Search Results - (( data distribution factor algorithm ) OR ( water pollution model algorithm ))

The Performance of Chlorophyll-a Distribution Estimation by Using Ratio Algorithm on Landsat-8 in Sungai Merbok Estuary / Jesse Vince Rabing ... [et al.] by Rabing, Jesse Vince, Abd.Aziz, Khairul Naim, Kamaruddin, Sharir Aizat, Roslani, Muhammad Akmal, Tajam, Jamil, Ahmad, Aziani, Nazri, Rosnani, Zainol, Zamzila Erdawati, Ramli, Rohayu, Shaari, Mohd Idrus

“…The distribution models generated from the algorithms were utilizing Landsat-8 satellite images with B-G and B-R bands ratio. …”
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Development of classification model between clean water and polluted water based on capacitance properties using Levenberg Marquardt (LM) algorithm of artificial neural network / Mohamad Firdaus Mohamad Salehuddin by Mohamad Salehuddin, Mohamad Firdaus

“…These measurement inputs were then going through the process of classification in ANN to generate the optimized models by using LM algorithm. The model is being trained, tested, and validated to differentiate between clean water and polluted water. …”
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Development of prediction model for phosphate in reservoir water system based machine learning algorithms by Latif S.D., Birima A.H., Ahmed A.N., Hatem D.M., Al-Ansari N., Fai C.M., El-Shafie A.

“…Decision trees; Eutrophication; Forecasting; Learning systems; Neural networks; Phosphate fertilizers; Predictive analytics; Reservoirs (water); Stochastic systems; Support vector machines; Water pollution; Water quality; Water supply; Conventional modeling; Cross validation; Developed model; Non-point source pollution; Prediction model; Primary sources; Statistical indices; Water quality parameters; Learning algorithms…”

Classification model for water quality using machine learning techniques by Azilawati, Rozaimee, Azrul Amri, Jamal, Azwa, Abdul Aziz

“…There is a need to resolve this problem for us to get good water that can be used for domestic purposes. This article proposes a suitable classification model for classifying water quality based on the machine learning algorithms. …”
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Enhancing river health monitoring: Developing a reliable predictive model and mitigation plan by Azha S.F., Sidek L.M., Ahmad Z., Zhang J., Basri H., Zawawi M.H., Noh N.M., Ahmed A.N.

“…Thus, there is a pressing need to create a precise and robust water quality prediction model. The dynamic and non-linear characteristics of water quality parameters pose significant challenges for conventional machine learning algorithms like multi-linear regression, as they struggle to capture these complexities. …”

Machine learning based-model to predict catalytic performance on removal of hazardous nitrophenols and azo dyes pollutants from wastewater by Khan M.S.J., Sidek L.M., Kumar P., Alkhadher S.A.A., Basri H., Zawawi M.H., El-Shafie A., Ahmed A.N.

Enhancing riverine load prediction of anthropogenic pollutants: Harnessing the potential of feed-forward backpropagation (FFBP) artificial neural network (ANN) models by Khairudin K., Ul-Saufie A.Z., Senin S.F., Zainudin Z., Rashid A.M., Abu Bakar N.F., Anas Abd Wahid M.Z., Azha S.F., Abd-Wahab F., Wang L., Sahar F.N., Osman M.S.

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Assessing the relationship between pollution sources and water quality parameters of Sungai Langat Basin using association rule mining by Nurizah Abdul Hasib, Zalinda Othman

“…Due to water pollution, the water quality in Sungai Langat Basin is declining. …”
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Removal of heavy metals from water by functionalized carbon nanotubes with deep eutectic solvents: An artificial neural network approach / Seef Saadi Fiyadh by Seef Saadi , Fiyadh

“…The NARX algorithm is used for the modelling of Hg2+ removal. …”
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Estimation of the denitrification in the lower Mississippi Valley by Saleh, Abdul Razak

“…CREAMS model was developed by a team of the Agricultural Research Service, United States Department of Agriculture scientists JQ simulate the effect of management systems on nonpoint source water pollution. …”
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Enhancing riverine load prediction of anthropogenic pollutants: harnessing the potential of feed-forward backpropagation (FFBP) artificial neural network (ANN) models by Khairudin, Khairunnisa, Ul-Saufie, Ahmad Zia, Senin, Syahrul Fithry, Zainudin, Zaki, Rashid, Ammar Mohd, Abu Bakar, Noor Fitrah, Anas Abd Wahid, Muhammad Zakwan, Azha, Syahida Farhan, Abd Wahab, Mohd Firdaus, Wang, Lei, Sahar, Farisha Nerina, Osman, Mohamed Syazwan

“…The feed-forward neural network model with a backpropagation algorithm and Bayesian regularisation training algorithm outperformed the radial basis neural network. …”
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Modeling of Cu(II) adsorption from an aqueous solution using an Artificial Neural Network (ANN) by Khan T., Manan T.S.B., Isa M.H., Ghanim A.A.J., Beddu S., Jusoh H., Iqbal M.S., Ayele G.T., Jami M.S.

“…copper; sulfur; water; adsorption; algorithm; chemistry; diffusion; kinetics; molecular model; solution and solubility; thermodynamics; water pollutant; Adsorption; Algorithms; Copper; Diffusion; Kinetics; Models, Molecular; Neural Networks, Computer; Solutions; Sulfur; Thermodynamics; Water; Water Pollutants, Chemical…”

Machine learning algorithm as a sustainable tool for dissolved oxygen prediction: a case study of Feitsui Reservoir, Taiwan by Ziyad Sami B.F., Latif S.D., Ahmed A.N., Chow M.F., Murti M.A., Suhendi A., Ziyad Sami B.H., Wong J.K., Birima A.H., El-Shafie A.

Feedforward artificial neural network-based model for predicting the removal of phenolic compounds from water by using deep eutectic solvent-functionalized CNTs by Ibrahim R.K., Fiyadh S.S., AlSaadi M.A., Hin L.S., Mohd N.S., Ibrahim S., Afan H.A., Fai C.M., Ahmed A.N., Elshafie A.

“…carbon nanotube; phenol derivative; solvent; adsorption; algorithm; chemistry; kinetics; theoretical model; water management; water pollutant; Adsorption; Algorithms; Kinetics; Models, Theoretical; Nanotubes, Carbon; Neural Networks, Computer; Phenols; Solvents; Water Pollutants, Chemical; Water Purification…”

A hybrid fuzzy logic and extreme learning machine for improving efficiency of circulating water systems in power generation plant by Aziz N.L.A.A., Yap K.S., Bunyamin M.A.

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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

“…The method used exponential model equation, Lagrange model equation 3rd & fourth degree polynomial fit, saturation growth-rate model in order to generate the required data and artificial neural network’s back propagation network algorithm. …”
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A stacked ensemble deep learning model for water quality prediction / Wong Wen Yee by Wong , Wen Yee

“…Therefore, the use of water quality indicators to detect the presence of pollutants is very important. …”
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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.

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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... by Khairudin, Khairunnisa, Osman, Mohamed Syazwan, Senin, Syahrul Fithry

“…Existing modelling approaches to simulate TMDL allocations of point source and non-point source pollutants typically consist of linking watershed model, receiving water transport model, and receiving water quality model. …”
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Prediction of Total Suspended Sediments in Penang Waters Using Remote Sensing by Tan, Sek Aun

“…Besides the derived algorithm, models suggested by other researchers were tested in this study. …”
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