Search Results - (( waste recognition algorithm ) OR ( waste ((recognition algorithm) OR (prediction algorithm)) ))

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…”

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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Computer algorithm for automated detection of intramedullary rod hole position and orientation / Ahmad Zulhilmi Mohd Ziyadi by Mohd Ziyadi, Ahmad Zulhilmi

“…Therefore to close the gap between manual and automatic, automatic image recognition system using machine vision algorithm must be developed. …”
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Recyclable waste classification using YOLO-based Convolutional Neural Network (CNN) / Shaharil Armin Sharizal by Sharizal, Shaharil Armin

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Evaluating endpoint detection algorithms for isolated word from Malay parliamentary speech by Seman N., Bakar Z.A., Bakar N.A., Mohamed H.F., Abdullah N.A.S., Ramakrisnan P., Ahmad S.M.S.

“…As a result, the Hidden Markov Model (HMM) recognizer derived the recognition accuracy rate of 91.4% for combination of both algorithms, if compared only 86.3% for STE and 82.1% for STZC rate alone. …”

Mobile tour guide application with attraction recognition for UTAR Kampar campus by Lee, Mun Hong

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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. ? …”

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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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.

“…All the input variables significantly influence the predicted biohydrogen. However, waste glycerol has the most significant effects. …”
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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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Characterization of dumping soil and settlement prediction using Monte Carlo approach by Mohd Pauzi, Nur Irfah

“…Dumping soil are characterize based on its characteristics such as Category I:soil like and non soil like, Category II: waste types and Category III: waste or soil. The importance of dumping soil characterization are that it helps the engineer to differentiate between soil and non soil like, the types of waste and to determine whether the soil mostly contains waste or soil. …”
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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.

Jaya algorithm hybridized with extreme gradient boosting to predict the corrosion-induced mass loss of agro-waste based monolithic and Ni-reinforced porous alumina by Dele-Afolabi, T.T., Jung, D.W., Ahmadipour, Masoud, Azmah Hanim, M.A., Adeleke, A.O., Kandasamy, M., Gunnasegaran, Prem

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Neural network prediction for efficient waste management in Malaysia 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 population growth factor. …”
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Using predictive analytics to solve a newsvendor problem / S. Sarifah Radiah Shariff and Hady Hud by Shariff, S. Sarifah Radiah, Hud, Hady

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