Adaptive Neuro-Fuzzy Inference System for Predicting Strength of High-Performance Concrete

机译：用于预测高性能混凝土强度的自适应神经模糊推理系统

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This study examines the performance of Adaptive Neuro-Fuzzy Inference System (ANFIS) for estimation of compressive strength of High-Performance Concrete (HPC) from given mix proportion. An ANFIS model merges advantages of both ANN and Fuzzy Logic. A total of 54 experimental datasets were used, where 36 datasets were used in training and 18 datasets were used for validating the model. Six input parameters include water binder ratio, age of testing, silica fumes, coarse and fine aggregate and superplasticizer, whereas compressive strength is the single output parameter. The experimental and obtained results were compared. The result illustrates that ANFIS model can be used as an alternative method to predict the compressive strength of high-performance concrete.

机译：本研究探讨了自适应神经模糊推理系统（ANFIS）的性能，用于从给定的混合比例估计高性能混凝土（HPC）的抗压强度。 ANFIS模型合并了ANN和模糊逻辑的优势。使用总共54个实验数据集，其中使用36个数据集在训练中使用，并且使用18个数据集来验证模型。六个输入参数包括水粘合剂比，测试年龄，二氧化硅烟雾，粗细胞和精细塑化剂，而抗压强度是单输出参数。比较实验和获得的结果。结果说明了ANFIS模型可以用作预测高性能混凝土的抗压强度的替代方法。

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《International Conference on Soft Computing for Problem Solving》|2020年|xviii 1013 pages :|共16页
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L. V. Prasad Meesaraganda; Nilarghya Sarkar; Nilanjan Tarafder;
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中图分类 TP301.6-532;
关键词
High-performance concrete; ANFIS model; Training and testing; Compressive strength;

机译：高性能混凝土;ANFIS模型;培训和测试;抗压强度;

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4. Adaptive Neuro-Fuzzy Inference System for Predicting Strength of High-Performance Concrete [C] . L. V. Prasad Meesaraganda, Nilarghya Sarkar, Nilanjan Tarafder International Conference on Soft Computing for Problem Solving . 2020

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5. Nonlinear adaptive noise cancellation for two-dimensional signals with adaptive neuro-fuzzy inference systems. [D] . Qin, Hao. 2005

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Adaptive Neuro-Fuzzy Inference System for Predicting Strength of High-Performance Concrete

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