Online dynamic ensemble deep random vector functional link neural network for forecasting حسب Ruobin Gao (16003195)

"…<p>This paper proposes a three-stage online deep learning model for time series based on the ensemble deep random vector functional link (edRVFL). …"

Development of an Optimization Scheme for A Fixed-Wing UAV Long Endurance with PEMFC and Battery حسب Al Rayes, Zaid

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Wide area monitoring system operations in modern power grids: A median regression function-based state estimation approach towards cyber attacks حسب Haris M. Khalid (17017743)

"…To address this issue, a median regression function (MRF)-based state estimation is presented in this paper. …"

Metaheuristic algorithm for testing web 2.0 applications. (c2012) حسب Zeitunlian, Hratch Michel

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

"…The results show that, unlike in the stationary case, the steady-state excess MSE is not a monotonically increasing function of the step size. …"
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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. …"
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Efficient heuristic algorithms for influence propagation in social networks. (c2018) حسب Lamaa, Karine H.

"…Then we introduce the notion of an influence propagation function and use it to design an efficient algorithm across all types of networks. …"
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Wild Blueberry Harvesting Losses Predicted with Selective Machine Learning Algorithms حسب Humna Khan (17541972)

"…For the purpose of predicting ground loss as a function of fruit zone, plant height, fruit production, slope, leaf loss, and blower damage, three ML models i.e., support vector regression (SVR), linear regression (LR), and random forest (RF)—were used. …"

Improved Transportation Model with Internet of Things Using Artificial Intelligence Algorithm حسب Ayman Khallel Al-Ani (17541447)

"…The proposed method is designed in such a way as to detect the number of loads that are present in a vehicle where functionality tasks are computed in the system. …"

Performance assessment and exhaustive listing of 500+ nature-inspired metaheuristic algorithms حسب Zhongqiang Ma (13765801)

"…In addition, whether these algorithms have a search bias to the origin (i.e., the center of the search space) is investigated. …"

An enhanced binary Rat Swarm Optimizer based on local-best concepts of PSO and collaborative crossover operators for feature selection حسب Abu Zitar, Raed

"…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. …"

Development of Lévy flight-based reptile search algorithm with local search ability for power systems engineering design problems حسب Abu Zitar, Raed

"…The need for better-performing algorithms to solve real-world power systems engineering problems has always been a challenging topic. …"
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Optimal multiobjective design of robust power system stabilizers using genetic algorithms حسب Abdel-Magid, Y.L.

"…The problem of robustly selecting the parameters of the power system stabilizers is converted to an optimization problem which is solved by a genetic algorithm with the eigenvalue-based multiobjective function. …"
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Robust Coordinated Design of Excitation and TCSC-Based Stabilizers Using genetic algorithms حسب Abdel-Magid, Y. L.

"…The coordinated design problem of robust excitation and TCSC-based controllers over a wide range of loading conditions and system configurations is formulated as an optimization problem with an eigenvalue-based objective function. …"
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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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New Fast Arctangent Approximation Algorithm for Generic Real-Time Embedded Applications حسب Mohieddine Benammar (18103039)

"…The new algorithm exploits the pseudo-linear region around the tangent function zero point to estimate a reduced input arctangent through a modified rational approximation before referring this estimate to its original value using miniature LUTs. …"

Using machine learning algorithm for detection of cyber-attacks in cyber physical systems حسب Almajed, Rasha

"…They have been exposed to cyberattacks because of their integration with an insecure network. In the event of a violation in internet security, an attacker was able to interfere with the system's functions, which might result in catastrophic consequences. …"
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Orthogonal Learning Rosenbrock’s Direct Rotation with the Gazelle Optimization Algorithm for Global Optimization حسب Abu Zitar, Raed

"…The gazelle optimization algorithm (GOA) is a global stochastic optimizer that is straightforward to comprehend and has powerful search capabilities. …"
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Modified Elite Opposition-Based Artificial Hummingbird Algorithm for Designing FOPID Controlled Cruise Control System حسب Abualigah, Laith

"…Efficient speed controllers for dynamic driving tasks in autonomous vehicles are crucial for ensuring safety and reliability. This study proposes a novel approach for designing a fractional order proportional-integral-derivative (FOPID) controller that utilizes a modified elite opposition-based artificial hummingbird algorithm (m-AHA) for optimal parameter tuning. …"
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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)

"…This research proposed a hybrid model for energy-efficient cluster formation and a head selection (E-CFSA) algorithm based on convolutional neural networks (CNNs) and a modified k-mean clustering (MKM) method for MEC. …"