Search Results - (( pattern machine algorithm ) OR ( between ((work algorithm) OR (swarm algorithm)) ))
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Multi-State Particle Swarm Optimization for Discrete Combinatorial Optimization Problem
Published 2014“…The proposed algorithm works based on a simplified mechanism of transition between two states. …”
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Verification of correctness properties for aggregation behavior of swarm robotics system using spin model checker / Siti Shafinaz Ali
Published 2015“…This research work focused on a developed swarm algorithm aimed at swarm aggregation. …”
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Verification correctness properties for aggregation behavior of swarm robotics system using SPIN model checker / Siti Shafinaz Ali
Published 2015“…This research work focused on a developed swarm algorithm aimed at swarm aggregation. …”
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Normative Fish Swarm Algorithm For Global Optimization With Applications
Published 2019“…Artificial Fish Swarm Algorithm (AFSA) have become popular optimization technique used to solve various problems, Nevertheless, according to surveys, the existing fish swarm algorithms still have some deficiencies to strike the exact optimum within appropriate convergence rate. …”
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A Navigation Strategy for Swarm Robotics Based on Bat Algorithm Optimization Technique
Published 2018“…This paper aims to adapt Bat Algorithm (BA) optimization techniques to the swarm robotics system. …”
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On spectral efficiency maximization in a partial joint processing system using a multi-start particle swarm optimization algorithm
Published 2015“…However, achieving equivalent backhaul reduction based on limited feedback channel state information is challenging when linear techniques, such as zero-forcing beamforming (BF) are used, which led to the use of stochastic algorithms instead. Therefore stochastic multi-start particle swarm optimization algorithm (MSPSOA) is proposed in this paper to achieve backhaul reduction and address the issue of lack of diversity, which is related to the basic particle swarm optimization algorithm (BPSOA). …”
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Hybrid firely and particle swarm optimisation algorithm for optimal dimming level and energy saving in lecturer’s room
Published 2022“…In order to identify the optimal dimming level, energy consumption, simulation time and luminaire performance, this research work presents the comparison between light-emitting diode (LED) and fluorescent luminaires using the HFPSO algorithm and using the particle swarm optimisation (PSO) algorithm and the firefly algorithm (FA). …”
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Hybrid firefly and particle swarm optimization algorithm for multi-objective optimal power flow with distributed generation
Published 2022“…Finally, a crowding distance and non-dominated-sorting-based multi-objective hybrid firefly & particle swarm optimization (MOHFPSO) algorithm is designed for MOOPF problems. …”
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Modified particle swarm optimization for optimum design of retaining wall
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Working Paper -
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Design of low order quantitative feedback theory and H-infinity-based controllers using particle swarm optimisation for a pneumatic actuator system
Published 2010“…PSO based QFT control algorithm is proposed for pneumatic servo actuator system. …”
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Single-objective and multi-objective optimization algorithms based on sperm fertilization procedure / Hisham Ahmad Theeb Shehadeh
Published 2018“…In this work, Single Objective Optimization Algorithm (SOOA) is proposed. …”
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Machining surface roughness monitoring using acoustic emission method
Published 2010“…The objective of this project is to collect the data acquisition of the experiment by operating milling process, to study the correlation of AE parameter with work piece surface quality by comparing the AE signals with average roughness, Ra of the work piece’s surface measured by using Perthometer, and to develop algorithm for online machining condition monitoring. …”
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Undergraduates Project Papers -
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A New Swarm-Based Framework for Handwritten Authorship Identification in Forensic Document Analysis
Published 2014“…Many researches have been done to develop algorithms for extracting good features that can reflect the authorship with good performance. …”
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Book Chapter -
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A new swarm-based framework for handwritten authorship identification in forensic document analysis
Published 2014“…Many researches have been done to develop algorithms for extracting good features that can reflect the authorship with good performance. …”
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Book Chapter -
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An efficient IDS using hybrid Magnetic swarm optimization in WANETs
Published 2018“…Our developed algorithm works in extracting the most relevant features that can assist in accurately detecting the network attacks. …”
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Hybrid optimal control-swarm intelligence for optimization of selected cancer chemotherapy model / Omar Ali Mohammad Shindi
Published 2018“…This research project proposes two hybrid techniques that’s combined between the optimal control theory (OCT) with the swarm intelligence (SI) and evolutionary algorithms (EA), and check the performance of this techniques, with the popular method that used purely SI and EA algorithms, such M-MOPSO, MOPOS, MOEAD, MODE. …”
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Particle swarm optimization technique of current tracking controller for electric power-assisted steering system
Published 2015“…In this case, three test procedure are done to show the performance of current tracking controller in different situations, also the current tracking performance with Particle Swarm Optimization (PSO)-PID controller compared to previous research that used Ant Colony Optimization (ACO)-PID controller [1] to show the percentage of error between reference motor current and actual motor current of proposed PSO optimization algorithm with 0.023% is much less than previous worked (ACO optimization algorithm) with 4.76%.So the proposed control strategy can improve otor current tracking performance in electric powers assisted steering (EPAS) systems.…”
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Predicting the success of suicide terrorist attacks using different machine learning algorithms
Published 2022“…With an accuracy rate of 98.4% and an AUC-ROC score of 99.9%, the Random Forest classifier was the most accurate among all other algorithms. This model is more trustworthy than previous work and provides a useful comparison between machine learning methods and an artificial neural network because it is less dependent and has a multiclass target feature.…”
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Conference or Workshop Item
