Predicting Compressive Strength of Concrete Using Histogram-Based Gradient Boosting Approach for Rapid Design of Mixtures
Message:
Article Type:
Research/Original Article (دارای رتبه معتبر)
Abstract:
Applications of machine learning techniques in concrete properties' prediction have great interest to many researchers worldwide. Indeed, some of the most common machine learning methods are those based on adopting boosting algorithms. A new approach, histogram-based gradient boosting, was recently introduced to the literature. It is a technique that buckets continuous feature values into discrete bins to speed up the computations and reduce memory usage. Previous studies have discussed its efficiency in various scientific disciplines to save computational time and memory. However, the algorithm's accuracy is still unclear, and its application in concrete properties estimation has not yet been considered. This paper is devoted to evaluating the capability of histogram-based gradient boosting in predicting concrete's compressive strength and comparing its accuracy to other boosting methods. Generally, the results of the study have shown that the histogram-based gradient boosting approach is capable of achieving reliable prediction of concrete compressive strength. Additionally, it showed the effects of each model's parameters on the accuracy of the estimation.
Language:
English
Published:
Civil Engineering Infrastructures Journal, Volume:56 Issue: 1, Jun 2023
Pages:
159 to 172
magiran.com/p2593128  
دانلود و مطالعه متن این مقاله با یکی از روشهای زیر امکان پذیر است:
اشتراک شخصی
با عضویت و پرداخت آنلاین حق اشتراک یک‌ساله به مبلغ 990,000ريال می‌توانید 70 عنوان مطلب دانلود کنید!
اشتراک سازمانی
به کتابخانه دانشگاه یا محل کار خود پیشنهاد کنید تا اشتراک سازمانی این پایگاه را برای دسترسی نامحدود همه کاربران به متن مطالب تهیه نمایند!
توجه!
  • حق عضویت دریافتی صرف حمایت از نشریات عضو و نگهداری، تکمیل و توسعه مگیران می‌شود.
  • پرداخت حق اشتراک و دانلود مقالات اجازه بازنشر آن در سایر رسانه‌های چاپی و دیجیتال را به کاربر نمی‌دهد.
In order to view content subscription is required

Personal subscription
Subscribe magiran.com for 50 € euros via PayPal and download 70 articles during a year.
Organization subscription
Please contact us to subscribe your university or library for unlimited access!