A comparative study of ANN and ANFIS models for the prediction of cement-based mortar materials compressive strength

Despite the extensive use of mortars materials in constructions over the last decades, there is not yet a reliable and robust method, available in the literature, which can estimate its strength based on its mix parameters. This limitation is due to the highly nonlinear relation between the mortar’s...

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Veröffentlicht in:	Neural computing & applications Jg. 33; H. 9; S. 4501 - 4532
Hauptverfasser:	Armaghani, Danial Jahed, Asteris, Panagiotis G.
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	London Springer London 01.05.2021 Springer Nature B.V
Schlagworte:	Adaptive systems Artificial Intelligence Artificial neural networks Comparative studies Compressive strength Computational Biology/Bioinformatics Computational Science and Engineering Computer Science Data Mining and Knowledge Discovery Fuzzy logic Image Processing and Computer Vision Metakaolin Mortars (material) Original Article Performance prediction Probability and Statistics in Computer Science Robustness Metakaolin Mortar Artificial neural networks Cement Artificial intelligence techniques Compressive strength Adaptive neuro-fuzzy inference system
ISSN:	0941-0643, 1433-3058
Online-Zugang:	Volltext
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