Mohammad Zounemat‐Kermani

Environmental Engineering · 2012–2022

A researcher in the Science corpus: 9 papers; trusts 8 researchers and is trusted by 2 researchers here, as inferred from the citation graph.

Subfields

• Environmental Engineering — 67 citations into it; #3,794 of 5,479 by trust here, #3,093 by citations
• Water Science and Technology — 52 citations into it
• Artificial Intelligence — 45 citations into it
• Global and Planetary Change — 41 citations into it
• Electrical and Electronic Engineering — 21 citations into it

Whom Mohammad Zounemat‐Kermani trusts overall

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

1. Ozgur Kisi
2. Jerome H. Friedman
3. Kwok-Wing Chau
4. Robert E. Schapire
5. Yoav Freund
6. A. Rahimikhoob
7. N. Null
8. Ioannis N. Daliakopoulos

Who trusts Mohammad Zounemat‐Kermani overall

1. Ozgur Kisi
2. Yingyi Chen
3. A. Mirarabi
4. Behrooz Keshtegar
5. Babak Jahani
6. Lihua Song

Papers from Mohammad Zounemat‐Kermani's perspective

Ordered by how strongly the researchers Mohammad Zounemat‐Kermani trusts endorse each paper. Same corpus, a different order for every researcher.

1. Particle Swarm Optimization Training Algorithm for ANNs in Stage Prediction of Shing Mun River
2. Groundwater level forecasting using artificial neural networks
3. A comparative study of artificial neural networks and support vector machines for predicting groundwater levels in a coastal aquifer
4. DENFIS: dynamic evolving neural-fuzzy inference system and its application for time-series prediction (IEEE transactions on fuzzy systems)
5. A novel kernelized fuzzy C-means algorithm with application in medical image segmentation (Artif. Intell. Medicine)
6. COMPARISON BETWEEN M5 MODEL TREE AND NEURAL NETWORKS FOR PREDICTION OF SIGNIFICANT WAVE HEIGHT IN LAKE SUPERIOR
7. An intelligent stock trading decision support system through integration of genetic algorithm based fuzzy neural network and artificial neural network (Fuzzy Sets Syst.)
8. Artificial neural networks: fundamentals, computing, design, and application.
9. Hourly predictive Levenberg–Marquardt ANN and multi linear regression models for predicting of dew point temperature (Meteorology and atmospheric physics (Print))
10. Imperialist competitive algorithm: An algorithm for optimization inspired by imperialistic competition (IEEE Congress on Evolutionary Computation)

Their papers

• Groundwater level prediction using machine learning models: A comprehensive review (2022) — 326 citations
• Ensemble machine learning paradigms in hydrology: A review (2021) — 558 citations
• On the complexities of sediment load modeling using integrative machine learning: Application of the great river of Loíza in Puerto Rico (2020) — 57 citations
• Prediction of Suspended Sediment Load Using Data-Driven Models (2019) — 65 citations
• Subset Modeling Basis ANFIS for Prediction of the Reference Evapotranspiration (2018) — 47 citations
• Modeling groundwater fluctuations by three different evolutionary neural network techniques using hydroclimatic data (2017) — 62 citations
• Evaluation of data driven models for river suspended sediment concentration modeling (2016) — 121 citations
• Solar radiation prediction using different techniques: model evaluation and comparison (2016) — 282 citations
• Hourly predictive Levenberg–Marquardt ANN and multi linear regression models for predicting of dew point temperature (2012) — 69 citations