Search Results - (( global optimisation ((sensor algorithm) OR (path algorithm)) ) OR ( _ variation a algorithm ))
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1
Optimised multi-robot path planning via smooth trajectory generation
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Final Year Project / Dissertation / Thesis -
2
Improvement Of Stereo Matching Algorithm Based On Sum Of Gradient Magnitude Differences And Semi-Global Method With Refinement Step
Published 2018“…A new stereo matching algorithm which uses improved matching cost computation and optimisation using the semi-global method (SGM) is proposed.The absolute difference is sensitive to low textured regions and high noise on the stereo images with radiometric distortions. …”
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3
Gait identification and optimisation for amphi-underwater robot by using ant colony algorithm
Published 2019“…For the optimization, the robot will travel from one specific point to another with the predefined position within optimized gait and fastest time by using Ant Colony Optimization (ACO) technique. The algorithm being compared, between Ant Colony Algorithm (ACO) and the Particle Swarm Optimisation (PSO) in terms of time and distance. …”
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4
A Hybrid Metaheuristic Technique Based on Grey Wolf Optimisation, Symbiotic Organism Search, and Ant Colony Optimisation for Solving Multi-Objective Vehicle Routing Problems
Published 2025“…The hybridisation mechanism combines the global exploration strength of GWO, the solution refinement capability of SOS, and the effective path construction of ACO into an integrated search strategy. …”
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Thesis -
5
Energy efficient cluster head distribution in wireless sensor networks
Published 2013“…Thus, the best selected CHs location with network global information using FLCH and PSO will be announced by the base station (BS) to the sensor nodes. …”
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Thesis -
6
Development of bacteria foraging optimization algorithm for cell formation in cellular manufacturing system considering cell load variations
Published 2013“…The performance of the proposed algorithm is compared with a number of algorithms that are most commonly used and reported in the corresponding scientific literature such as K-means clustering, the C-link clustering and genetic algorithm using a well-known performance measure that combined cell load variations and a number of exceptional elements. …”
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7
Variation over time of the Perez calibration algorithm for ground-based spectrometer
Published 2016“…This paper aims to study the variation of the Perez calibration algorithm over time for a spectrometer. …”
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Improved Differential Evolution-Based MPPT Algorithm Using SEPIC for PV Systems Under Partial Shading Conditions and Load Variation
Published 2018“…The main contribution of the proposed algorithm are the following: capability in tracking GMPP and faster respond against load variation; optimization algorithm can search for the GMPP within a larger operating region as it is implemented by using a single-ended primary-inductor converter; and easy tuning as less parameter has to be set in the algorithm. …”
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9
Variation over time of the Du Mortier Calibration algorithm for ground-based spectrometer.
Published 2016“…The purpose of this paper is to study the variation over time of the Du Mortier calibration algorithm used in a spectrometer for atmospheric condition measurement. …”
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10
Forecasting Torque and Drag for Oil Wells Prediction using Variation of Decision Tree Algorithm
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Final Year Project -
11
Designing substitution boxes based on chaotic map and globalized firefly algorithm
Published 2019“…The third variation is called globalized firefly algorithm with chaos (CGFA), which was designed as a combination of CFA initialization and GFA. …”
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Thesis -
12
3D face registration across pose variation and facial expression using cross profile alignment
Published 2011“…In a 3D face recognition system, face registration is usually employed to compensate the pose variation in a 3D face model. …”
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Thesis -
13
A Comparative Study of FP-growth Variations
Published 2009“…This paper presents a summarization and a comparative study of the available FP-growth algorithm variations produced for mining frequent itemsets showing their capabilities and efficiency in terms of time and memory consumption.…”
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Citation Index Journal -
14
Box-counting fractal dimension algorithm variations on retina images
Published 2016“…This research work investigates the influences of FD algorithm variation on the measurement of retinal vasculature complexity. …”
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Proceeding Paper -
15
Design of low order quantitative feedback theory and H-infinity-based controllers using particle swarm optimisation for a pneumatic actuator system
Published 2010“…The pneumatic system parameters uncertainty is the main problem in the design of a desired control algorithm for this plant. Where the variation in thermodynamic conditions causes an uncertainty in a number of the model’s parameters and the large change of pneumatic actuator load leads to variation in the actuator dynamics. …”
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16
A new algorithm to estimate attenuation using frequency shift methods
Published 2012“…The proposed algorithm has been tested to gauge its performance using three different scenarios; Q variation, travel time variation, and signal to noise ratio (SNR) variation. …”
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Article -
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Model-based hybrid variational level set method applied to lung cancer detection
Published 2024“…This algorithm simplifies the (Local Intensity Clustering) LIC model and devises a new energy functional based on the region-based pressure function. …”
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Analysis of algorithms variation in multilayer perceptron neural network for agarwood oil qualities classification
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Conference or Workshop Item -
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Image Reconstruction Based on Combination of Inverse Scattering Technique and Total Variation Regularization Method
Published 2020“…The Forward-Backward Time-Stepping - Total Variation (FBTS-TV) regularization algorithm is in a two-dimensional case and implemented in C++ language executed in single computing. …”
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Thesis -
20
Enhancement of bearing defect diagnosis via genetic algorithm optimized feature selection
Published 2015“…Thus, it can be concluded that the developed algorithm is capable to improve the classification efficiency by improving the generality of the classifier in classifying test data with unpredictable variations under various working conditions.…”
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