Zaher Mundher Yaseen

Environmental Engineering · 2015–2020

A researcher in the Science corpus: 18 papers; trusts 21 researchers and is trusted by 4 researchers here, as inferred from the citation graph.

Subfields

• Environmental Engineering — 170 citations into it; #2,363 of 5,479 by trust here, #560 by citations
• Artificial Intelligence — 118 citations into it
• Water Science and Technology — 115 citations into it
• Global and Planetary Change — 105 citations into it
• Electrical and Electronic Engineering — 88 citations into it
• Civil and Structural Engineering — 45 citations into it
• Statistics and Probability — 24 citations into it
• Computational Theory and Mathematics — 21 citations into it

Whom Zaher Mundher Yaseen trusts overall

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

1. Ravinesh C. Deo
2. Ozgur Kisi
3. G. Huang
4. Tianfeng Chai
5. Jan Adamowski
6. Vladimir Naumovich Vapni
7. Holger R. Maier
8. Hsuan-Tien Lin
9. Xin-She Yang
10. N. Null

Who trusts Zaher Mundher Yaseen overall

1. Ravinesh C. Deo
2. Mohammad Ali Ghorbani
3. Zhenliang Yin
4. Anurag Malik
5. Ozgur Kisi
6. Hristos Tyralis
7. Rahim Barzegar
8. John M. Quilty
9. Jan Adamowski
10. Xiaohui Yuan

Papers from Zaher Mundher Yaseen's perspective

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

1. ImageNet classification with deep convolutional neural networks
2. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
3. Gradient-based learning applied to document recognition
4. Long Short-Term Memory
5. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
6. The Nature of Statistical Learning Theory
7. Attention is All you Need (Neural Information Processing Systems)
8. Learning Multiple Layers of Features from Tiny Images
9. ImageNet: A large-scale hierarchical image database
10. Going deeper with convolutions

Their papers

• An enhanced extreme learning machine model for river flow forecasting: State-of-the-art, practical applications in water resource engineering area and future research direction (2019) — 612 citations
• Stream-flow forecasting using extreme learning machines: a case study in a semi-arid region in Iraq (2016) — 299 citations
• Implementation of a hybrid MLP-FFA model for water level prediction of Lake Egirdir, Turkey (2018) — 131 citations
• Simulation of the depth scouring downstream sluice gate: The validation of newly developed data-intelligent models (2020) — 65 citations
• The Hybridization of Ensemble Empirical Mode Decomposition with Forecasting Models: Application of Short-Term Wind Speed and Power Modeling (2020) — 61 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
• River water quality index prediction and uncertainty analysis: A comparative study of machine learning models (2020) — 320 citations
• A survey on river water quality modelling using artificial intelligence models: 2000–2020 (2020) — 551 citations
• Complete ensemble empirical mode decomposition hybridized with random forest and kernel ridge regression model for monthly rainfall forecasts (2020) — 175 citations
• Surrogate permeability modelling of low-permeable rocks using convolutional neural networks (2020) — 50 citations
• Copula based assessment of meteorological drought characteristics: Regional investigation of Iran (2019) — 135 citations
• Shear strength of steel fiber-unconfined reinforced concrete beam simulation: Application of novel intelligent model (2019) — 110 citations
• Reference evapotranspiration prediction using hybridized fuzzy model with firefly algorithm: Regional case study in Burkina Faso (2018) — 164 citations
• Non-tuned data intelligent model for soil temperature estimation: A new approach (2018) — 101 citations
• Pan evaporation prediction using a hybrid multilayer perceptron-firefly algorithm (MLP-FFA) model: case study in North Iran (2018) — 184 citations
• Predicting compressive strength of lightweight foamed concrete using extreme learning machine model (2018) — 397 citations
• Novel approach for streamflow forecasting using a hybrid ANFIS-FFA model (2017) — 241 citations
• Artificial intelligence based models for stream-flow forecasting: 2000-2015 (2015) — 501 citations