Mohammad Saeed Mafipour
Engineering computations · 2019–2020
A researcher in the Science corpus: 3 papers; trusts 1 researcher and is trusted by 0 researchers here, as inferred from the citation graph.
Whom Mohammad Saeed Mafipour trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
Papers from Mohammad Saeed Mafipour's perspective
Ordered by how strongly the researchers Mohammad Saeed Mafipour trusts endorse each paper. Same corpus, a different order for every researcher.
- Learning capability and storage capacity of two-hidden-layer feedforward networks (IEEE Trans. Neural Networks)
- Extreme learning machine: Theory and applications
- Properties of concrete incorporating fly ash and ground granulated blast-furnace slag
- Neural networks for predicting compressive strength of structural light weight concrete
- Prediction of compressive strength of SCC and HPC with high volume fly ash using ANN
- An evolutionary fuzzy modelling approach and comparison of different methods for shear strength prediction of high-strength concrete beams without stirrups
- Predicting the compressive strength and slump of high strength concrete using neural network
- Importance of input data normalization for the application of neural networks to complex industrial problems
- Cocaine and Chest Pain
- Performance Analysis of Various Activation Functions in Generalized MLP Architectures of Neural Networks
Their papers
- A novel hybrid extreme learning machine–grey wolf optimizer (ELM-GWO) model to predict compressive strength of concrete with partial replacements for cement (2020) — 317 citations
- Prediction of concrete strength in presence of furnace slag and fly ash using Hybrid ANN-GA (Artificial Neural Network-Genetic Algorithm) (2020) — 199 citations
- Application of Extreme Learning Machine (ELM) and Genetic Programming (GP) to design steel-concrete composite floor systems at elevated temperatures (2019) — 157 citations