A novel feed-through Elman neural network for predicting the compressive and flexural strengths of eco-friendly jarosite mixed concrete: design, simulation and a comparative study-Reference-Cited by-同舟云学术

A novel feed-through Elman neural network for predicting the compressive and flexural strengths of eco-friendly jarosite mixed concrete: design, simulation and a comparative study

Published:2023-05-03 Issue:1 Volume:28 Page:399-414
ISSN:1432-7643
Container-title:Soft Computing
language:en
Short-container-title:Soft Comput

Author:

Gupta Tanvi^ORCID,Kumar Rajesh^ORCID

Publisher

Springer Science and Business Media LLC

Subject

Geometry and Topology,Theoretical Computer Science,Software

Link

https://link.springer.com/content/pdf/10.1007/s00500-023-08195-9.pdf

Reference53 articles.

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3. Asokan P, Saxena M, Asolekar S (2010) Recycling hazardous jarosite waste using coal combustion residues. Mater Charact 61(12):1342–1355

4. Asteris PG, Mokos VG (2020) Concrete compressive strength using artificial neural networks. Neural Comput Appl 32(15):11807–11826

5. Bai J, Wild S, Ware J, Sabir B (2003) Using neural networks to predict workability of concrete incorporating metakaolin and fly ash. Adv Eng Softw 34(11–12):663–669

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