Search Results - (( wave optimization method algorithm ) OR ( variable estimation based algorithm ))
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1
Inversion Of Surface Wave Phase Velocity Using New Genetic Algorithm Technique For Geotechnical Site Investigation
Published 2011“…Therefore the use of genetic algorithm (GA) optimization technique which is one of nonlinear optimization methods is an appropriate choice to solve surface wave inversion problem having high nonlinearity and multimodality. …”
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2
Optimizing the efficiency of Oscillating Water Column (OWC) wave energy converter using genetic algorithm
Published 2015“…This paper, describes a method to maximize the pneumatic system efficiency using optimization technique based on Genetic algorithm. …”
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3
Low computational complexity for optimizing energy efficiency in mm-wave hybrid precoding system for 5G
Published 2021“…We propose effective alternating minimization algorithms based on the zero gradient method to establish fully-connected structures (FCSs) and partially-connected structures (PCSs). …”
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4
Low computational complexity for optimizing energy efficiency in mm-wave hybrid precoding system for 5G
Published 2021“…We propose effective alternating minimization algorithms based on the zero gradient method to establish fully-connected structures (FCSs) and partially-connected structures (PCSs). …”
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5
Variable block based motion estimation using hexagon diamond full search algorithm (HDFSA) via block subtraction technique
Published 2015“…The fixed block matching uses the same block size throughout the motion estimation process while the variable block matching uses different block size. …”
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6
Heuristic optimization-based wave kernel descriptor for deformable 3D shape matching and retrieval
Published 2018“…This paper presents an optimized wave kernel signature (OWKS) using a modified particle swarm optimization (MPSO) algorithm. …”
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Heuristic optimization-based wave kernel descriptor for deformable 3D shape matching and retrieval
Published 2018“…This paper presents an optimized wave kernel signature (OWKS) using a modified particle swarm optimization (MPSO) algorithm. …”
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8
Robust diagnostics and variable selection procedure based on modified reweighted fast consistent and high breakdown estimator for high dimensional data
Published 2022“…A modified reweighted fast consistent and high breakdown (MRFCH) estimator in high dimensional data based on the diagonal elements of the scatter matrix instead of its entire elements in the computation of robust Mahalanobis distance within the RFCH algorithm is developed. …”
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9
Control of IC Engine: Design a Novel MIMO Fuzzy Backstepping Adaptive Based Fuzzy Estimator Variable Structure Control.
Published 2011“…The fuzzy controller in proposed fuzzy estimator variable structure controller is based on Lyapunov fuzzy inference system (FIS) with minimum model based rule base. …”
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10
A generalized laser simulator algorithm for optimal path planning in constraints environment
Published 2022“…The results demonstrated that the proposed method could generate an optimal collision-free path. …”
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11
Assessment of forest aboveground biomass estimation from superview-1 satellite image using machine learning approaches / Azinuddin Mohd Asri
Published 2022“…The suitable independent variables (hL, DBH, and CPA) were vital to estimating the dependent variable (Sc) and producing a carbon stock map for the final result. …”
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12
Interferometric array planning using division algorithm for radio astronomy applications
Published 2017“…In the second scheme, a genetic algorithm is developed, in order to optimize a correlator array of antennas by using Genetic Algorithm (GA). …”
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13
Gooseneck barnacle optimization algorithm: A novel nature inspired optimization theory and application
Published 2024“…In contrast to the previously published Barnacle Mating Optimizer (BMO) algorithm, GBO more accurately captures the unique static and dynamic mating behaviours specific to gooseneck barnacles. …”
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14
Railway wheelset parameter estimation using signals from lateral velocity sensor
Published 2008“…The algorithm includes an instrumental variable (IV) element to reduce estimation bias and a variable forgetting factor for good parameter tracking and smooth steady state. …”
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15
Robust variable selection methods for large- scale data in the presence of multicollinearity, autocorrelated errors and outliers
Published 2016“…The stability procedure based on RFCH estimator is therefore developed. The results of the study show that our propose Robust Multi Split based on RFCH successfully and consistently select the correct variables in the final model. …”
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16
An Ultrasound-Assisted System For The Optimization Of Biodiesel Production From Chicken Fat Oil Using A Genetic Algorithm And Response Surface Methodology
Published 2015“…The time reduction for the ultrasonic method compared to the conventional method makes the ultrasonic method superior.…”
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17
Artificial Robust Control of Robot Arm: Design a Novel SISO Backstepping Adaptive Lyapunov Based Variable Structure Control.
Published 2011“…The proposed approach effectively combines the design technique from variable structure controller is based on Lyapunov and fuzzy estimator to estimate the nonlinearity of undefined system dynamic in backstepping controller. …”
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18
Deep Learning-Driven Mobility And Utility-Based Resource Management In Mm-Wave Enable Ultradense Heterogeneous Networks
Published 2025thesis::doctoral thesis -
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Robust Estimation Methods And Outlier Detection In Mediation Models
Published 2010“…Mediation models refer to the relationships among three variables: an independent variables (IV), a potential mediating variable (M), and a dependent variable (DV). …”
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20
Long-term electrical energy consumption: Formulating and forecasting via optimized gene expression programming / Seyed Hamidreza Aghay Kaboli
Published 2018“…In the developed feature selection approach, multi-objective binary-valued backtracking search algorithm (MOBBSA) is used as an efficient evolutionary search algorithm to search within different combinations of input variables and selects the non-dominated feature subsets, which minimize simultaneously both the estimation error and the number of features. …”
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