Search Results - (( based optimization based algorithm ) OR ( data virtualization based algorithm ))
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Feature selection based on particle swarm optimization algorithm for sentiment analysis classification
Published 2021“…An improved approach was proposed to increase the sentiment analysis accuracy based on text pre-processing and Naïve Bayes Classifier algorithm hybrid with Particle Swarm Optimization (NBC-PSO). …”
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Development of an augmented reality based facility layout planning and optimization / Tan Chee Hau
Published 2020“…FLP’s research can be divided into the procedural approach, algorithmic approach, Virtual Reality (VR) and AR-based approaches. …”
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Optimized Load Balancing based Task Scheduling in Cloud Environment
Published 2014“…In this paper, task scheduling strategy based on load balancing Quantum Particles Swarm algorithm (BLQPSO) was proposed. …”
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Optimisation model for scheduling MapReduce jobs in big data processing / Ibrahim Abaker Targio Hashem
Published 2017“…In this study, we aim to optimize task scheduling and resource utilization using an evolutionary algorithm based on the proposed completion time and monetary cost of cloud service models. …”
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Energy-efficient algorithms for dynamic virtual machine consolidation in cloud data centers
Published 2017“…Based on the proposed algorithms, energy consumption can be reduced…”
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Enhancing hyperparameters of LSTM network models through genetic algorithm for virtual learning environment prediction
Published 2025“…Adaptive gradient-based algorithms, including ADAM, NADAM, ADADELTA, ADAGRAD, and ADAMAX, exhibited superior performance. …”
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A new routing mechanism for energy-efficient in bluetooth mesh-low power nodes based on wireless sensor network
Published 2023“…The multi-criterion energyefficient routing mechanism uses the ACO algorithm, inspired by ants' foraging behaviour. In Bluetooth M-LPNWSN systems, virtual ants explore paths based on signal robustness, distances, and energy consumption. …”
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Using the bees algorithm to optimise a support vector machine for wood defect classification
Published 2007“…The paper presents the results obtained to demonstrate the strengths of the Bees Algorithm as an optimization tool.…”
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Resource scheduling algorithm with load balancing for cloud service provisioning
Published 2019“…Increasing utilization of Virtual Machines through effective and fair load balancing is then achieved by dynamically selecting a request from a class using Multidimensional Queuing Load Optimization algorithm. …”
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Controller placement problem in the optimization of 5G based SDN and NFV architecture
Published 2021“…In addition, energy savings of up to 70% are achieved compared to the proposed Dijkstra-based energy-aware algorithms.…”
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Modeling And Control Of V-Groove Rotary Impact Driver
Published 2020“…The speed is optimized by using state-flow algorithm with fixed-point data types, thus reduced hardware computational requirement with acceptable accuracy. …”
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Parameter Estimation of Lorenz Attractor: A Combined Deep Neural Network and K-Means Clustering Approach
Published 2022“…After that, it has been suggested to improve the efficiencies in the Deep Neural Network (DNN) model by combining the DNN with an unsupervised machine learning algorithm, the K-Means clustering algorithm. This study constructs the flow of DNN based method with the K-Means algorithm. …”
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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 motion planning method for industrial robots based on the digital twin concept
Published 2025“…This study proposes a novel motion planning method for six-degree-of-freedom industrial robots based on DT technology. By integrating an improved Artificial potential field method, A* algorithm, and a synergistic approach combining 3-5-3 polynomial interpolation with particle swarm optimization, we effectively address the challenges of dynamic obstacle avoidance and trajectory optimization. …”
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