Search Results - (( simulation optimization task algorithm ) OR ( data optimization method algorithm ))
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Attribute reduction based scheduling algorithm with enhanced hybrid genetic algorithm and particle swarm optimization for optimal device selection
Published 2022“…Therefore, in this paper, we proposed Dynamic tasks scheduling algorithm based on attribute reduction with an enhanced hybrid Genetic Algorithm and Particle Swarm Optimization for optimal device selection. …”
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Hybrid Henry Gas-Harris Hawks comprehensive-opposition algorithm for task scheduling in cloud computing
Published 2025“…To achieve optimal performance, it requires accurate task allocation to resources. …”
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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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Multi-objective optimization for integrated task scheduling and load balancing in fog computing for IoT applications
Published 2025“…By using a task scheduling and offloading method, the FOCS algorithm arranges data according to size and sends it to the appropriate fog nodes. …”
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Optimising cloud computing performance with an enhanced dynamic load balancing algorithm for superior task allocation
Published 2024“…Additionally, if a VM cannot meet a cloudlet's deadline, the algorithm redirects the cloudlet to a secondary data centre and reconfigures CPU resources among VMs to ensure optimal allocation. …”
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An enhanced segment particle swarm optimization algorithm for kinetic parameters estimation of the main metabolic model of Escherichia coli
Published 2020“…Hence, based on the aforementioned problems, the optimization algorithm methods played an important role in addressing these problems. …”
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Space allocation for examination scheduling using Genetic Algorithm / Alya Kauthar Azman
Published 2025“…This study applies Genetic Algorithms (GA) to optimize space distribution for test scheduling, addressing the challenge of managing multiple test sessions across distinct locations. …”
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Cluster optimization in VANET using MFO algorithm and K-Means clustering
Published 2023“…Proven to be an effective and efficient method for solving optimization problem. To design K-Means algorithm that portion nodes based on their proximities by optimize the distance between nodes within same cluster by assigning them to the closet cluster center. …”
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BAT-BP: A new BAT based back-propagation algorithm for efficient data classification
Published 2016“…Training neural networks particularly back propagation algorithm is a complex task of great importance in the field of supervised learning. …”
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Simulated kalman filter (SKF) based image template matching for distance measurement by using stereo vision system
Published 2018“…In addition, it is expected that it can be applied in real-time application. In this study, Simulated Kalman Filter (SKF) is applied to image template matching application as the optimization algorithm. …”
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Task scheduling in cloud computing using hybrid genetic algorithm and bald eagle search (GA-BES)
Published 2022“…The natural evolution optimization algorithm which is genetic algorithm can be improve by combining the nature meta-heuristic algorithms which is bald eagle search to improve the makespan of genetic algorithm using cloudsim that need to be implement on the eclipse platform. …”
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Academic Exercise -
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Road damage detection for autonomous driving vehicles using YOLOv8 and salp swarm algorithm
Published 2025“…Consequently, this paper proposes a method to improve the detection accuracy of You Only Look Once version 8 (YOLOv8) using Salp Swarm Algorithm (SSA) for hyperparameter optimization, focusing on eight key parameters. …”
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Scheduling scientific workflow using multiobjective algorithm with fuzzy resource utilization in multi-cloud environment
Published 2020“…In this respect, this paper proposes a new multi-objective scheduling algorithm with Fuzzy resource utilization (FR-MOS) for scheduling scientific workflow based on particle swarm optimization (PSO) method. …”
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Deep reinforcement learning online offloading for SWIPT multiple access edge computing network
Published 2021“…Simulation results are presented to demonstrate that the proposed algorithm is able to approach near-optimal performance and superior in decreasing tasks computation time compared with existing optimization methods, enabling real time optimal resource allocation and offloading achievable in a fast-fading wireless environment.…”
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Proceedings -
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Even-odd scheduling based energy efficient routing for wireless sensor network (WSN) / Muhammad Zafar Iqbal Khan
Published 2022“…Using the simulation software, it was observed that the alive nodes are higher in numbers i.e. 189 nodes after 500 rounds for the proposed routing algorithm compared to the previous methods which had only 150 alive nodes. …”
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Development of optimized maintenance scheduling model for coal-fired power plant boiler
Published 2023“…Literature revealed that mathematical methods and metaheuristic algorithms are common approaches in solving combinatorial optimization problems with a large search space in a reasonable computational run time. …”
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Dynamic partitioning and data allocation method on heterogeneous architecture / Muhammad Helmi Rosli
Published 2015“…These network form cluster of computing resources that simulates supercomputer. Processing images are computationally complex due to its data and task intensive nature. …”
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Reproducing kernel Hilbert space method for cox proportional hazard model
Published 2016“…Then, we apply the kernel method to the survival data. Finally, we propose an algorithm of minimization of the loss function in the general Cox model. …”
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Removal of BCG artefact from concurrent fMRI-EEG recordings based on EMD and PCA
Published 2017“…Results The method was tested with both simulated and real EEG data of 11 participants. …”
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LSSVM parameters tuning with enhanced artificial bee colony
Published 2014“…To date, exploring an efficient method for optimizing Least Squares Support Vector Machines (LSSVM) hyperparameters has been an enthusiastic research area among academic researchers.LSSVM is a practical machine learning approach that has been broadly utilized in numerous fields. …”
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