Supervised term-category feature weighting for improved text classification حسب Attieh, Joseph

"…GradientDescentANN replaces the iterative additive process mentioned previously by computing the term-category matrix using a gradient descent ANN model. Training the ANN using the gradient descent algorithm allows updating the term-category matrix until reaching convergence. …"
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Impacts of On-Grid Solar PV on Distribution Networks and Potential Solutions: A Case Study in the Region of Zahle حسب Korkmaz, Jessica

"…The siting and sizing methodology is conducted by considering five different optimization algorithms, namely the single-objective genetic algorithm (SOGA), the combined SOGA and loss sensitivity factor algorithm (SOGA-LSF), the multi-objective genetic algorithm (MOGA), the combined MOGA-LSF and the CAPADD algorithm of OpenDSS. …"
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A Fully Optical Laser Based System for Damage Detection and Localization in Rail Tracks Using Ultrasonic Rayleigh Waves: A Numerical and Experimental Study حسب Masurkar, Faeez

"…Further, As the quality of received signals differs at different sensing points as a result of the surface conditions of the specimen, the Self Adaptive Smart Algorithm (SASA) method was adopted to filter out the noise and accurately pinpoint the defect reflected wave packet which ultimately aids in better detection and localization. …"
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The Frontiers of Deep Reinforcement Learning for Resource Management in Future Wireless HetNets: Techniques, Challenges, and Research Directions حسب Abdulmalik Alwarafy (17984104)

"…To this end, we carefully identify the types of DRL algorithms utilized in each related work, the elements of these algorithms, and the main findings of each related work. …"

Computation of conformal invariants حسب Mohamed M.S. Nasser (16931772)

"…In particular, we provide an algorithm for computing the conformal capacity of a condenser. …"

A fuzzy basis function network for generator excitation control حسب Abido, M.A.

"…The proposed FBFN is trained over a wide range of operating conditions in order to re-tune the PSS parameters in real-time based on generator loading conditions. The orthogonal least squares learning algorithm is developed for designing an adequate and parsimonious FBFN model. …"
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A fine-grained XML structural comparison approach حسب Tekli, Joe

"…Our approach consists of two main algorithms for discovering the structural commonality between sub-trees and computing tree-based edit operations costs. …"
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A novel hybrid methodology for fault diagnosis of wind energy conversion systems حسب Khaled Dhibi (16891524)

"…Therefore, a hybrid feature selection based diagnosis technique, that can preserve the advantages of wrapper and filter algorithms as well as RF model, is proposed. …"

Meta Reinforcement Learning for UAV-Assisted Energy Harvesting IoT Devices in Disaster-Affected Areas حسب Marwan Dhuheir (19170898)

"…We conducted extensive simulations and compared our approach with two state-of-the-art models using traditional RL algorithms represented by a deep Q-network algorithm, a Particle Swarm Optimization (PSO) algorithm, and one greedy solution. …"

Simulations of the penetration of 6061-T6511 aluminum targets by spherical-nosed VAR 4340 steel projectiles حسب Warren, Thomas

"…In the context of an analysis code, this approximation eliminates the need for discretizing the target as well as the need for a contact algorithm. Thus, this method substantially reduces the computer time and memory requirements. …"
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Toward automatic motivator selection for autism behavior intervention therapy حسب Siyam, Nur

"…We use a Q-learning algorithm to solve the modeled problem. Our proposed solution is then implemented as a mobile application developed for special education plans coordination. …"
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Enhancement of blocking performance in all-optical WDM networks. (c2012) حسب Joun, Carla J.

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Phased Array Technique for Brain Source Localization حسب Zarghami, Tahereh

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Fast Transient Stability Assessment of Power Systems Using Optimized Temporal Convolutional Networks حسب Mohamed Massaoudi (16888710)

"…In a postfault scenario, a copula of processing blocks is implemented to ensure the reliability of the proposed method where high-importance features are incorporated into the TCN-GWO model. The proposed algorithm unlocks scalability and system adaptability to operational variability by adopting numeric imputation and missing-data-tolerant techniques. …"

A hybrid neuro-fuzzy power system stabilizer for multimachine powersystems حسب Abido, M.A.

"…The proposed FBFN is trained over a wide range of operating conditions in order to re-tune the PSS parameters in real-time based on machine loading conditions. The orthogonal least squares (OLS) learning algorithm is developed for designing an adequate and parsimonious FBFN model. …"
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Recursive Parameter Identification Of A Class Of Nonlinear Systems From Noisy Measurements حسب Emara-Shabaik, Husam

"…A model is proposed to identify the parameters of a class of stochastic nonlinearsystems. …"
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Parallel processing حسب Mansour, Nashat

"…The parallel genetic algorithm is based on a model of natural evolution. …"
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A new minimum curvator multi-step method for unconstrained optimization حسب Obeid, Samir

"…In this paper, we carry on with a similar idea and define a rational model with a free parameter. Our derivation of the new algorithm is based on determining some value of the parameter that minimizes the curvature in some chosen metric. …"
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Vibration suppression in a cantilever beam using a string-type vibration absorber حسب Issa, Jimmy S.

"…The string is rigidly connected to the fixed end of the beam and through a spring and damper to a second point on the beam. The finite element method is used to model the system and a reduced order model is obtained through modal reduction performed on both the string and the beam. …"
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STEM: spatial speech separation using twin-delayed DDPG reinforcement learning and expectation maximization حسب Muhammad Salman Khan (7202543)

"…Its perceptual evaluation of speech quality (PESQ) score is 0.55 points better than a self-supervised learning (SSL) model and almost equivalent to the diffusion models at computational cost and training data which is many folds lesser than required by these algorithms. …"