Search Results - (( location selection means algorithm ) OR ( swarm optimization window algorithm ))
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Development of an education simulator for particle swarm optimization in solving economic dispatch problems: article / Mohd Hafiz Mat Hussain
Published 2009“…The developed simulator incorporated particle swarm optimizations (PSO) to solve the ED problems. …”
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Development of an education simulator for particle swarm optimization in solving economic dispatch problems / Mohd Hafiz Mat Hussain
Published 2009“…The developed simulator incorporated particle swarm optimizations (PSO) to solve the ED problems. …”
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3
Enhancement on the modified artificial bee colony algorithm to optimize the vehicle routing problem with time windows
Published 2022“…The Artificial Bee Colony (ABC) is a popular swarm intelligence algorithm for COP. In this study, existing Modified ABC (MABC) algorithm is revised to solve the VRPTW. …”
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4
Mathematical models and optimization algorithms for low-carbon Location-Inventory-Routing Problem with uncertainty
Published 2024“…Given the NP-Hard nature of the three models proposed in this thesis, two metaheuristic algorithms have been developed. A hybrid Particle Swarm Optimization-Bacterial Foraging Algorithm is developed for solving the single objective LIRP model. …”
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Enhanced AI-based anomaly detection method in the intrusion detection system (IDS) / Kayvan Atefi
Published 2019“…In fact a data clustering method is proposed consisting of separate outputs: (i) To select a relevant subset of original features based on our proposed algorithm; which is Enhanced Binary Particle swarm Optimization (EBPSO), (ii) To mine data using various data chunks (windows) and overcome a failure of single clustering. …”
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Modified K-Nearest Neighborhood Algorithm For Optimal Selection Of Distribution Centre In The Disaster Relief Operation
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Kernel and multi-class classifiers for multi-floor wlan localisation
Published 2016“…For fingerprint database optimisation, novel access point (AP) selection algorithms which are based on variant AP selection are investigated to improve computational accuracy compared to existing AP selection algorithms such as Max-Mean and InfoGain. …”
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8
Dynamic Robust Bootstrap Algorithm for Linear Model Selection Using Least Trimmed Squares
Published 2009“…Kallel et al. ( 2002 ) proposed utilizing the bootstrap technique for model selection. They used the classical bootstrap method to estimate the bootstrap location and the scale parameters based on calculating the Mean of Squared Residual (MSR). …”
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9
Indoor positioning using weighted magnetic field signal distance similarity measure and fuzzy based algorithms
Published 2021“…For the triangle area algorithm, the smallest triangle area is selected from the triangle formed from the matching RPs cluster to estimate location. …”
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10
Implementation of machine learning algorithms for streamflow prediction of Dokan dam
Published 2023“…The selected statistical indices are root mean square error (RMSE), mean absolute error (MAE), mean square error (MSE), correlation coefficient (R), and coefficient of determination (R2), Nash Sutcliffe Model Efficiency Coefficient (NSE), and the RMSE-observations standard deviation ratio (RSR). …”
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Determination of the best single imputation algorithm for missing rainfall data treatment
Published 2016“…These algorithms are tested on hourly rainfall data records from six selected rainfall stations located in the Kuantan River Basin. …”
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Determination of the Best Single Imputation Algorithm for Missing Rainfall Data Treatment
Published 2016“…These algorithms are tested on hourly rainfall data records from six selected rainfall stations located in the Kuantan River Basin. …”
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An Improved Wavelet Neural Network For Classification And Function Approximation
Published 2011“…Second, the proposed enhanced fuzzy c-means clustering algorithm—specifically, the modified point symmetry-based fuzzy c-means (MPSDFCM) algorithm—was employed in selecting the locations of the translation vectors of the WNN. …”
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14
An improved energy-efficient clustering protocol to prolong the wireless sensor network lifetime
Published 2021“…Lastly, cluster heads (CHs) are selected in optimal locations with the rotation of the CH function among members of the cluster based on a new CH selection-rotation algorithm by combining a back-off timer mechanism for CH selection and rotation mechanism for CH rotation. …”
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15
Slice sampler and metropolis hastings approaches for bayesian analysis of extreme data
Published 2016“…Here, we have exhaustedly studied all the possible priors for location and scale parameters and come out with a few suggestions for the prior selection of a Gumbel model. …”
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16
Fuzzy genetic algorithms for combinatorial optimisation problems
Published 2012“…The female chromosome is selected by standard tournament selection while the male chromosome is selected based on the hamming distance from the selected female chromosome, fitness value or the active genes. …”
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17
Advanced machine learning algorithm to predict the implication of climate change on groundwater level for protecting aquifer from depletion
Published 2025“…For all five locations, four ML algorithms have been trained, tested, and then evaluated: long short-term memory (LSTM), extreme gradient boost (XGBoost), Artificial Neural Network (ANN), and Support Vector Regression (SVR). …”
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Robust diagnostics and variable selection procedure based on modified reweighted fast consistent and high breakdown estimator for high dimensional data
Published 2022“…However, in practice, high leverage points may lead to misleading results in solving variable selection problems. Therefore, a robust sure independence screening procedure based on the weighted correlation algorithm of MRFCH for high dimensional data is developed to address this problem. …”
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Relevance detection and summarizing strategies identification algorithm using linguistic measures / Seyed Asadollah Abdiesfandani
Published 2016“…Summarization is a process to select important information from a source text. …”
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Replica Creation Algorithm for Data Grids
Published 2012“…DRCM was evaluated using network simulation (OptorSim) based on selected performance metrics (mean job execution time, efficient network usage, average storage usage, and computing element usage), scenarios, and topologies. …”
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