Search Results - (( basic localization based algorithm ) OR ( using estimation using algorithm ))
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Image watermarking optimization algorithms in transform domains and feature regions
Published 2012“…Recently,the strategy of researchers has introduced image watermarking techniques using the invariant transforms for their rotation and scale invariant properties.However,it suffers from local transformations which make watermarks difficult to recover.This thesis will introduce a set of content based image watermarking schemes which can resist both local geometric attacks and traditional signal processingattacks simultaneously. …”
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2
Enhancing navigation accuracy of Turtlebot3 Burger mobile robot
Published 2024“…To address this challenge, the Kalman Filter algorithm is implemented in this robot, as it is widely used for mobile robot navigation and system integration. …”
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Conference or Workshop Item -
3
A hybrid range-free algorithm using dynamic communication range for wireless sensor networks
Published 2020“…Distance-Vector Hop (DV-Hop) is a representative range-free localization algorithm, which is widely utilized to locate node position in location-based application. …”
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Fuzzy adaptive teaching learning-based optimization for solving unconstrained numerical optimization problems
Published 2022“…The performance of the fuzzy adaptive teaching learning-based optimization is evaluated against other metaheuristic algorithms including basic teaching learning-based optimization on 23 unconstrained global test functions. …”
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Block based motion vector estimation using fuhs16 uhds16 and uhds8 algorithms for video sequence
Published 2011“…Based on the theoretical and fundamental research analysis the FUHS16 and UHDS16 algorithms using 16 × 16 block-based motion estimation formulations were developed. …”
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Book Chapter -
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Development an accurate and stable range-free localization scheme for anisotropic wireless sensor networks
Published 2022“…Nevertheless, as the representative range-free localization scheme, Distance Vector-Hop (DV-Hop) localization algorithm demonstrates extremely poor localization accuracy under anisotropic wireless sensor networks. …”
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8
Local search manoeuvres recruitment in the bees algorithm
Published 2011“…Swarm intelligence of honey bees had motivated many bioinspired based optimisation techniques. The Bees Algorithm (BA) was created specifically by mimicking the foraging behavior of foraging bees in searching for food sources.During the searching, the original BA ignores the possibilities of the recruits being lost during the flying.The BA algorithm can become closer to the nature foraging behavior of bees by taking account of this phenomenon.This paper proposes an enhanced BA which adds a neighbourhood search parameter which we called as the Local Search Manoeuvres (LSM) recruitment factor.The parameter controls the possibilities of a bee extends its neighbourhood searching area in certain direction.The aim of LSM recruitment is to decrease the number of searching iteration in solving optimization problems that have high dimensions.The experiment results on several benchmark functions show that the BA with LSM performs better compared to the one with basic recruitment.…”
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System identification using Extended Kalman Filter
Published 2017“…The EKF algorithm performance was compared with Recursive Least Square (RLS) estimation algorithm as a comparison algorithm performance. …”
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Student Project -
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Vision Based Calibration and Localization Technique for Video Sensor Networks
Published 2009“…Very few of these localization algorithms use vision based technique. …”
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Indoor positioning using weighted magnetic field signal distance similarity measure and fuzzy based algorithms
Published 2021“…Therefore, for the second objective, another algorithm named the fuzzy algorithm is designed which combines the clustering algorithm, matching algorithm, triangle area algorithm and average Euclidean algorithm used to estimate location. …”
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12
Cyclic Path Planning Of Hyper-Redundant Manipulator Using Whale Optimization Algorithm
Published 2023Article -
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Hierarchical Bayesian estimation for stationary autoregressive models using reversible jump MCMC algorithm
Published 2018“…The performance of the algorithm is tested by using simulated data. The test results show that the algorithm can estimate the order and coefficients of the autoregressive model very well. …”
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Estimation in spot welding parameters using genetic algorithm
Published 2007“…By using Genetic algorithm (GA) the spot welding parameters can be estimated.…”
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Implementation of a modified incremental conductance MPPT algorithm with direct control based on a fuzzy duty cycle change estimator using dSPACE
Published 2014“…A fuzzy logic estimator (FLE) is used to estimate the new duty cycle used to track the PV array maximum power point. …”
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Evaluation of a spacecraft attitude and rate estimation algorithm
Published 2010“…Practical implications: Because the simulation set‐up is clearly stated, the results of this evaluation can be used as a benchmark for other estimation algorithms. …”
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Simulated Kalman Filter algorithms for solving optimization problems
Published 2019“…These algorithms are inspired by the estimation capability of the well-known Kalman filter estimation method. …”
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Stator resistance estimation of induction motor using genetic algorithm
Published 2012“…This project is about to design genetic algorithm estimator using MATLAB software, and builds an actual induction motor using Newcastle University Drives Simulation Library. …”
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Undergraduates Project Papers -
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Comparison of machine learning algorithms for estimating mangrove age using sentinel 2A at Pulau Tuba, Kedah, Malaysia / Fareena Faris Francis Singaram
Published 2021“…Therefore, this study aimed to used OBIA method with selected machine learning algorithm to estimate the mangrove age by using Sentinel 2A image. …”
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Application of artificial neural network genetic algorithm in inferential estimation and control of a distillation column
Published 2005“…Adaptation of network weights using Genetic Algorithm (GA) was proposed as a mechanism to improve the performance of Artificial Neural Network (ANN) inferential estimator. …”
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