A Novel Approach for Automatic Detection of Concrete Surface Voids Using Image Texture Analysis and History-Based Adaptive Differential Evolution Optimized Support Vector Machine
المؤلفون المشاركون
Nguyen, Quoc-Lam
Hoang, Nhat-Duc
المصدر
العدد
المجلد 2020، العدد 2020 (31 ديسمبر/كانون الأول 2020)، ص ص. 1-15، 15ص.
الناشر
Hindawi Publishing Corporation
تاريخ النشر
2020-07-28
دولة النشر
مصر
عدد الصفحات
15
التخصصات الرئيسية
الملخص EN
To inspect the quality of concrete structures, surface voids or bugholes existing on a concrete surface after the casting process needs to be detected.
To improve the productivity of the inspection work, this study develops a hybrid intelligence approach that combines image texture analysis, machine learning, and metaheuristic optimization.
Image texture computations employ the Gabor filter and gray-level run lengths to characterize the condition of a concrete surface.
Based on features of image texture, Support Vector Machines (SVM) establish a decision boundary that separates collected image samples into two categories of no surface void (negative class) and surface void (positive class).
Furthermore, to assist the SVM model training phase, the state-of-the-art history-based adaptive differential evolution with linear population size reduction (L-SHADE) is utilized.
The hybrid intelligence approach, named as L-SHADE-SVM-SVD, has been developed and complied in Visual C#.NET framework.
Experiments with 1000 image samples show that the L-SHADE-SVM-SVD can obtain a high prediction accuracy of roughly 93%.
Therefore, the newly developed model can be a promising alternative for construction inspectors in concrete quality assessment.
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
Hoang, Nhat-Duc& Nguyen, Quoc-Lam. 2020. A Novel Approach for Automatic Detection of Concrete Surface Voids Using Image Texture Analysis and History-Based Adaptive Differential Evolution Optimized Support Vector Machine. Advances in Civil Engineering،Vol. 2020, no. 2020, pp.1-15.
https://search.emarefa.net/detail/BIM-1121552
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
Hoang, Nhat-Duc& Nguyen, Quoc-Lam. A Novel Approach for Automatic Detection of Concrete Surface Voids Using Image Texture Analysis and History-Based Adaptive Differential Evolution Optimized Support Vector Machine. Advances in Civil Engineering No. 2020 (2020), pp.1-15.
https://search.emarefa.net/detail/BIM-1121552
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
Hoang, Nhat-Duc& Nguyen, Quoc-Lam. A Novel Approach for Automatic Detection of Concrete Surface Voids Using Image Texture Analysis and History-Based Adaptive Differential Evolution Optimized Support Vector Machine. Advances in Civil Engineering. 2020. Vol. 2020, no. 2020, pp.1-15.
https://search.emarefa.net/detail/BIM-1121552
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references
رقم السجل
BIM-1121552
قاعدة معامل التأثير والاستشهادات المرجعية العربي "ارسيف Arcif"
أضخم قاعدة بيانات عربية للاستشهادات المرجعية للمجلات العلمية المحكمة الصادرة في العالم العربي
تقوم هذه الخدمة بالتحقق من التشابه أو الانتحال في الأبحاث والمقالات العلمية والأطروحات الجامعية والكتب والأبحاث باللغة العربية، وتحديد درجة التشابه أو أصالة الأعمال البحثية وحماية ملكيتها الفكرية. تعرف اكثر