کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
4508641 | 1321619 | 2008 | 6 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Pattern Extraction from Human Preference Reasoning Using Conditional Probability Co-occurrences Matrix of Texture Analysis
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کلمات کلیدی
موضوعات مرتبط
علوم زیستی و بیوفناوری
علوم کشاورزی و بیولوژیک
علوم زراعت و اصلاح نباتات
پیش نمایش صفحه اول مقاله
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چکیده انگلیسی
A new approach is proposed for extraction of features from human preferences reasoning. Conditional Probability Table (CPT) is a mentality representation to control the reasoning in Bayesian Belief Network (BBN). A software tool was developed using texture analysis with a co-occurrences matrix algorithm. As a case study, it was tested on BBN of moss (Rhacomitrium canescens) produce preferences. The result successfully represented features extracted as specific patterns. It is applicable as a new computational method for reducing many concrete parameters (Dimensionality) and extracting the information from CPT in five textural features. These features are essential as abstractive parameters for designing customized agro-industrial production to provide every consumer with a produce that matches his or her unique preferences.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Engineering in Agriculture, Environment and Food - Volume 1, Issue 2, 2008, Pages 45-50
Journal: Engineering in Agriculture, Environment and Food - Volume 1, Issue 2, 2008, Pages 45-50
نویسندگان
Mirwan Ushada, Haruhiko Murase,