Search Results - (( using function based algorithm ) OR ( basic (equalization OR localization) based algorithm ))
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1
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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Nomadic people optimizer (NPO) for large-scale optimization problems
Published 2019“…The basic component of the algorithm consists of several clans and each clan searches for the best place (or best solution) based on the position of their leader. …”
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3
Global Algorithms for Nonlinear Discrete Optimization and Discrete-Valued Optimal Control Problems
Published 2009“…Then, we construct an auxiliary function, called a discrete filled function, at this local minimizer. …”
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Adaptive mechanism for enhanced performance of shark smell optimization / Nur Atharah Kamarzaman, Shahril Irwan Sulaiman and Intan Rahayu Ibrahim
Published 2021“…Numerical results indicate that the ASSO algorithm strategy outperforms the basic SSO algorithm, Genertic Algorithm (GA), Particle Swarm Intelligence (PSO), Firefly Algorithm (FA), Artificial Bee Colony (ABC) and Teaching Learning Based Optimization (TBLO) in term of reaching for global solution.…”
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An enhanced minimum variance distortionless response beamformer techniques to reduce interference in array antenna system
Published 2017“…Metaheuristic optimization algorithms are used widely to solve many engineering problems. …”
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6
Simulation on Emotion Recognition for Autism Therapy
Published 2017“…This paper mainly focusing on the simulation of emotion recognition software based on the Local Binary Pattern (LBP) algorithm to extract the features from the image. …”
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Final Year Project -
7
A Survey Of Supervised Machine Learning In Wireless Sensor Network: A Power Management Perspective
Published 2013“…Machine learning algorithms are iteration based algorithms, as the new knowledge is based on the previous predicted /calculated knowledge which helps to decrease errors in order to increase efficiency. …”
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8
Hybrid-discrete multi-objective particle swarm optimization for multi-objective job-shop scheduling
Published 2022“…This research first proposes an improved continuous MOPSO to address the rapid clustering problem that exists in the basic PSO algorithm using three improvement strategies: re-initialization of particles, systematic switch of best solutions and mutation on global best selection. …”
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9
Fingerprint Image Compression Using Wavelet Transform
Published 2003“…In fact, wavelet refers to a set of basic function, which is recursively defined form, a set of scaling coefficients and scaling function. …”
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10
Efficient beamforming and spectral efficiency maximization in a joint transmission LTE-A system
Published 2016“…Moreover, addressing the lack-of-diversity issue in Basic Particle Swarm Optimization Algorithm (BPSOA) is a primary concern of this work. …”
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11
Design and development of single-axis solar tracking system and water level control for application of line focus concentrator for solar desalination process
Published 2017“…The tracking algorithm determines the angles which are used to determine the position of solar tracker. …”
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Undergraduates Project Papers -
12
Optimization of Upstream Offshore Oilfield Production Planning under Uncertainty and Downstream Crude Oil Scheduling at Refinery Front-End
Published 2012“…A continuous time model based on transfer events is used to represent the scheduling problem and this model is a nonconvex MINLP model which presents multiple local optima. …”
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Final Year Project -
13
Solving power system state estimation using orthogonal decomposition algorithm / Tey Siew Kian
Published 2009“…This optimal state estimate and corrected data base are then used by the security monitoring and operation and control functions of the center.Most state estimation programs in practical use are formulated as overdetermined systems (Pozrikidis, 2008) of nonlinear equations and solved as weighted least square problems (refer to section 2.1.1).This research involves finding the least squares solution of the power system state estimation problem, HTR-1HDx = HTR-1 [z - f (x)] (refer to section 2.3.1) and to develop a program to implement the said algorithm. …”
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14
Application Of Multi-Layer Perceptron Technique To Detect And Locate The Base Of A Young Corn Plant
Published 2007“…Morphological operation is applied to remove the small blobs. Prior to localization of the base of young corn tree, skeletonizing operation is performed to get the basic shape of the object. …”
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15
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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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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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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19
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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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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