Výsledky vyhledávání - "Robert Makomere"

Akademický článek

Low-temperature desulfurization forecasting using soft computing models

Autor: Robert Makomere, Hilary Rutto, Alfayo Alugongo, Lawrence Koech

Publikováno v: EQA, Vol 62, Pp 45-54 (2024)

Flue Gas Desulfurization (FGD) is pivotal in reducing Sulfur Dioxide (SO2) concentrations through neutralization. This study explored dry FGD modeling using Artificial Neural Networks (ANN) and Adaptive Neuro-Fuzzy Inference Systems (ANFIS). The inde

Externí odkaz: https://doaj.org/article/88809b93e07e434da8c27e51ca0a0efd

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Akademický článek

Preparation, characterization and application of polymeric ultra-permeable biodegradable ferromagnetic nanocomposite adsorbent for removal of Cr(VI) from synthetic wastewater: kinetics, isotherms and thermodynamics

Autor: Evans Suter, Hilary Rutto, Robert Makomere, Musamba Banza, Tumisang Seodigeng, Sammy Kiambi, Wesley Omwoyo

Publikováno v: Frontiers in Environmental Chemistry, Vol 5 (2024)

Hexavalent chromium (Cr(VI)) contamination in drinking water due to industrial activities is a growing worldwide concern. Cr(VI) concentrations exceeding a few parts per billion (ppb) can cause serious health problems such as asthma, blood cancer, ki

Externí odkaz: https://doaj.org/article/9ca95d5a921848b5be4f505d3f56c6b0

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Akademický článek

Modelling of Low-Temperature Sulphur Dioxide Removal Using Response Surface Methodology (RSM), Artificial Neural Network (ANN) and Adaptive Neuro-Fuzzy Inference System (ANFIS)

Autor: Robert Makomere, Hilary Rutto, Lawrence Koech, Musamba Banza

Publikováno v: Engineering Proceedings, Vol 37, Iss 1, p 92 (2023)

Empirical and machine learning models are estimation tools relevant to obtaining scalable solutions to engineering problems. In this study, response surface methodology (RSM) was incorporated to correlate the experimental findings based on mathematic

Externí odkaz: https://doaj.org/article/efde2ca97037420ca66ae924a7af49da

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The assessment of response surface methodology (RSM) and artificial neural network (ANN) modeling in dry flue gas desulfurization at low temperatures

Autor: Robert Makomere, Hilary Rutto, Lawrence Koech

Publikováno v: Journal of Environmental Science and Health, Part A. 58:191-203

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::da3bd5ddcaa088185354b3b7a9276e8a
https://doi.org/10.1080/10934529.2023.2174334

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The use of artificial neural network (ANN) in dry flue gas desulphurization modelling: Levenberg–Marquardt (LM) and Bayesian regularization (BR) algorithm comparison

Autor: Robert Makomere, Hilary Rutto, Lawrence Koech, Musamba Banza

Publikováno v: The Canadian Journal of Chemical Engineering. 101:3273-3286

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::4f79a807ded448ae6a679c0a2ed28635
https://doi.org/10.1002/cjce.24715

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Author response for 'The use of Artificial Neural Network (ANN) in Dry Flue Gas Desulphurization Modelling: Levenberg‐Marquardt (LM) and Bayesian Regularization (BR) algorithm comparison'

Autor: null Robert Makomere, null Hilary Rutto, null Lawrence Koech, null Musamba Banza

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::d81374d1cd86b394e06e7c07f3f06cf8
https://doi.org/10.1002/cjce.24715/v2/response1

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