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High-performance concrete compressive strength prediction using Genetic Weighted Pyramid Operation Tree (GWPOT)

机译:使用遗传加权金字塔操作树(GWpOT)预测高性能混凝土抗压强度

摘要

This study uses the Genetic Weighted Pyramid Operation Tree (GWPOT) to build a model to solve the problem of predicting high-performance concrete compressive strength. GWPOT is a new improvement of the genetic operation tree that consists of the Genetic Algorithm, Weighted Operation Structure, and Pyramid Operation Tree. The developed model obtained better results in benchmark tests against several widely used artificial intelligence (AI) models, including the Artificial Neural Network (ANN), Support Vector Machine (SVM), and Evolutionary Support Vector Machine Inference Model (ESIM). Further, unlike competitor models that use “black-box” techniques, the proposed GWPOT model generates explicit formulas, which provide important advantages in practical application.
机译:本研究使用遗传加权金字塔操作树(GWPOT)建立模型,以解决预测高性能混凝土抗压强度的问题。 GWPOT是遗传运算树的新改进,它由遗传算法,加权运算结构和金字塔运算树组成。在针对几种广泛使用的人工智能(AI)模型的基准测试中,开发的模型获得了更好的结果,其中包括人工神经网络(ANN),支持向量机(SVM)和进化支持向量机推理模型(ESIM)。此外,与使用“黑匣子”技术的竞争对手模型不同,所提出的GWPOT模型会生成明确的公式,这在实际应用中具有重要的优势。

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