Hossein Moayedi

Artificial Intelligence · 2018–2020

A researcher in the Science corpus: 10 papers; trusts 8 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 29 citations into it
• Civil and Structural Engineering — 27 citations into it
• Management, Monitoring, Policy and Law — 18 citations into it
• Building and Construction — 17 citations into it
• Global and Planetary Change — 15 citations into it
• Water Science and Technology — 15 citations into it
• Environmental Engineering — 11 citations into it
• Mechanics of Materials — 9 citations into it

Whom Hossein Moayedi trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

1. N. Null

Who trusts Hossein Moayedi overall

1. Anurag Malik
2. Yanan Zhang
3. Y. Tikhamarine

Papers from Hossein Moayedi's perspective

Ordered by how strongly the researchers Hossein Moayedi trusts endorse each paper. Same corpus, a different order for every researcher.

1. Performance evaluation of GIS-based new ensemble data mining techniques of adaptive neuro-fuzzy inference system (ANFIS) with genetic algorithm (GA), differential evolution (DE), and particle swarm…
2. Stochastic gradient boosting
3. Predicting modulus elasticity of recycled aggregate concrete using M5′ model tree algorithm
4. A comparative assessment of flood susceptibility modeling using Multi-Criteria Decision-Making Analysis and Machine Learning Methods (Journal of Hydrology)
5. Support vector regression approach with different kernel functions for predicting blast-induced ground vibration: a case study in an open-pit coal mine of Vietnam (SN Applied Sciences)
6. Support-Vector Networks
7. Particle swarm optimization
8. Concrete compressive strength using artificial neural networks (Neural computing & applications (Print))
9. Compressive strength prediction of recycled concrete based on deep learning (Construction and Building Materials)
10. Predicting the compressive strength of silica fume concrete using hybrid artificial neural network with multi-objective grey wolves (Journal of Cleaner Production)

Their papers

• The feasibility of Levenberg–Marquardt algorithm combined with imperialist competitive computational method predicting drag reduction in crude oil pipelines (2020) — 59 citations
• Using neural network optimized by imperialist competition method and genetic algorithm to predict water productivity of a nanofluid-based solar still equipped with thermoelectric modules (2020) — 94 citations
• Evaluating and Predicting the Stability of Roadways in Tunnelling and Underground Space Using Artificial Neural Network-Based Particle Swarm Optimization (2020) — 67 citations
• A proper model to predict energy efficiency, exergy efficiency, and water productivity of a solar still via optimized neural network (2020) — 70 citations
• A spatially explicit deep learning neural network model for the prediction of landslide susceptibility (2020) — 294 citations
• A novel artificial intelligence technique to predict compressive strength of recycled aggregate concrete using ICA-XGBoost model (2020) — 322 citations
• Herding Behaviors of grasshopper and Harris hawk for hybridizing the neural network in predicting the soil compression coefficient (2020) — 70 citations
• Green synthesis using cherry and orange juice and characterization of TbFeO3 ceramic nanostructures and their application as photocatalysts under UV light for removal of organic dyes in water (2020) — 143 citations
• Hydrothermal synthesis of DyMn2O5/Ba3Mn2O8 nanocomposite as a potential hydrogen storage material (2019) — 318 citations
• Modification of landslide susceptibility mapping using optimized PSO-ANN technique (2018) — 324 citations