Search Results - (( data optimization method algorithm ) OR ( parameter extraction process algorithm ))
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Parameter extraction of single, double, and three diodes photovoltaic model based on guaranteed convergence arithmetic optimization algorithm and modified third order Newton Raphso...
Published 2022“…Extraction of the photovoltaic (PV) model parameters is critical for forecasting these systems’ energy output. …”
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A new model for iris data set classification based on linear support vector machine parameter's optimization
Published 2020“…In this study, we proposed a newly mode for classifying iris data set using SVM classifier and genetic algorithm to optimize c and gamma parameters of linear SVM, in addition principle components analysis (PCA) algorithm was use for features reduction.…”
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Machine learning in botda fibre sensor for distributed temperature measurement
Published 2023“…Therefore, this thesis explores the comparative analysis for BOTDA data processing using the six most suited machine learning algorithms. …”
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Development of a scaled conjugate gradient algorithm for significant RF neural signal processing
Published 2025“…Scale Conjugate Gradient (SCG) algorithm is an efficient training method for ANN that accelerates the learning process and improves output accuracy. …”
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Improvement on rooftop classification of worldview-3 imagery using object-based image analysis
Published 2019“…A spatio-statistical optimization technique that combines the Taguchi statistical method and a spatial plateau objective function (POF) was presented to improve the segmentation procedures for building footprint extraction. …”
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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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PSO modelling and PID controlled of automatic fish feeder system
Published 2020“…The main objective of this study is to improve the performance of fish feeding system by using PID controller through ARX modelling. In this study, raw data at distribution part with speed of 130 rpm, 160 rpm, 190 rpm, 220 rpm and 250 rpm were extracted and used to determine ARX equation parameters as transfer function by using PSO algorithm to optimize ARX model parameter. …”
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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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Development of an islanding detection scheme based on combination of slantlet transform and ridgelet probabilistic neural network in distributed generation
Published 2019“…In order to train Ridgelet probabilistic neural network, a modified differential evolution algorithm with new mutation phase, crossover process, and selection mechanism is introduced. …”
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Modelling of Liquid-liquid Equilibrium Behaviour of Aqueous Two-Phase Polymer Mixture System for Protein Extraction
Published 2007“…We solve the minimization problem using the modified Shor's R-algorithm for non-smooth optimization [3,4]. We compare our results with the calculations of Johansson et al. [5] and the experimental data of Albertsson et al. [6].…”
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AQUEOUS TWO-PHASE POLYMER MIXTURE SYSTEM AS PROTEIN XTRACTION TECHNIQUE. MODELLING OF PROTEIN PARTITIONING BEHAVIOR
Published 2007“…Aqueous Two-Phase Extraction System has the otential as an efficient yet inexpensive, large-scale extraction for high-value proteins as it provides a mild environment for proteins, allows integration with upstream process, offers high yield and eliminates a large portion of the contaminating lysate. …”
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Context enrichment framework for sentiment analysis in handling word ambiguity resolution
Published 2024“…For classification performances, optimization of machine learning parameters and exploration of deep learning approaches can be applied for further enhancement.…”
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Operational structural damage identification using de-noised modal feature in machine learning / Chen Shilei
Published 2021“…Machine learning is also a focus in this work, which was employed to process and classify FRF data in terms of damage. …”
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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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VLSI floor planning optimization using genetic algorithm and cross entropy method / Angeline Teoh Szu Fern
Published 2012“…These two models are based on topological placement method. DM is optimized using genetic algorithm (GA). …”
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Data-driven continuous-time Hammerstein modeling with missing data using improved Archimedes optimization algorithm
Published 2024“…This research introduces the improved Archimedes optimization algorithm (IAOA) for data-driven modeling of continuous-time Hammerstein models with missing data. …”
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ANALYSIS AND OPTIMIZATION OF HYDROCYCLONE GEOMETRY USING BOX-BEHNKEN AND MULTI-OBJECTIVE OPTIMIZATION ALGORITHM
Published 2021“…However, the process of designing an optimal hydrocyclone is difficult due to its sensitivity to many parameters such as geometrical dimensions and operational parameters which is still lacking. …”
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