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Air Pollution Index Estimation Model Based On Artificial Neural Network by Mohammed Nasser, Al-Subaie

“…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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Prediction of the level of air pollution during wildfires using machine learning classification methods by Khalid, Syed Mohammed, Hassan, Raini

“…The Air Pollutant Index (API) is used to identify and classify the ambient air quality status. …”
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GIS-based air quality modelling: spatial prediction of PM10 for Selangor State, Malaysia using machine learning algorithms by Tella, A., Balogun, A.-L.

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Forecasting the air pollution index using artifical neural network at Muar, Johor, Malaysia / Ahmad Farid Rasdi by Rasdi, Ahmad Farid

“…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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Air pollution forecasting in Kuala Terengganu using Artificial Neural Network (ANN) / Nur Raudzah Abdullah by Abdullah, Nur Raudzah

“…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 by Almalawi, A., Alsolami, F., Khan, A.I., Alkhathlan, A., Fahad, A., Irshad, K., Qaiyum, S., Alfakeeh, A.S.

“…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 by Almalawi, A., Alsolami, F., Khan, A.I., Alkhathlan, A., Fahad, A., Irshad, K., Qaiyum, S., Alfakeeh, A.S.

“…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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The implications for ahybrid detection technique against malicious sqlattacks on web applications by Bahjat Arif, Sarajaldeen Akram, Wani, Sharyar

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Optimal economic environmental power dispatch by using artificial bee colony algorithm by Hassan, Elia Erwani, Mohd Noor, Hanan Izzati, Hashim, Mohd Ruzaini, Sulaima, Mohamad Fani, Bahaman, Nazrulazhar

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Digital Quran With Storage Optimization Through Duplication Handling And Compressed Sparse Matrix Method by Ashraf Saleh Mohammad Alomoush

An inclusive multiple model for predicting total sediment transport rate in the presence of coastal vegetation cover based on optimized kernel extreme learning models by Jalil-Masir H., Fattahi R., Ghanbari-Adivi E., Asadi Aghbolaghi M., Ehteram M., Ahmed A.N., El-Shafie A.

Application of data mining techniques for economic evaluation of air pollution impact and control by Lukman, Iing

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Development of effluent removal prediction model efficiency in septic sludge treatment plant through clonal selection algorithm by Ting S.C., Ismail A.R., Malek M.A.

A Stacked Ensemble Deep Learning Approach For Imbalanced Multi-class Water Quality Index Prediction by Wen Yee Wong, Khairunnisa Hasikin, Anis Salwa Mohd Khairuddin, Sarah Abdul Razak, Hanee Farzana Hizaddin, Mohd Istajib Mokhtar, Muhammad Mokhzaini Azizan

Investigating the reliability of machine learning algorithms as an advanced tool for ozone concentration prediction by Ayman Mohammed Shaher Yafouz, Mr.

“…The hybrid technique has been developed by using deep learning algorithms with the structure of multiple layers (with several neurons) of CNN and LSTM. …”

Swarm Intelligence-Based Smart Energy Allocation Strategy for Charging Stations of Plug-In Hybrid Electric Vehicles by Rahman, Imran, Vasant, Pandian, Mahinder Singh, Balbir Singh, Abdullah-Al-Wadud, M.

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Intelligent cooperative web caching policies for media objects based on J48 decision tree and naïve Bayes supervised machine learning algorithms in structured peer-to-peer systems by Ibrahim, Hamidah, Mohammed, Waheed Yasin, Udzir, Nur Izura, Abdul Hamid, Nor Asilah Wati

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Advancements In Monitoring water Quality Based On Various Sensing Methods: A Systematic Review by Siti Nadhirah Zainurin, Wan Zakiah Wan Ismail, Siti Nurul Iman Mahamud, Irneza Ismail, Khairul Nabilah Zainul Ariffin, Wan Maryam Wan Ahmad Kamil, Juliza Jamaludin

An integrated approach for the prediction of water quality index based on land use attribute using data generation method and back propagation network algorith by Gorashi, Faris, Abdullah, Alias

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Interactive Fuzzy Logic Interface for Enhanced Real-Time Water Quality Index Monitoring by Amar Lokman, Wan Zakiah Wan Ismail, Nor Azlina Ab Aziz, Anith Khairunnisa Ghazali