Genetic and heuristic algorithms for regrouping service sites. (c2000) حسب Tabbara, Hiba

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Efficient Algorithms for Constructing Preset Distinguishing Sequences for Nondeterministic Finite State Machines حسب Haddad, Abdul Rahim

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Distributed optimal coverage control in multi-agent systems: Known and unknown environments حسب Mohammadhasan Faghihi (22303057)

"…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. …"

Tracking analysis of the NLMS algorithm in the presence of both random and cyclic nonstationarities حسب Moinuddin, M.

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A utility-based algorithm for joint uplink/downlink scheduling in wireless cellular networks حسب Saad, Walid

"…While most existing literature focuses on downlink-only or uplink-only scheduling algorithms, the proposed algorithm aims at ensuring a utility function that jointly captures the quality of service in terms of delay and channel quality on both links. …"
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Multi-Target Tracking Resources Allocation Using Multi-Agent Modeling and Auction Algorithm حسب De Rochechouart, Maxence

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Process Targeting Of Multi-Characteristic Product Using Fuzzy Logic And Genetic Algorithm With An Interval Based Taguchi Cost Function حسب Mujahid, S.N.

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Process Targeting Of Multi-Characteristic Product Using Fuzzy Logic And Genetic Algorithm With An Interval Based Taguchi Cost Function حسب Duffuaa, S. O.

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Optimum sensors allocation for drones multi-target tracking under complex environment using improved prairie dog optimization حسب Abu Zitar, Raed

"…This hybrid approach, the Improved Prairie Dog Optimization Algorithm (IPDOA) with the Genetic Algorithm (GA), utilizes the strengths of both algorithms to improve the overall optimization performance. …"
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ANT-colony optimization-direct torque control for a doubly fed induction motor : An experimental validation حسب Said Mahfoud (17150968)

"…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). …"

New enumeration algorithm for regular boolean functions حسب Nasrallah, Walid F.

"…After proving this equivalence, this paper introduces a novel data structure that may, with further tweaking, enable faster enumeration algorithms for both regular Boolean functions and all-capacities knapsack problem instances.…"
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Guaranteed Cost Control Of A Markov Jump Linear Uncertain System UsingA Time-Multiplied Cost Function حسب Boukas, EK

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Guaranteed Cost Control Of A Markov Jump Linear Uncertain System Using A Time-Multiplied Cost Function حسب Boukas, EK

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Guaranteed Cost Control Of A Markov Jump Linear Uncertain System Using A Time-Multiplied Cost Function حسب Boukas, EK

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A deterministic heuristic algorithm for optimal multiprocessor scheduling. (c1995) حسب Moujabber, Bassam N.

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Modified arithmetic optimization algorithm for drones measurements and tracks assignment problem حسب Abu Zitar, Raed

"…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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On the Optimization of Band Gaps in Periodic Waveguides حسب Jamil Renno (14070771)

"…<h3 dir="ltr">Purpose</h3><p dir="ltr">This work applies a computational framework for vibration attenuation in periodic structures by combining the established wave and finite element (WFE) method with nature-inspired optimization algorithms. The purpose of this work is to provide a systematic comparison of various nature-inspired algorithms across both low-cost analytical and high-fidelity simulation-driven design problems.…"

Incremental and Heuristic Algorithms for Deriving Adaptive Distinguishing Test Cases for Nondeterministic Finite State Machines حسب Saleh, Ayat

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Optimum Track to Track Fusion Using CMA-ES and LSTM Techniques حسب Fares, Samar

"…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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Adaptive Time-Varying Brain Source Localization حسب Al-Momani, Sajedah A.

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