ارایه مدل طبقه بندی بر اساس سیستم استنتاج فازی و الگوریتم ژنتیک جهت تشخیص اختلال خواندن در دانش آموزان مقطع راهنمایی

نوع مقاله: مقاله پژوهشی

نویسندگان

1 کارشناسی ارشد، گروه مهندسی کامپیوتر، واحد شهرقدس، دانشگاه آزاد اسلامی، تهران، ایران

2 دکتری، گروه مهندسی کامپیوتر، واحد شهرقدس، دانشگاه آزاد اسلامی، تهران، ایران

3 دکتری، گروه مهندسی برق-الکترونیک، واحد شهرقدس، دانشگاه آزاد اسلامی،تهران، ایران

چکیده

اختلال یادگیری از اختلال‌های شایع دوران کودکی است. مهمترین اختلال یادگیری، اختلال خواندن که به مهارتهای مبتنی بر خواندن اشاره دارد. این پژوهش یک مدل هایبریدی فازی-ژنتیکی جهت مدیریت عدم قطعیت جهت تشخیص اختلال خواندن ارایه می‌نماید. بدین‌منظور از مدل‌های طبقه‌بندی در فرآیند تشخیص اختلال استفاده‌شده‌است. در سیستم فازی، دانش مورد نیاز جهت طراحی سیستم از گروهی از افراد خبره شامل معلمان و متخصصان استخراج می‌شود. سیستم فازی پیشنهادی با قابلیت مدیریت عدم‌قطعیت در دانش، از مدل یادگیری تکاملی الگوریتم ژنتیک استفاده‌می‌کند. جامعه آماری، شامل 260 دانش‌آموزان دختر دبیرستان دوره اول متوسطه مدرسه غیردولتی معرفت واقع در استان البرز در سال تحصیلی 95-94 است. به منظور ارزیابی کارایی سیستم از تحلیل منحنی ROC استفاده‌شده‌است. نتایج نشان می‌دهد که کارایی مدل طبقه‌بندی فازی بعد از یادگیری قوانین توسط الگوریتم ژنتیک به %51/98 افزایش‌یافته‌است. سیستم طبقه بندی فازی پیشنهادی قادر به تشخیص صحیح اختلال خواندن با درجه اطمینان بالا است و جهت مدیریت نایقینی در تشخیص اختلال خواندن و بهبود وضعیت تحصیلی دانش آموزان می تواند موثر‌واقع‌شود.

چکیده تصویری

ارایه مدل طبقه بندی بر اساس سیستم استنتاج فازی و الگوریتم ژنتیک جهت تشخیص اختلال خواندن در دانش آموزان مقطع راهنمایی

کلیدواژه‌ها

موضوعات


عنوان مقاله [English]

A New Classification Model Fuzzy-Genetic Algorithm for Detection of learning disability of Dyslexia in Secondary School Students

نویسندگان [English]

  • Fahimeh Rezaee 1
  • Rahil Hosseini 2
  • Mahdi Mazinani 3
1 Department of Artificial Intelligence, Shahr-e-Qods Branch, Islamic Azad University, Tehran, Iran
2 Department of Computer Engineering, Shahr-e-Qods Branch, Islamic Azad University, Tehran, Iran
3 Department of Electrical Engineering, Shahr-e-Qods Branch, Islamic Azad University, Tehran, Iran
چکیده [English]

Learning disability is very common in childhood. The most important disability is reading disorder which is related to reading skills. This research represents a hybrid scoring model using genetic algorithm and fuzzy set theory to manage uncertainty in diagnosis of reading disability. For this, fuzzy classification models were applied for diagnosis of the reading disability. In the fuzzy system, the knowledge was extracted from a group of experts who were teachers and specialists. In the proposed model, the knowledge of experts was automatically extracted using the learning process of the Genetic algorithm. A dataset of 260 girl students was collected from the Marefat High school in the Alborz province in the years of 1394 and 1395. The performance of the proposed model was investigated using the ROC curve analysis. The results show efficiency of the fuzzy classification model was increased to 98.51% after the rule learning with the Genetic algorithm. The proposed fuzzy classifier models uncertainty in the knowledge of expert to improve students’ progress.

کلیدواژه‌ها [English]

  • Dyslexia
  • Fuzzy Modeling
  • Classification
  • Genetic Algorithm
  • Modelling Uncertainty

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