Zero-liquid discharge (ZLD) technology for resource recovery from wastewater: A review M Yaqub, W Lee Science of the total environment 681, 551-563, 2019 | 351 | 2019 |
Environmental-, social-, and governance-related factors for business investment and sustainability: A scientometric review of global trends H Ahmad, M Yaqub, SH Lee Environment, Development and Sustainability 26 (2), 2965-2987, 2024 | 202 | 2024 |
Modeling of a full-scale sewage treatment plant to predict the nutrient removal efficiency using a long short-term memory (LSTM) neural network M Yaqub, H Asif, S Kim, W Lee Journal of Water Process Engineering 37, 2020 | 106 | 2020 |
Comprehensive review on machine learning methodologies for modeling dye removal processes in wastewater SK Bhagat, KE Pilario, OE Babalola, T Tiyasha, M Yaqub, CE Onu, ... Journal of Cleaner Production 385, 135522, 2023 | 63 | 2023 |
Electrolyzed water as a disinfectant: A systematic review of factors affecting the production and efficiency of hypochlorous acid Rita E. Ampiaw, M Yaqub, W Lee Journal of Water Process Engineering 43, https://doi.org/10.1016/j.jwpe.2021 …, 2021 | 55* | 2021 |
Heavy metals removal from aqueous solution through micellar enhanced ultrafiltration: A review M Yaqub, SH Lee Environmental Engineering Research 24 (3), 363-375, 2019 | 55 | 2019 |
Micellar enhanced ultrafiltration (MEUF) of mercury-contaminated wastewater: Experimental and artificial neural network modeling M Yaqub, SH Lee Journal of Water Process Engineering 33, 101046, 2020 | 50 | 2020 |
Treating reverse osmosis concentrate to address scaling and fouling problems in zero-liquid discharge systems: A scientometric review of global trends M Yaqub, MN Nguyen, W Lee Science of The Total Environment 844, 157081, 2022 | 48 | 2022 |
Modeling nutrient removal by membrane bioreactor at a sewage treatment plant using machine learning models M Yaqub, W Lee Journal of Water Process Engineering 46, 102521, 2022 | 38 | 2022 |
Soft computing techniques in prediction Cr (VI) removal efficiency of polymer inclusion membranes M Yaqub, B Eren, V Eyupoglu KOREAN SOC ENVIRONMENTAL ENGINEERS, 2020 | 32 | 2020 |
Investigating micellar-enhanced ultrafiltration (MEUF) of mercury and arsenic from aqueous solution using response surface methodology and gene expression programming M Yaqub, S H Lee, W Lee Separation and Purification Technology 281 (15), 2021 | 30* | 2021 |
Experimental and neural network modeling of micellar enhanced ultrafiltration for arsenic removal from aqueous solution M Yaqub, SH Lee Environmental Engineering Research 26 (1), 2021 | 28 | 2021 |
Flood causes, consequences and protection measures in Pakistan M Yaqub, B Eren, E Doğan Disaster Science and Engineering 1 (1), 8-16, 2015 | 28 | 2015 |
A systematic literature review on lake water level prediction models S Ozdemir, M Yaqub, SO Yildirim Environmental Modelling & Software 163, 105684, 2023 | 27 | 2023 |
Optimization of cesium adsorption by Prussian blue using experiments and gene expression modeling MN Nguyen, M Yaqub, S Kim, W Lee Journal of Water Process Engineering 41, 102084, 2021 | 21 | 2021 |
Assessment of long-term nutrient effective waste-derived growth media for ornamental nurseries S Ozdemir, OH Dede, M Yaqub Waste and Biomass Valorization 8, 2663-2671, 2017 | 20 | 2017 |
Environmental Consciousness Survey of University Students B EREN, M Yaqub ISITES2015 Valencia -Spain, 2015 | 20 | 2015 |
Adsorption of Microcystin onto Activated Carbon: A Review RE Ampiaw, M Yaqub, W Lee Membrane Water Treatment 10 (6), 405-415, 2019 | 18 | 2019 |
Assessment of neural network training algorithms for the prediction of polymeric inclusion membranes efficiency M Yaqub, B Eren, V Eyüpoğlu Sakarya Üniversitesi Fen Bilimleri Enstitüsü Dergisi 20 (3), 533-542, 2016 | 18* | 2016 |
A comparative study of artificial neural network models for the prediction of Cd removal efficiency of polymer inclusion membranes B Eren, M Yaqub, V Eyupoglu Desalination Water Treat 143, 48-58, 2019 | 17 | 2019 |