Using intelligent methods in classification of safflower (Carthamus tinctorius L.)

سال انتشار: 1392
نوع سند: مقاله کنفرانسی
زبان: انگلیسی
مشاهده: 678

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شناسه ملی سند علمی:

TIAU01_764

تاریخ نمایه سازی: 14 شهریور 1393

چکیده مقاله:

The first step for optimal use of genetic resources in breeding programs is genetic diversity. In this study, 30 genetic diversity of Safflower (Carthamus tinctorius L.) using morphological traits were studied. Morphological traits are used to classify Safflower types. The purpose of classification is to determine what type of Safflower production is greatest in what regions and what relationship exists between morphological traits and performance. Classification usingmorphological traits of Safflower is complex and brings about non linear problems. In the such circumstances, better use of Intelligent methods. One of intelligent methods is pattern recognition. Because the number of sample size was not enough, Therefore an alternativemethod of sampling, sample size was increased from 180 samples to 1260 samples, so that there can be improved accuracy. Because the number of Morphological traits was many and Also, there was a correlation between them. So using principal component analysis(PCA) method, thenumber of Morphological traits was reduced from 15 traits to 10 traits. In Continue, intelligent algorithms such as Bayes methods and Artificial Neural Networks(ANN) methods were applied to the dataset and Respectively, of the system with accuracy answer 90.07% and 95.95% were received

نویسندگان

e Salehpour

Graduate Student of computer, Islamic Azad University, Shabestar Branch,Iran

a farzan

Assistant Professor of computer, Islamic Azad University, Shabestar Branch, Iran

a.r ahmadzadeh

Assistant Professor of Agriculture, Islamic Azad University, Shabestar Branch, Iran