Search Results - (( data extraction means algorithm ) OR ( parameter optimization based algorithm ))
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Individual-tree segmentation and extraction based on LiDAR point cloud data
Published 2024“…The objective was to identify the optimal parameters for both algorithms in terms of tree height extraction precision. …”
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Towards enhanced remaining useful life prediction of lithium-ion batteries with uncertainty using optimized deep learning algorithm
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Zero root-mean-square error for single- and double-diode photovoltaic models parameter determination
Published 2022“…In this work, a new improved arithmetic optimization method based on the adaption of Newton–Raphson and Levenberg–Marquardt damping parameter (IAOANRaLMp) is presented to globally extract the parameter of the single- and double-diode PV models. …”
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Modeling, Testing and Experimental Validation of Laser Machining Micro Quality Response by Artificial Neural Network
Published 2009“…Experimentally observed responses were used to train, map and optimize the network algorithms before the best architecture was selected. …”
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Development of an islanding detection scheme based on combination of slantlet transform and ridgelet probabilistic neural network in distributed generation
Published 2019“…Then, by means of the Slantlet Transform theory, the matrix data extraction for any decomposition level are computed and the best of them are selected as input data to feed to an effective classifier. …”
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Optimization of Microbial Electrolysis Cell for Sago Mill Wastewater Derived Biohydrogen via Modeling and Artificial Neural Network
Published 2023“…Model validity describes the first sub-objective, which is to solve the complexity of the nonlinear interaction of multiple MEC input variables related to the hydrogen production rate response using artificial neural networks (ANN) before validating the mathematical modeling results by comparing experimental data with the predicted substrate concentration profile and hydrogen production rate profile based on the re-estimated input values of the model parameters using single-objective optimization based on the nonlinear convex method using gradient descent algorithm. …”
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Intelligent grading of agarwood essential oil quality using artificial neural network (ANN) / Noratikah Zawani Mahabob
Published 2022“…The training and validation of the ANN was based on optimization of its training parameters and guided by the convergence of the mean squared errors (MSE). …”
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Machine-learning-based adaptive distance protection relay to eliminate zone-3 protection under-reach problem on statcom-compensated transmission lines
Published 2020“…This current study proposes an intelligent data mining approach for the Machine Learning- Adaptive Distance Relay (ML-ADR) fault classification model using novel extracted 1-cycle transient voltage and current signals hidden knowledge from both healthy and faulty lines parameters. …”
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Context enrichment framework for sentiment analysis in handling word ambiguity resolution
Published 2024“…However, ambiguous words pose a challenge for sentiment analysis algorithms as they require the identification of the correct meaning and word polarity within a specific context. …”
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Integrated optimal control and parameter estimation algorithms for discrete-time nonlinear stochastic dynamical systems
Published 2011“…The main idea is the integration of optimal control and parameter estimation. In this work, a simplified model-based optimal control model with adjustable parameters is constructed. …”
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On Adopting Parameter Free Optimization Algorithms for Combinatorial Interaction Testing
Published 2015“…In doing so, this paper reviews two existing parameter free optimization algorithms involving Teaching Learning Based Optimization (TLBO) and Fruitfly Optimization Algorithm (FOA) in an effort to promote their adoption for CIT.…”
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Finite impulse response optimizers for solving optimization problems
Published 2019“…Selecting optimal parameters’ values may improve an algorithm’s performance. …”
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Finite impulse response optimizers for solving optimization problems
Published 2019“…Selecting optimal parameters’ values may improve an algorithm’s performance. …”
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LS-SVM Hyper-parameters Optimization Based on GWO Algorithm for Time Series Forecasting
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Conference or Workshop Item -
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Enhanced gravitational search algorithm for nano-process parameter optimization problem / Norlina Mohd Sabri
Published 2020“…Based on the capabilities of the metaheuristic algorithms, this research is proposing the enhanced Gravitational Search Algorithm (eGSA) to solve the nano-process parameter optimization problem. …”
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Optimization of turning parameters using genetic algorithm method
Published 2008“…This study about development of optimization for turning parameters based on the Genetic Algorithm (GA). …”
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Undergraduates Project Papers -
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Optimization of milling parameters using ant colony optimization
Published 2008“…The simulation based on ACO algorithm are successful develop and the optimization of parameters values is to maximize the production rate is obtain from the simulation.…”
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Undergraduates Project Papers
