Search Results - (( waste ((connection algorithm) OR (conversion algorithm)) ) OR ( waste prediction algorithm ))

Data-Driven Approach to Modeling Biohydrogen Production from Biodiesel Production Waste: Effect of Activation Functions on Model Configurations by Hossain, S.K.S., Ayodele, B.V., Alhulaybi, Z.A., Alwi, M.M.A.

“…One such process used for waste glycerol conversion is the bioprocess, whereby thermophilic microorganisms are utilized. …”
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Handover Decision-Making Algorithm for 5G Heterogeneous Networks by Mark Irwin Goh, Abbas Ibrahim Mbulwa, Hoe, Tung Yew, Aroland Kiring, Chung, Seng Kheau, Ali Farzamnia, Ali Chekima, Manas Kumar Haldar

“…The proposed algorithm reduces the number of unnecessary handovers by estimating the connection time to a small cell network using the dwell time prediction technique. …”
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Bayesian optimized multilayer perceptron neural network modelling of biochar and syngas production from pyrolysis of biomass-derived wastes by Kanthasamy, R., Almatrafi, E., Ali, I., Hussain Sait, H., Zwawi, M., Abnisa, F., Choe Peng, L., Victor Ayodele, B.

“…This study employs Bayesian optimized multilayer perceptron neural network for modelling the prediction of biochar and syngas from pyrolysis of biomass-derived wastes. …”
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Prediction of generated power from steam turbine waste heat recovery mechanism system on naturally aspirated spark ignition engine using artificial neural network by Herawan, Safarudin Gazali, Talib, Kamarulhelmy, Putra, Azma, Ismail, Ahmad Faris, Shamsudin, Shamsul Anuar, Musthafah, Mohd Tahir

“…This paper proposes a prediction model on the performance of a naturally aspirated spark ignition engine equipped with a waste heat recovery mechanism (WHRM) using steam turbine mechanism. …”
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Development of a fuzzy multi-objective mathematical model for hazardous waste location-routing problem by Hassani, Omid Boyer

“…The generated hazardous waste quantity is not predictable precisely. Therefore, amount of waste is uncertain parameter. …”
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Performance of amidoxime-modified poly(acrylonitrile- Co-acrylic acid) for removal of boron in aqueous solution by Lau, Kia Li

“…Among several models, radial basis function (RBF) with orthogonal least square (OLS) algorithm displays good prediction on boron adsorption behaviour with mean square error (MSE) and coefficient of determination (R²) at 0.000209 and 0.9985, respectively. …”
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Artificial Neural Network-Forecasted Compression Strength of Alkaline-Activated Slag Concretes by Yi, Xuan Tang, Yeong, Huei Lee, Mugahed, Amran, Roman, Fediuk, Nikolai, Vatin, Beng, Ahmad Hong Kueh, Yee, Yong Lee

“…The prediction accuracy of the optimal ANN model was then compared to existing ANN-based models, while the variable selection was compared to existing AASC models with other machine learning algorithms, due to limitations in the ANN-based model. …”
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Early Admission Selection Process Into Sixth Form Science Streams Using Neural Networks Model by Wong, Tuck Sung

“…A neural networks solution, using Multi Layer Perceptron (MLP) and Steepest Gradient Descent algorithm, was studied to offer a better model to select students more meticulously. …”
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Evaluating different machine learning models for predicting municipal solid waste generation: a case study of Malaysia by Latif S.D., Hazrin N.A.B., Younes M.K., Ahmed A.N., Elshafie A.

“…This study managed to fill in the gap of using GPR for predicting municipal solid waste generation. The outcome of this study could be of direct interest to public and private solid waste management companies in order to effectively manage solid waste through predicting the municipal solid waste generation accurately. ? …”

A hybrid P-graph and WEKA approach in decision-making: waste conversion technologies selection by Ali, Rabiatul Adawiyah, Nik Ibrahim, Nik Nor Liyana, Wan Abdul Karim Ghani, Wan Azlina, Sani, Nor Samsiah, Hon, Loong Lam

“…The focus of user interface for selection of waste conversion technologies. As a result, the model can be used to determine the best municipal solid waste conversion technology.…”
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DeMI interface tool for profit estimation and waste conversion technology recommendations in enhancing municipal solid waste management by Ali, R.A., Nik Ibrahim, N.N.L., Ghani, W.A.W.A.K., Sani, N.S., Lam, H.L.

“…The M5P algorithm, adept at profit estimation, establishes correlations between MSW weight and profitability, while the J48 algorithm offers recommendations for suitable waste conversion technologies based on profit potential. …”
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Design of smart waste bin and prediction algorithm for waste management in household area by Yusoff, Siti Hajar, Abdullah Din, Ummi Nur Kamilah, Mansor, Hasmah, Midi, Nur Shahida, Zaini, Syasya Azra

“…This project has proposed Artificial Neural Network (ANN) based prediction algorithm that can forecast Solid Waste Generation (SWG) based on household size factor. …”
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Predicting municipal solid waste using a coupled artificial neural network with archimedes optimisation algorithm and socioeconomic components by Liang G., Panahi F., Ahmed A.N., Ehteram M., Band S.S., Elshafie A.

ESS-IoT: The Smart Waste Management System for General Household by Wong S.Y., Han H., Cheng K.M., Koo A.C., Yussof S.

“…On the other hand, the waste classification is implemented using two classification algorithms: Random Forest (RF) prediction model and Convolutional Neural Network (CNN) prediction model. …”

Performance analysis of support vector machine, Gaussian Process Regression, sequential quadratic programming algorithms in modeling hydrogen-rich syngas production from catalyzed... by Ayodele, B.V., Mustapa, S.I., Kanthasamy, R., Mohammad, N., AlTurki, A., Babu, T.S.

“…Whereas the best performance in terms of prediction of the syngas composition was obtained using the NLRQM algorithm with an inbuilt SQP and LM algorithms. …”
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Biochar production from valorization of agricultural Wastes: Data-Driven modelling using Machine learning algorithms by Kanthasamy, R., Almatrafi, E., Ali, I., Hussain Sait, H., Zwawi, M., Abnisa, F., Choe Peng, L., Victor Ayodele, B.

“…The artificial neural network-based algorithms outperformed the SVM and GPR as indicated by the R2 > 0.9 and low predictive errors. …”
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A comparative study of clonal selection algorithm for effluent removal forecasting in septic sludge treatment plant by Chun T.S., Malek M.A., Ismail A.R.

“…Algorithms; Artificial intelligence; Biochemical oxygen demand; Bioinformatics; Developing countries; Effluent treatment; Effluents; Forecasting; Least squares approximations; Oxygen; Pattern recognition; Support vector machines; Water quality; Biological oxygen demand; Clonal selection algorithms; Least-square support vector machines; Sludge treatment plants; Total suspended solids; Chemical oxygen demand; oxygen; sewage; algorithm; clone; comparative study; effluent; least squares method; nonlinearity; pattern recognition; simulation; sludge; water treatment; activated sludge; algorithm; Article; biochemical oxygen demand; chemical oxygen demand; clonal selection algorithm; comparative study; computer simulation; effluent; forecasting; pattern recognition; prediction; regression analysis; septic sludge treatment plant; sludge treatment; statistical model; support vector machine; suspended particulate matter; waste water treatment plant; chemistry; procedures; sewage; theoretical model; Algorithms; Biological Oxygen Demand Analysis; Forecasting; Least-Squares Analysis; Models, Theoretical; Sewage; Support Vector Machines; Waste Disposal, Fluid…”

An Ultrasound-Assisted System For The Optimization Of Biodiesel Production From Chicken Fat Oil Using A Genetic Algorithm And Response Surface Methodology by R., Mamat, Fayyazi, E., Ghobadian, B., G., Najafi, Hosseinzadeh, B., Hosseinzadeh, J.

“…Because vegetable oil and animal fat wastes are cheaper, the tendency to produce biodiesel from these materials is increasing. …”
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Performance analysis of support vector machine, Gaussian Process Regression, sequential quadratic programming algorithms in modeling hydrogen-rich syngas production from catalyzed... by Ayodele, B.V., Mustapa, S.I., Kanthasamy, R., Mohammad, N., AlTurki, A., Babu, T.S.

“…Whereas the best performance in terms of prediction of the syngas composition was obtained using the NLRQM algorithm with an inbuilt SQP and LM algorithms. …”
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Waste Prediction in Gross Pollutant Trap Using Machine Learning Approach by Elpina, Sari, Tri Basuki, Kurniawan

“…This research compares 3 algorithms for predicting the amount of waste trapped by GPT: Simple Linear Regression, Multiple Linear Regression, and Polynomial Regression. …”
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