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1
An adaptive block-based matching algorithm for crowd motion sequences
Published 2018“…However, algorithms based on optical flow and background subtraction have numerous limitations such as the complexity of the computation in the presence of high dense crowd and sudden motion changes. …”
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2
An adaptive block-based matching algorithm for crowd motion sequences
Published 2018“…However, algorithms based on optical flow and background subtraction have numerous limitations such as the complexity of the computation in the presence of high dense crowd and sudden motion changes. …”
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3
An optical flow measurement technique based on continuous wavelet transform
Published 2018“…Flow measurement underwater oil leak is a challenging problem, due to the complex nature of flow dynamics. …”
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4
An optical flow measurement technique based on continuous wavelet transform
Published 2018“…Flow measurement underwater oil leak is a challenging problem, due to the complex nature of flow dynamics. …”
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5
Optimal placement and sizing of FACTS devices for optimal power flow using metaheuristic optimizers
Published 2022“…OPF is one of the well-known problems in power system operations and with the inclusion of the FACTS devices allocation problems into OPF will make the solution more complex. Thus, seven metaheuristic algorithms: Barnacles Mating Optimizer (BMO), Marine Predators Algorithm (MPA), Moth–Flame Optimization (MFO), Particle Swarm Optimization (PSO), Gravitational Search Algorithm (GSA), Teaching–Learning-Based Optimization (TLBO) and Heap-Based Optimizer (HBO) are used to solve two objective functions: power loss and cost minimizations. …”
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6
An application of teaching–learning-based optimization for solving the optimal power flow problem with stochastic wind and solar power generators
Published 2023“…This paper proposes the implementation of metaheuristic algorithm namely, teaching–learning-based optimization (TLBO) algorithm to solve optimal power flow (OPF) problem. …”
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7
Optimal operation and control of hybrid power systems with stochastic renewables and FACTS devices: An intelligent multi-objective optimization approach
Published 2025“…The application of the recently developed flow direction algorithm, including its multi-objective variant with an �-based constraint-handling mechanism to OPF problem is the primary contributions of this work. …”
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Optimization of cost-based hybrid flowshop scheduling using teaching-learning-based optimization algorithm
Published 2024“…A cost-based hybrid flowshop scheduling (CHFS) combines flow shop and job shop elements, with cost considerations as a key indicator. …”
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9
Reduced Galloping Column Algorithm For Memory Testing
Published 2015“…However, the existing GalCol algorithm takes huge test time due to its test complexity. …”
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10
A trade-off criterion for bi-objective problem in solving hybrid flow shop scheduling with energy efficient (EE-HFS) using multi-objective dragonfly algorithm (MODA)
Published 2024“…The (EE-HFS) optimization has been carried out using the Multi-Objective Dragonfly Algorithm (MODA). The optimization result was compared with well-established algorithms, the Pareto Envelope-based Selection Algorithm II (PESA2), Multi-Objective Evolutionary Algorithm Based on Decomposition (MOEA/D), and new algorithms, Multi-Objective Grasshopper Optimization Algorithm (MOGOA) and Multi-Objective Ant Lion Optimizer (MOALO). …”
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11
Development of floor mapping mobile robot algorithm using enhanced Artificial Neuro-Based SLAM (ANBS)
Published 2020“…The paper will highlight implementing a Rplidar sensor with a floor mapping mobile robot platform with the enhanced error corrections based on the Artificial Neuro-Based SLAM (ANBS) algorithm. …”
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12
Physics-guided deep neural network to characterize non-Newtonian fluid flow for optimal use of energy resources
Published 2021“…The simulated results and analysis demonstrate an excellent agreement between the proposed algorithm and non-Newtonian fluids flow attributes. …”
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13
Optimal power flow using hybrid firefly and particle swarm optimization algorithm
Published 2020“…In this paper, a novel, effective meta-heuristic, population-based Hybrid Firefly Particle Swarm Optimization (HFPSO) algorithm is applied to solve different non-linear and convex optimal power flow (OPF) problems. …”
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14
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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15
Hybrid firefly and particle swarm optimization algorithm for multi-objective optimal power flow with distributed generation
Published 2022“…The proposed algorithm is simulated for simultaneous OPF-based conflicting objectives, respectively. …”
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16
Hybrid flow shop scheduling problem with energy utilization using non-dominated sorting genetic algorithm-III (NSGA-III) optimization
Published 2023“…The model was compared with the most sought algorithm and latest multi-objective algorithms, Strength Pareto Evolutionary Algorithm 2 (SPEA -II), Multi-Objective Algorithm Particle Swarm Optimization (MOPSO), Pareto Envelope-based Selection Algorithm II (PESA-II) and Multi-objective Evolutionary Algorithm based on Decomposition (MOEA/D). …”
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A Machine Learning Classification Approach to Detect TLS-based Malware using Entropy-based Flow Set Features
Published 2022“…Due to the complexity of TLS traffic decryption, several anomaly-based detection studies have been conducted to detect TLS-based malware using different features and machine learning (ML) algorithms. …”
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18
A comparative evaluation of heuristic and metaheuristic job scheduling algorithms for optimized resource management in cloud environments
Published 2026“…The CloudSim simulator is applied to evaluate each algorithm using key performance metrics, including makespan, average flow time, and the number of cloudlets that fail to meet deadlines. …”
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19
Dynamic Feedback Flow Control Algorithms for Unicast and Multicast Available Bit Rate Service in Asynchronous Transfer Mode Networks
Published 2000“…Thirdly, the design and implementation issues have been addressed together with the major drawbacks of the previous schemes and hence two algorithms have been proposed. A dynamic rate-based flow control (DRFC) scheme has been developed to support ABR service in unicast environment, while an adaptive feedback consolidation (AFC) algorithm has been designed for ABR multicasting. …”
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20
Implementation Of FPGA Based Encryption Chip Using VHD - Data Encryption Standard (DES) Algorithm
Published 2006“…Traditional Encryption Algorithms are implemented in software base because of the complexities involved in the operations. …”
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