Ramin Kazemi 
- (2024): Assessing the compressive strength of eco-friendly concrete made with rice husk ash: A hybrid artificial intelligence-aided technique. In: Structures, v. 68 (Oktober 2024).
- (2023): Evaluating the rapid chloride permeability of self-compacting concrete containing fly ash and silica fume exposed to different temperatures: An artificial intelligence framework. In: Construction and Building Materials, v. 409 (Dezember 2023).
- (2024): Compressive strength prediction of sustainable concrete containing waste foundry sand using metaheuristic optimization‐based hybrid artificial neural network. In: Structural Concrete, v. 25, n. 2 (Januar 2024).
- (2023): Towards sustainable use of foundry by-products: Evaluating the compressive strength of green concrete containing waste foundry sand using hybrid biogeography-based optimization with artificial neural networks. In: Journal of Building Engineering, v. 76 (Oktober 2023).
- (2023): New insight into the prediction of strength properties of cementitious mortar containing nano‐ and micro‐silica based on porosity using hybrid artificial intelligence techniques. In: Structural Concrete, v. 24, n. 4 (5 Juli 2023).
- (2021): Hybrid artificial neural network with biogeography-based optimization to assess the role of cement fineness on ecological footprint and mechanical properties of cement mortar expose to freezing/thawing. In: Construction and Building Materials, v. 304 (Oktober 2021).
- (2019): Effect of cement strength class on the generalization of Abrams' law. In: Structural Concrete, v. 20, n. 1 (Februar 2019).
- (2017): ANN prediction of cement mortar compressive strength, influence of cement strength class. In: Construction and Building Materials, v. 138 (Mai 2017).
Structurae kooperiert mit
