Spherical cavity-expansion forcing function in PRONTO 3D for application to penetration problems by Tabbara, Mazen R.

“…In this spirit, a forcing function which is derived from a spherical-cavity expansion analysis has been implemented in PRONTO 3D. …”
Get full text
Get full text
Get full text

Online dynamic ensemble deep random vector functional link neural network for forecasting by 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). …”

Wide area monitoring system operations in modern power grids: A median regression function-based state estimation approach towards cyber attacks by 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) by Zeitunlian, Hratch Michel

Get full text
Get full text

Tracking analysis of the NLMS algorithm in the presence of both random and cyclic nonstationarities by 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. …”
Get full text
Get full text

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

“…In particular, a new modified method based on the Arithmetic Optimization Algorithm is proposed. …”
Get full text

Efficient heuristic algorithms for influence propagation in social networks. (c2018) by 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. …”
Get full text
Get full text
Get full text

Wild Blueberry Harvesting Losses Predicted with Selective Machine Learning Algorithms by 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 by 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 by 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. …”

Optimal multiobjective design of robust power system stabilizers using genetic algorithms by 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. …”
Get full text
Get full text

Robust Coordinated Design of Excitation and TCSC-Based Stabilizers Using genetic algorithms by 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. …”
Get full text

Using machine learning algorithm for detection of cyber-attacks in cyber physical systems by 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. …”
Get full text
Get full text

Orthogonal Learning Rosenbrock’s Direct Rotation with the Gazelle Optimization Algorithm for Global Optimization by Abu Zitar, Raed

“…The gazelle optimization algorithm (GOA) is a global stochastic optimizer that is straightforward to comprehend and has powerful search capabilities. …”
Get full text

Multi-Cluster Jumping Particle Swarm Optimization for Fast Convergence by Atiq Ur Rehman (8843024)

“…Moreover, majority of improvements made by the researchers in optimization techniques have focused on the accuracy of solution and have overlooked the convergence speed of an algorithm. Keeping in view the need of an optimization algorithm with fast convergence speed, suitable for high dimensional data space, this article proposes a novel concept of Multi-Cluster Jumping PSO. …”

A Hybrid Deep Learning Model Using CNN and K-Mean Clustering for Energy Efficient Modelling in Mobile EdgeIoT by 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. …”

A novel AI approach for optimal deployment of EV fast charging station and reliability analysis with solar based DGs in distribution network by Fareed Ahmad (134672)

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

Get full text

Selection of the learning gain matrix of an iterative learning control algorithm in presence of measurement noise by Saab, Samer S.

“…This work also provides a recursive algorithm that generates the appropriate learning gain functions that meet the arbitrary high precision output tracking objective. …”
Get full text
Get full text
Get full text
Get full text

Power System Transient Stability Assessment Based on Machine Learning Algorithms and Grid Topology by Senyuk, Mihail

“…Transient stability of a power system was analyzed as the base function. …”
Get full text