بدائل البحث:
algorithm cost » algorithm goa (توسيع البحث), algorithm its (توسيع البحث)
algorithm aoa » algorithm goa (توسيع البحث), algorithm fa (توسيع البحث), algorithm a (توسيع البحث)
algorithm cost » algorithm goa (توسيع البحث), algorithm its (توسيع البحث)
algorithm aoa » algorithm goa (توسيع البحث), algorithm fa (توسيع البحث), algorithm a (توسيع البحث)
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Evaluation of transfer functions for punctured turbo codes
منشور في 2000"…A modified algorithm for evaluating transfer functions of turbo codes with punctured systematic bits is presented. …"
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Augmented arithmetic optimization algorithm using opposite-based learning and lévy flight distribution for global optimization and data clustering
منشور في 2022"…This paper proposes a new data clustering method using the advantages of metaheuristic (MH) optimization algorithms. A novel MH optimization algorithm, called arithmetic optimization algorithm (AOA), was proposed to address complex optimization tasks. …"
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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
منشور في 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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Adapted arithmetic optimization algorithm for multi-level thresholding image segmentation: a case study of chest x-ray images
منشور في 2023"…The solutions are evaluated using Otsu's fitness function throughout the optimization process. The picture histogram is used to display the algorithm's potential solutions. …"
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Modified arithmetic optimization algorithm for drones measurements and tracks assignment problem
منشور في 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
منشور في 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
منشور في 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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Logarithmic spiral search based arithmetic optimization algorithm with selective mechanism and its application to functional electrical stimulation system control
منشور في 2022"…The proposed algorithm (Ls-AOA) was tested against unimodal and multimodal benchmark functions and demonstrated better capability comparatively using other efficient metaheuristic algorithms reported in the literature. …"
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ANT-colony optimization-direct torque control for a doubly fed induction motor : An experimental validation
منشور في 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
منشور في 2017احصل على النص الكامل
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Distributed optimal coverage control in multi-agent systems: Known and unknown environments
منشور في 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
منشور في 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. …"