Search Results - (( rainfall distribution selection algorithm ) OR ( based pollution index algorithm ))
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Air Pollution Index Estimation Model Based On Artificial Neural Network
Published 2021“…However, choosing a correct model structure, and optimum training algorithm with minimum complexity is crucial. Therefore, a dimensional reduction method was implemented based on the multiway principal component analysis (MPCA) method. …”
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The use of radar-rainfall inputs for quantitative precipitation estimation (QPE) in Klang River Basin / Suzana Ramli
Published 2015“…Flooding is a natural disaster that often occurs in Malaysia due to its heavy rainfall distribution. Lately, the exceptional amount of rainfall worsens the flood situation. …”
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Forecasting the air pollution index using artifical neural network at Muar, Johor, Malaysia / Ahmad Farid Rasdi
Published 2021“…This study mainly focuses on forecasting the Air Pollution Index. In this study, secondary data was used which is obtained from the Department of Environment (DOE) regarding the Air Pollution Index in Malaysia. …”
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Prediction of the level of air pollution during wildfires using machine learning classification methods
Published 2020“…The Air Pollutant Index (API) is used to identify and classify the ambient air quality status. …”
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Comparison of future intensity duration frequency curve by considering the impact of climate change: case study for Kuching city
Published 2016“…The selected study rainfall station is Kuching Airport. …”
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Air pollution forecasting in Kuala Terengganu using Artificial Neural Network (ANN) / Nur Raudzah Abdullah
Published 2020“…In this study, ANN algorithm is used to forecast air pollution index (API) for the next day in Kuala Terengganu. …”
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An IoT based system for magnify air pollution monitoring and prognosis using hybrid artificial intelligence technique
Published 2022“…The hypothesized artificial intelligence models are evaluated to the Root Mean Squares Error, Mean Squared Error and Mean absolute error, depending upon the performance measurements and a lower error value model is chosen. Based on the algorithm of the Artificial Intelligent System, the level of 5 air pollutants like CO2, SO2, NO2, PM 2.5 and PM10 can be predicted immediately by integrating the observations with errors. …”
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An IoT based system for magnify air pollution monitoring and prognosis using hybrid artificial intelligence technique
Published 2022“…The hypothesized artificial intelligence models are evaluated to the Root Mean Squares Error, Mean Squared Error and Mean absolute error, depending upon the performance measurements and a lower error value model is chosen. Based on the algorithm of the Artificial Intelligent System, the level of 5 air pollutants like CO2, SO2, NO2, PM 2.5 and PM10 can be predicted immediately by integrating the observations with errors. …”
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Reservoir Inflow Forecasting Using Artificial Neural Network and Adaptive Neuro-Fuzzy Inference System Techniques
Published 2007“…The reservoir inflow and rainfall data sets were examined for normal distribution and the best data transformation was used. …”
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A Stacked Ensemble Deep Learning Approach For Imbalanced Multi-class Water Quality Index Prediction
Published 2024journal::journal article -
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Investigating the reliability of machine learning algorithms as an advanced tool for ozone concentration prediction
Published 2023“…The hybrid technique has been developed by using deep learning algorithms with the structure of multiple layers (with several neurons) of CNN and LSTM. …”
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Swarm Intelligence-Based Smart Energy Allocation Strategy for Charging Stations of Plug-In Hybrid Electric Vehicles
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Advancements In Monitoring water Quality Based On Various Sensing Methods: A Systematic Review
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