Search Results - (( parameter optimization method algorithm ) OR ( spatial information based algorithm ))
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1
A buffer-based online clustering for evolving data stream
Published 2019“…In addition, BOCEDS proposes an online micro-cluster energy-updating function based on the spatial information of the data stream. …”
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2
Multimodality registration of two-dimensional echocardiography and cardiac CT for mitral valve diagnosis and surgical planning
Published 2024journal::journal article -
3
Task-state EEG signal classification for spatial cognitive evaluation based on multiscale high-density convolutional neural network
Published 2022“…Secondly, to enhance feature propagation and reduce the number of parameters, the dense network was connected after the multi-scale convolutional network, and the learning rate change function of the stochastic gradient descent algorithm was optimized to objectively evaluate the training effect. …”
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4
A joint Bayesian optimization for the classification of fine spatial resolution remotely sensed imagery using object-based convolutional neural networks
Published 2022“…A Bayesian technique was used to find the best parameters for the multiresolution segmentation (MRS) algorithm while the CNN model learns the image features at different layers, achieving joint optimization. …”
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5
Multimodality registration of two-dimensional echocardiography and cardiac CT for mitral valve diagnosis and surgical planning
Published 2024“…For spatial registration, an intensity-based normalized mutual information method was applied with a pattern search optimization algorithm to produce an interpolated cardiac CT image. …”
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6
On-orbit spatial image characterisation and restoration based on stochastic characteristic targets / Wong Soo Mee
Published 2021“…The experimental results demonstrate that the proposed framework is practical and effective, with < 2.3% of relative error at the Nyquist frequency as compared to the well-established edge method. In continuation of the first framework, the proposed MTF measurement algorithms are evaluated experimentally as a blur kernel estimation method for spatially varying and invariant blur removal. …”
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7
Time series modeling of water level at Sulaiman Station, Klang River, Malaysia
Published 2010“…The estimation of parameters of the model is accomplished using the hybrid learning algorithm consisting of standard neural network backpropagation algorithm and least squares method. …”
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8
Development of a registration framework for echocardiography and computed tomography cardiovascular image fusion / Azira Khalil
Published 2018“…Next, in the preprocessing phase, the noise of echocardiography image is reduced using the speckle reducing anisotropic diffusion (SRAD) technique. For the spatial registration, an intensity-based normalized mutual information (NMI) method is applied with pattern search optimization algorithm to produce an interpolated cardiac CT image. …”
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9
An extended ID3 decision tree algorithm for spatial data
Published 2011“…As in the ID3 algorithm that use information gain in the attribute selection, the proposed algorithm uses the spatial information gain to choose the best splitting layer from a set of explanatory layers. …”
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10
Landslide susceptibility mapping using decision-tree based chi-squared automatic interaction detection (CHAID) and logistic regression (LR) integration
Published 2014“…This new algorithm was developed to overcome the subjectivity of the manual categorization of scale data of landslide conditioning factors, and to predict rainfall-induced susceptibility map in Kuala Lumpur city and surrounding areas using geographic information system (GIS). …”
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11
Classification model for hotspot occurrences using spatial decision tree algorithm
Published 2013“…As the ID3 algorithm that uses information gain in the attribute selection, the proposed algorithm uses spatial information gain to choose the best splitting layer from a set of explanatory layers. …”
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12
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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13
Parameters optimization of surface grinding process with particles swarm optimization, gravitational search, and sine cosine algorithms: a comparative analysis
Published 2018“…The efficiency of the three algorithms are evaluated and compared with previous results obtained by other optimization methods on similar studies. …”
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14
Optimization of PID parameters for hydraulic positioning system utilizing variable weight Grey-Taguchi and particle swarm optimization
Published 2014“…Particle swarm optimization algorithm (PSO) is one of the artificial intelligence methods. …”
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15
Optimization of turning parameters using ant colony optimization
Published 2008“…The project objectives are to develop Ant Colony Optimization (ACO) algorithm for CNC turning process and to optimize turning parameters for minimized production cost per unit. …”
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16
Parameter estimation in double exponential smoothing using genetic algorithm / Foo Fong Yeng, Lau Gee Choon and Zuhaimy Ismail
Published 2014“…Trial and error often serves as the best method to determine the parameter. Therefore, a good optimization technique is required for identify the best parameter in minimizing the forecast errors. …”
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17
Fitness-guided particle swarm optimization with adaptive Newton-Raphson for photovoltaic model parameter estimation
Published 2025Subjects:Article -
18
Application Of Genetic Algorithms For Robust Parameter Optimization
Published 2010“…Genetic algorithms (GA) are fairly recent in this respect but afford a novel method of parameter optimization. …”
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19
Optimization of PID Parameters Utilizing Variable Weight Grey-Taguchi Method and Particle Swarm Optimization
Published 2017“…Particle swarm optimization algorithm (PSO) is one of the artificial intelligence methods. …”
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20
Inversed Control Parameter in Whale Optimization Algorithm and Grey Wolf Optimizer for Wrapper-Based Feature Selection: A Comparative Study
Published 2023“…—Whale Optimization Algorithm (WOA) and Grey Wolf Optimizer (GWO) are well-perform metaheuristic algorithms used by various researchers in solving feature selection problems. …”
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