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algorithm cost » algorithm aoa (Expand Search), algorithm its (Expand Search)
algorithm goa » algorithm fa (Expand Search), algorithm _ (Expand Search), algorithms a (Expand Search)
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Evaluation of transfer functions for punctured turbo codes
Published 2000“…A modified algorithm for evaluating transfer functions of turbo codes with punctured systematic bits is presented. …”
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Multi-Target Tracking Resources Allocation Using Multi-Agent Modeling and Auction Algorithm
Published 2023Subjects: Get full text
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A Quasi-Oppositional Method for Output Tracking Control by Swarm-Based MPID Controller on AC/HVDC Interconnected Systems With Virtual Inertia Emulation
Published 2021“…The role of the proposed quasi oppositional based SMPID controller is to modify the tracking strategy on AC/HVDC interconnected systems while reducing the related cost function. The proposed analysis is established considering the most highly cited, well-known tested and newly expanded swarm-based optimization algorithms (SBOAs), such as Grasshopper Optimization Algorithm (GOA), Grey Wolf Optimization (GWO), Artificial Fish Swarm Algorithm (AFSA), Artificial Bee Colony (ABC) and Particle Swarm Optimization (PSO). …”
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Attacking ElGamal based cryptographic algorithms using Pollard's rho algorithm
Published 2005Get full text
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A hybrid of clustering and meta-heuristic algorithms to solve a p-mobile hub location–allocation problem with the depreciation cost of hub facilities
Published 2021“…Three objective functions are considered to minimize costs, noise pollutions, and the harassment caused by the establishment of a hub for people, a new objective that locates hubs in less populated areas. …”
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Orthogonal Learning Rosenbrock’s Direct Rotation with the Gazelle Optimization Algorithm for Global Optimization
Published 2022“…Nevertheless, the GOA is unsuitable for addressing multimodal, hybrid functions, and data mining problems. …”
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Modified arithmetic optimization algorithm for drones measurements and tracks assignment problem
Published 2023“…In particular, a new modified method based on the Arithmetic Optimization Algorithm is proposed. The optimization is applied to a formulated cost function that considers uncertainty, false alarms, and existing clutters. …”
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An enhanced binary Rat Swarm Optimizer based on local-best concepts of PSO and collaborative crossover operators for feature selection
Published 2022“…The binary enhanced RSO is built based on three successive modifications: i) an S-shape transfer function is used to develop binary RSO algorithms; ii) the local search paradigm of particle swarm optimization is used with the iterative loop of RSO to boost its local exploitation; iii) three crossover mechanisms are used and controlled by a switch probability to improve the diversity. …”
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Optimum Track to Track Fusion Using CMA-ES and LSTM Techniques
Published 2024“…An objective function utilizing the covariance of the fused tracks is used by the first algorithm while a cost function based on the Kullback-Leibler (KL) divergence measure is used in the second case for training the LSTM. …”
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ANT-colony optimization-direct torque control for a doubly fed induction motor : An experimental validation
Published 2022“…The new combined ACO-DTC strategy has been studied for optimizing the gains of the PID controller by using a cost function such as Integral Square Error (ISE). …”
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Accommodating High Penetrations of Renewable Distributed Generation Mix in Smart Grids
Published 2017Get full text
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Distributed optimal coverage control in multi-agent systems: Known and unknown environments
Published 2024“…The proposed approach leverages a novel cost function for optimizing the agents’ coverage and the cost function eventually aligns with the conventional Voronoi-based cost function. …”
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A Hybrid Deep Learning Model Using CNN and K-Mean Clustering for Energy Efficient Modelling in Mobile EdgeIoT
Published 2023“…The proposed model determines a training dataset by covering all the aspects of cost function calculation. This training dataset helps to train the model, which allows for efficient decision-making in optimum energy usage. …”
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