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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Accommodating High Penetrations of Renewable Distributed Generation Mix in Smart Grids حسب Khayata, Mohammad Tarek

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A genetic-based algorithm for fuzzy unit commitment model حسب Mantawy, A.H.

"…The genetic algorithm (GA) approach is then used to solve the proposed fuzzy UCP model. …"
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Stochastic evolution algorithm for technology mapping حسب Al-Mulhem, A.S.

"…SELF-Map is based on the Stochastic Evolution (SE) algorithm. The state space model of the problem is defined and suitable cost function which allows optimization for area, delay, or area-delay combinations is proposed. …"
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Improved scatter search algorithm for predicting all-atoms protein structures using charmm22 energy model. (c2010) حسب Ghalayini, Iman Adnan

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

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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 حسب Mahdi Mokhtarzadeh (11593310)

"…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. …"

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 Hybrid Deep Learning Model Using CNN and K-Mean Clustering for Energy Efficient Modelling in Mobile EdgeIoT حسب Dhananjay Bisen (19482454)

"…It also reduces the number of reclustering cycles, which helps to overcome the energy consumption and delay during the reclustering process. The proposed model determines a training dataset by covering all the aspects of cost function calculation. …"

Optimized Load-Scheduling Algorithm for CubeSat's Electric Power System Management Considering Communication Link حسب Bayan Hussein (16904856)

"…An optimization problem is formulated with data rate and BER in the cost function while maintaining energy and power constraints. …"

Cortical EEG Source Localization of Focal Epilepsy حسب Siyam, Wisal Elfatih Mohamed

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Economic load dispatch using memetic sine cosine algorithm حسب Abu Zitar, Raed

"…SCA is a recent population based optimizer turned towards the optimal solution using a mathematical-based model based on sine and cosine trigonometric functions. …"
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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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New fault models and efficient BIST algorithms for dual-portmemories حسب Amin, A.A.

"…The testability problem of dual-port memories is investigated. A functional model is defined, and architectural modifications to enhance the testability of such chips are described. …"
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Design and Implementation of an Advanced Control and Guidance Algorithm of a Single Rotor Helicopter حسب Al-Omari, Muhannad A. R. I.

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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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