التفاصيل البيبلوغرافية
| العنوان: |
机器学习和元启发式算法优化混凝土配合比 研究进展. (Chinese) |
| Alternate Title: |
Research progress on mixture optimization of concrete based on machine learning and metaheuristic algorithms. (English) |
| المؤلفون: |
陈云, 付前旺 |
| المصدر: |
Acta Materiae Compositae Sinica; Nov2024, Vol. 41 Issue 11, p5824-5851, 28p |
| Abstract (English): |
The concrete mix ratio determines its cost, workability, mechanical properties, and durability. The traditional method of concrete mix ratio optimization is through a large number of laboratory tests, which consumes a lot of time, labor, and resources. To solve the above problems, concrete proportion optimization using machine learning and meta-heuristic optimization algorithms has been proven to be a promising technical tool. Presents a comprehensive review of the research on concrete proportion design and optimization. First, the basic working principles and advantages of commonly used machine learning and meta-heuristic algorithms are discussed. Then, the applications of machine learning and meta-heuristic-based algorithms in single-objective and multi-objective optimization of various types of concrete proportions are summarized. Finally, current trends and opportunities in advancing the field of concrete proportion design and optimization are highlighted and discussed in the context of the current state of the art, providing a basis for deeper development and application of machine learning techniques in the field of concrete. [ABSTRACT FROM AUTHOR] |
| Abstract (Chinese): |
混凝土配合比决定其成本、工作性能、力学性能和耐久性能，传统混凝土配合比优化方法是通过大 量实验室试验，需要消耗大量时间、人力和资源。为了解决上述问题，利用机器学习和元启发式优化算法进 行混凝土配合比优化已被证明是一种具有广阔前景的技术手段。本文全面回顾了有关混凝土配合比设计和优 化方面的研究。首先，讨论了常用的机器学习和元启发式算法的基本工作原理和优势。然后，归纳总结了基 于机器学习和元启发式算法在单一目标、多目标优化各种类型混凝土配合比方面的应用。最后，结合当前的 技术水平，强调并讨论了推进混凝土配合比设计和优化领域的当前趋势和机遇，为机器学习技术在混凝土领 域更深层次的开发和应用提供了依据。 [ABSTRACT FROM AUTHOR] |
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| قاعدة البيانات: |
Complementary Index |