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Comparative assessment of various MPPT algorithms for solar photovoltaic systems under dynamic shading conditions
Published 2025“…The parameters considered for comparison are rise time, settling time and power output under different environmental conditions such as irradiance and temperature. …”
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Air quality forecasting and mapping in Malaysian urban areas: A hybrid deep learning approach
Published 2025text::Thesis -
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Extreme air pollutant data analysis using classical and Bayesian approaches
Published 2015“…MTM algorithm is an extension of MH algorithm, designed to improve the convergence of MH algorithm by performing parallel computation. …”
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The prediction of diesel engine NOx emissions using artificial neural network / Mohd. Mahadzir Mohammud and Khairil Faizi Mustafa
Published 2003“…The modelling algorithm implemented, takes a large set of measurements to learn how to predict the NOx emission from four operating parameters. …”
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The prediction of diesel engine NOx emissions using artificial neural network / Mohd Mahadzir Mohammud and Khairil Faizi Mustafa
Published 2003“…The modelling algorithm implemented, takes a large set of measurements to learn how to predict the NOx emission from four operating parameters. …”
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Numerical Analysis of structural batteries response with the presence of uncertainty
Published 2023“…The proposed research is devoted to the uncertainty analysis of structural battery behavior under various parameters. To help with the analysis, a dedicated algorithm based on an elimination approach to solve numerical problems with uncertain parameters is successfully developed using Visual Basic. …”
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Numerical Analysis of Structural Batteries Response with the Presence of Uncertainty
Published 2023“…The proposed research is devoted to the uncertainty analysis of structural battery behavior under various parameters. To help with the analysis, a dedicated algorithm based on an elimination approach to solve numerical problems with uncertain parameters is successfully developed using Visual Basic. …”
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The assessment of ambient carbon monoxide concentration levels / Hasmawati Mat Hassan
Published 2020“…The concentration of air pollutants in the atmosphere has greatly influenced by the meteorological parameters such as wind which is the main parameter for the transport of air pollutants. …”
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Interactive Fuzzy Logic Interface for Enhanced Real-Time Water Quality Index Monitoring
Published 2026journal::journal article -
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Prediction of Total Maximum Daily Loads (TMDLs) of pollutants in river by using artificial neural network (ANN) / Khairunnisa Khairudin, Mohamed Syazwan Osman and Syahrul Fithry Se...
Published 2020“…Total Maximum Daily Load (TMDL) studies are crucial in determining a pollutant reduction target and allocates load reductions necessary to the source(s) of the pollutant. …”
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Partial least squares integrated national water quality standards (NWQS) for indexing of water quality from industrial effluent
Published 2015“…Indexing with DOE-WQI equation method using six (6) pre-determined DOE-WQI parameters revealed that all stations falls under Class III with a slightly polluted status. …”
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Effects of Ambient Tropospheric Ozone on Mr-219 Rice in the Muda Irrigation Scheme Area
Published 2005“…Tropospheric ozone (03) is recognised as the pollutant most likely to cause widespread crop damage. …”
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Optimizations and docking simulation study for metolachlor adsorption from water onto MIL-101(Cr) metal�organic framework
Published 2022“…The artificial neural network learning algorithm was employed to predict the adsorption of MET with high level of accuracy R2 0.999 and RMSE 0.047. …”
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Optimizations and docking simulation study for metolachlor adsorption from water onto MIL-101(Cr) metal�organic framework
Published 2022“…The artificial neural network learning algorithm was employed to predict the adsorption of MET with high level of accuracy R2 0.999 and RMSE 0.047. …”
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Optimizations and docking simulation study for metolachlor adsorption from water onto MIL-101(Cr) metal�organic framework
Published 2022“…The artificial neural network learning algorithm was employed to predict the adsorption of MET with high level of accuracy R2 0.999 and RMSE 0.047. …”
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