Search Results - (( partner selection method algorithm ) OR ( parameter evaluation method algorithm ))*

Optimization of support vector machine parameters in modeling of Iju deposit mineralization and alteration zones using particle swarm optimization algorithm and grid search method by Abbaszadeh M., Soltani-Mohammadi S., Ahmed A.N.

Lithium-ion Battery State of Charge Estimation Method Using Optimized Deep Recurrent Neural Network Algorithm by Lipu M.S.H., Hannan M.A., Hussain A., Saad M.H.M., Ayob A., Muttaqi K.M.

Modeling and Analysis of New Hybrid Clustering Technique for Vehicular Ad Hoc Network by Abdulrazzak H.N., Hock G.C., Mohamed Radzi N.A., Tan N.M.L., Kwong C.F.

“…To address these problems, a novel method combining a covering rough set and a K-Means clustering algorithm (RK-Means) was proposed in this paper. …”

Application of Decision Tree Algorithm for Predicting Monthly Pan Evaporation Rate by Abed M., Imteaz M.A., Ahmed A.N., Huang Y.F.

Prediction of Oil Palm Yield Using Machine Learning in the Perspective of Fluctuating Weather and Soil Moisture Conditions: Evaluation of a Generic Workflow by Khan N., Kamaruddin M.A., Ullah Sheikh U., Zawawi M.H., Yusup Y., Bakht M.P., Mohamed Noor N.

“…The performance of two top regression models, namely Extra Tree and AdaBoost was evaluated using six statistical evaluation metrics. …”

Enhancement and assessment of WKS variance parameter for intelligent 3D shape recognition and matching based on MPSO by Naffouti, S.E., Aouissaoui, I., Fougerolle, Y., Sakly, A., Meriaudeau, F.

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Recent advancement of remaining useful life prediction of lithium-ion battery in electric vehicle applications: A review of modelling mechanisms, network configurations, factors, a... by Reza M.S., Mannan M., Mansor M., Ker P.J., Mahlia T.M.I., Hannan M.A.

“…However, achieving precise RUL prediction for electric vehicles presents a challenging task due to several issues related to intricate operational characteristics and dynamic shifts in model parameters throughout the aging process, battery parameters data extraction, data preprocessing, and hyperparameters tuning of the prediction model. …”

Seismic attribute feasibility study for fault and fracture analysis and integration with spectral decomposition: Application in Sarawak basin by Hamidi, R., Ghosh, D.

“…Comparing each pair of conventional vs. spectral assisted attributes shows enhancement of the results (more details and better resolution) in all evaluated seismic attributes with the proposed method. …”
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Artificial Bee Colony for Minimizing the Energy Consumption in Mobile Ad Hoc Network by Tareq, M., Abed, S.A., Sundararajan, E.A.

“…The evaluation is based on node speed and packet size topology parameters. …”
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Applications of IoT and Artificial Intelligence in Water Quality Monitoring and Prediction: A Review by Mustafa H.M., Mustapha A., Hayder G., Salisu A.

Modelling monthly pan evaporation utilising Random Forest and deep learning algorithms by Abed M., Imteaz M.A., Ahmed A.N., Huang Y.F.

Application of Machine Learning and Deep Learning Algorithms for Landslide Susceptibility Assessment in Landslide Prone Himalayan Region by Bhattacharya S., Ali T., Chakravortti S., Pal T., Majee B.K., Mondal A., Pande C.B., Bilal M., Rahman M.T., Chakrabortty R.

“…In recent years, statistical methods and, increasingly, machine learning-based approaches have gained popularity for landslide susceptibility modeling. …”

Predicting the maturity and organic richness using artificial neural networks (ANNs): A case study of Montney Formation, NE British Columbia, Canada by Barham, A., Ismail, M.S., Hermana, M., Padmanabhan, E., Baashar, Y., Sabir, O.

“…Total Organic Carbon (TOC) and maturity level (Tmax) for any source rock considered to be the key parameters for evaluating its potentiality. The TOC and Tmax are estimated mainly by analyzing core samples or cuttings using the common nonfilter acidification combustion and pyrolysis, both methods are time-consuming and costly. …”
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Predicting the maturity and organic richness using artificial neural networks (ANNs): A case study of Montney Formation, NE British Columbia, Canada by Barham A., Ismail M.S., Hermana M., Padmanabhan E., Baashar Y., Sabir O.

Developing an ensembled machine learning model for predicting water quality index in Johor River Basin by Sidek L.M., Mohiyaden H.A., Marufuzzaman M., Noh N.S.M., Heddam S., Ehteram M., Kisi O., Sammen S.S.

“…Then, in terms of WQI calculation, feature importance method is used to identify the most important parameters that can be used to predict the WQI. …”

Investigating the influence of meteorological parameters on the accuracy of sea-level prediction models in Sabah, Malaysia by Muslim T.O., Ahmed A.N., Malek M.A., Afan H.A., Ibrahim R.K., El-Shafie A., Sapitang M., Sherif M., Sefelnasr A., El-Shafie A.

Parameter extraction of photovoltaic module using hybrid evolutionary algorithm by Muhsen D.H., Ghazali A.B., Khatib T.

Taguchi-Grey Relational Analysis Method for Parameter Tuning of Multi-objective Pareto Ant Colony System Algorithm by Muthana, Shatha Abdulhadi, Ku Mahamud, Ku Ruhana

“…The gray relational grade (GRG) performance metric and the Friedman test were used to evaluate the algorithm’s performance. The Taguchi-GRA method that produced the new values for the algorithm’s parameters was shown to be able to provide a better multi-objective generator maintenance scheduling (GMS) solution. …”
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Opposition-Based Learning Binary Bat Algorithm as Feature Selection Approach in Taguchi's T-Method by Marlan Z.M., Jamaludin K.R., Harudin N.

Evaluation of lightning current parameters using measured lightning induced voltage on distribution power lines by Izadi, Mahdi, Ab Kadir, Mohd Zainal Abidin, Osman, Miszaina

“…In this paper, an algorithm had been proposed to evaluate the lightning current parameters using measured voltage from overhead distribution lines based on lightning location obtained from lightning location system. …”
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