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1
Topology-aware hypergraph based approach to optimize scheduling of parallel applications onto distributed parallel architectures
Published 2020“…Any optimization algorithm is suitable for only a specific domain of optimization problems. …”
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2
OPTIMIZATION OF HYBRID-FUZZY CONTROLLER FOR SERVOMOTOR CONTROL USING A MODIFIED GENETIC ALGORITHM
Published 2011“…In this thesis, a new optimization GA-based algorithm that emanates from modification of conventional GA to reduce the iterations number and the duration time, namely, semi-parallel operation genetic algorithm (SPOGA) is proposed. …”
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3
Analysis of evolutionary computing performance via mapreduce parallel processing architecture / Ahmad Firdaus Ahmad Fadzil
Published 2014“…MR is an emerging parallel processing framework that hides the complex parallelization processes by employing the functional abstraction of "map and reduce" The Performance of the parallelized GA via MR and PSO via MR are evaluated using an analogous case study to find out the speedup and efficiency in order to measure the scalability of both proposed algorithms. …”
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4
WCDMA teletraffic performance improvement via power resource optimization using distributed parallel genetic algorithm
Published 2023“…The algorithm works by finding the minimum transmitter power with the help of Distributed Parallel Genetic Algorithm (DPGA) employed on an offload microcontroller system to form optimal beam coverage to reduce power usage of adaptive antenna at WCDMA base station. …”
Conference paper -
5
The Parallel Fuzzy C-Median Clustering Algorithm Using Spark for the Big Data
Published 2024“…Therefore, we develop a Parallel Fuzzy C-Median Clustering Algorithm Using Spark for Big Data that can handle large datasets while maintaining high accuracy and scalability. …”
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6
Single-objective and multi-objective optimization algorithms based on sperm fertilization procedure / Hisham Ahmad Theeb Shehadeh
Published 2018“…These algorithms are Genetic Algorithms (GA), Parallel Genetic Algorithm (PGA), Particle Swarm Optimization (PSO) and Accelerated Particle Swarm Optimization (APSO). …”
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7
Customised fitness function of evolutionary algorithm for optimization of car park space / Ahmad Syahir Ab. Aziz
Published 2017“…Therefore, framework development methodology is used to make sure the system successful and can be developed according to the schedule. Genetic algorithm is chosen for the development of the prototype to prove that genetic algorithm is the best technique to implement for optimization. …”
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8
Design and implementation of a real-time adaptive learning algorithm controller for a 3-DOF parallel manipulator / Mustafa Jabbar Hayawi
Published 2015“…A parallel manipulator is a closed loop mechanism which consists of a moving platform that is connected to a fixed base by at least two kinematic chains in parallel. …”
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9
Design of low order quantitative feedback theory and H-infinity-based controllers using particle swarm optimisation for a pneumatic actuator system
Published 2010“…The method uses particle swarm optimization (PSO) to tune the controller and performance weighting function parameters by minimizing a cost function subject to -norm specifications. …”
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10
OPTIMIZATION OF TWO FISH ENCRYPTION ALGORITHM ON FPGA
Published 2004“…Besides that, Twofish also uses a 32 bit Pseudo Hadamard Transform to mix the outputs from its 2 parallel 32-bit g functions. …”
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Final Year Project -
11
Genetic algorithm optimization of I/O scales for FLIC in servomotor control
Published 2009“…This paper discusses the modeling and simulation of DC servomotor control built using MATLAB/Simulink, and the analysis of controller performance, namely a Fuzzy Logic parallel I Controller (FLIC) in which the I/O scale factors of Fuzzy Logic Controller (FLC) and integrator constant are optimized using Genetic Algorithm (GA). …”
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12
Optimal finite- time prescribed performance of servo pneumatic positioning with PID control tuning using an evolutionary mating algorithm
Published 2023“…This paper presents an optimum tuning on finite-time prescribed performance with PID (FT-PPC-PID) controller using the Evolutionary Mating Algorithm (EMA) approach for a pneumatic servo system’s (PSS) rod-piston positioning. …”
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13
Distributed parallel deep learning with a hybrid backpropagation-particle swarm optimization for community detection in large complex networks
Published 2022“…Next, the method is integrated with two optimization algorithms: (1) backpropagation (BP), which optimizes deep learning locally within each local chunk of the CN; (2) particle swarm optimization (PSO), which is used to improve the BP optimization involving all CN chunks. …”
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14
Optimization Of Twofish Encryption Algorithm On FPGA
Published 2005“…Besides that, Twofish also uses a 32 bit Pseudo Hadamard Transform to mix the outputs from its 2 parallel 32-bit g functions. …”
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15
Automatic generic process migration system in linux
Published 2012“…A migration algorithm is designed which attempts to exploit the unique features of the basic migration algorithms to form a generic algorithm. …”
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16
Estimation of core size distribution of magnetic nanoparticles using high-Tc SQUID magnetometer and particle swarm optimizer-based inversion technique
Published 2023“…In this work, the core size estimation technique of magnetic nanoparticles (MNPs) using the static magnetization curve obtained from a high-Tc SQUID magnetometer and a metaheuristic inversion technique based on the Particle Swarm Optimizer (PSO) algorithm is presented. …”
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Deep Learning-Driven Mobility And Utility-Based Resource Management In Mm-Wave Enable Ultradense Heterogeneous Networks
Published 2025thesis::doctoral thesis -
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Development of a multi-objective optimization model for transport and environment in a closed-loop automotive supply chain
Published 2014“…After that a Meta-heuristic method is used for finding the global optimum solution. …”
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19
Adaptive genetic algorithm to improve negotiation process by agents e-commerce
Published 2011“…The proposed negotiation algorithm employs Bayesian learning and similarity functions in order to predict opponent agent’s type and preferences. …”
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20
EMG motion pattern classification through design and optimization of neural network
Published 2012“…Extracted time and time-frequency based feature sets are used to train the neural network. A back-propagation neural network with Levenberg-Marquardt training algorithm has been utilized for the classification of EMG signals. …”
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