Publications by authors named "Lawrence Koech"
Precision forecasting of spray-dry desulfurization using Gaussian noise data augmentation and k-fold cross-validation optimized neural computing.
J Environ Sci Health A Tox Hazard Subst Environ Eng
March 2024
Article Synopsis
- Perceptron models are vital for pattern recognition and classification, and this study focused on applying artificial neural networks (ANN) to predict the performance of a mini-spray dryer for desulfurization processes.
- The research utilized k-fold cross-validation and trained 21 ANN models on various input conditions, including temperature, pH, stoichiometric ratio, and solid concentration, with synthetic data generated through Gaussian noise augmentation.
- The study highlighted that effective cross-validation and data augmentation are essential for improving neural network performance, with the logsig activation function and 10 hidden cells yielding the best results in accurately mapping data to actual values.
This study presents the findings of an investigation involving the absorption of SO from flue gases, using three different sorbents, in a spray dryer. Experimentation involved the evaluation of three sorbents, i.e.
View Article and Find Full Text PDFThe assessment of response surface methodology (RSM) and artificial neural network (ANN) modeling in dry flue gas desulfurization at low temperatures.
J Environ Sci Health A Tox Hazard Subst Environ Eng
March 2023
Article Synopsis
- The study evaluates the efficiency of a flue gas desulfurization (FGD) system, focusing on sulfur dioxide removal and reagent conversion in dry FGD (DFGD) systems.
- Researchers used response surface methodology (RSM) and artificial neural networks (ANN) to analyze how factors like hydration time and temperature affect the system's performance.
- The results show that a specific ANN model (5-10-2 architecture) produced highly accurate predictions with R-squared values of 0.993 and 0.9986, indicating good model reliability and performance in mapping the DFGD process.
Leaching kinetics of bottom ash waste as a source of calcium ions.
J Air Waste Manag Assoc
February 2015
Bottom ash is a waste material from coal-fired power plants, and it is known to contain elements that are potentially toxic at high concentration levels when disposed in landfills. This study investigates the use of bottom ash as a partial substitute sorbent for wet flue gas desulfurization (FGD) processes by focusing on its leaching kinetics in adipic acid. This was studied basing on the shrinking core model that was applied to the experimental data obtained by the authors presented at the International Conference on Industrial, Manufacturing, Automation and Mechanical Engineering, Johannesburg, South Africa, November 27-28, 2013) on dissolution of bottom ash.
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