신경회로망을 이용한 퍼지 IF-THEN 규칙 정제 방법

طريقة تنقيح قواعد «إذا-فإن» الضبابية باستخدام الشبكات العصبية

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ID: 271915
1970
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Abstract
지식 획득 또는 추출은 인공지능 분야에서 전문가 시스템 개발의 장애로 여겨진다. 퍼지 IF-THEN 규칙들은 불확실한 지식의 가장 흔히 사용되는 표현 도구이며, 인공지능에 널리 적용된다. Training data의 불충분과 규칙추출 방법의 한계와 같은 불확실한 요인들 때문에, 데이터로부터 추출된 퍼지 IF-THEN 규칙들은 만족한 성능을 갖지 못한다. 이
يُعدّ اكتساب المعرفة أو استخراجها عقبةً في تطوير الأنظمة الخبيرة في مجال الذكاء الاصطناعي. وتُعدّ قواعد IF-THEN الضبابية أداة التمثيل الأكثر استخداماً للمعرفة غير المؤكدة، وتُطبّق على نطاق واسع في الذكاء الاصطناعي. وبسبب عوامل عدم اليقين، مثل عدم كفاية بيانات التدريب (Training data) ومحدودية طرائق استخراج القواعد، فإن قواعد IF-THEN الضبابية المستخرجة من البيانات لا تحقق أداءً مرضياً. هذا
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염찬욱1970한국정보기술학회논문지신경회로망을 Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors 염찬욱;최한수;
Journal 한국정보기술학회논문지
Year 1970
DOI
DOI not found
URL
https://doi.org/10.14801/jkiit.2019.17.8.21
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