 作者:Jasmeen Gill ; Akshay Girdhar ; Tejwant Singh
  • 期刊名称:International Journal on Computer Science and Engineering
  • 印刷版ISSN:2229-5631
  • 电子版ISSN:0975-3397
  • 出版年度:2017
  • 卷号:9
  • 期号:05
  • 页码:257-265
  • 出版社:Engg Journals Publications
  • 摘要:Agriculture and food industry are the backbone of any country. Fruit industry is the prime contributor in agricultural sector. Thus, automation of fruit 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 fruit 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.
  • 关键词:Fruit grading and sorting; artificial neural networks; Genetic algorithms; Hybrid intelligent system; Pattern recognition
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