A Survey of cuckoo search algorithm: optimizer and new applications by Abualigah, Laith

“…Cuckoo search (CS) is an efficient swarm intelligence-based algorithm that has come a long way since its start in 2009. …”
Get full text

A Simulated Annealing Algorithm For Fuzzy Unit Commitment Problem by Mantawy, A. H.

“…This paper presents a new algorithm based on integrating simulated annealing and fuzzy logic methods to solve the unit commitment problem. …”
Get full text

A simulated annealing algorithm for fuzzy unit commitment problem by Mantawy, A.H.

“…This paper presents a new algorithm based on integrating simulated annealing and fuzzy logic methods to solve the unit commitment problem. …”
Get full text
Get full text

Economic load dispatch using memetic sine cosine algorithm by 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. …”
Get full text

An efficient method for the open-shop scheduling problem using simulated annealing by Harmanani, Haidar M.

“…The method is based on a simulated annealing algorithm that efficiently explores the solution space. …”
Get full text
Get full text
Get full text
Get full text

Power Control Algorithms for Media Transmission in Remote Healthcare Systems by Ali Hassan Sodhro (18629392)

“…Thus, this paper first proposes a transmission power control (TPC)-based energy-efficient algorithm (EEA) for when a subject is in different postures, i.e., standing, walking, and running, in wireless body sensor networks. …”

Multiclass feature selection with metaheuristic optimization algorithms: a review by Abu Zitar, Raed

“…Datasets can be classified using various methods. Nevertheless, metaheuristic algorithms attract substantial attention to solving different problems in optimization. …”
Get full text

Interval-Valued SVM Based ABO for Fault Detection and Diagnosis of Wind Energy Conversion Systems by Majdi Mansouri (16869885)

“…The proposed improved ABO method consists in reducing the number of samples in the training data set using the Euclidean distance and extracting the most significant features from the reduced data using ABO algorithm. …”

A new minimum curvator multi-step method for unconstrained optimization by Obeid, Samir

“…Our derivation of the new algorithm is based on determining some value of the parameter that minimizes the curvature in some chosen metric. …”
Get full text
Get full text
Get full text

Parameter Estimation Of Wiener-Hammerstein Models Via Genetic Algorithms by Emara-Shabaik, Husam

“…Numerical simulations are presented to illustrate the effectiveness of the proposed algorithm based on different input signals, and different noise-to-signal ratios of the output. …”
Get full text

Methods for system-on-chip test design, scheduling and optimization. (c2006) by Farah, Rana

Get full text
Get full text

Dynamic Layout Planning Using a Hybrid Incremental Solution Method by Zouein, Pierrette

Get full text
Get full text
Get full text

Development of a cerebral aneurysm segmentation method to prevent sentinel hemorrhage by Yousra Regaya (17788964)

“…A robust brain aneurysm segmentation has the potential to prevent the blood leakage, also known as sentinel hemorrhage. Here, we present a method combining a multiresolution and a statistical approach in two dimensional domain to segment cerebral aneurysm in which the Contourlet transform (CT) extracts the image features, while the Hidden Markov Random Field with Expectation Maximization (HMRF-EM) segments the image, based on the spatial contextual constraints. …”

Combinatorial method for bandwidth selection in wind speed kernel density estimation by El Dakkak, Omar

“…In this study, a non-parametric combinatorial method is implemented for obtaining an accurate non-parametric kernel density estimation (KDE)-based statistical model of wind speed, in which the selection of the bandwidth parameter is optimised concerning mean integrated absolute error (L 1 error ) between the true and hypothesised densities. …”
Get full text

Data mining approach to predict student's selection of program majors by SIDDARTHA, SHARMILA

“…At the same time, institutional databases have large volumes of data relating to student demographic profiles, course grades and academic performance. …”
Get full text

Incorporation of Robust Sliding Mode Control and Adaptive Multi-Layer Neural Network-Based Observer for Unmanned Aerial Vehicles by Zainab Akhtar (15192184)

“…<p dir="ltr">The control and state estimation of Unmanned Aerial Vehicles (UAVs) provide significant challenges due to their complex and nonlinear dynamics, as well as uncertainties arising from factors such as sensor noise, wind gusts, and parameter fluctuations. Neural network-based methods tackle these problems by accurately approximating unknown nonlinearities through training on input-output data. …”

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

A method for optimizing test bus assignment and sizing for system-on-a-chip by Harmanani, Haidar M.

“…Test access mechanism (TAM) is an important element of test access architectures for embedded cores and is responsible for on-chip test patterns transport from the source to the core under test to the sink. …”
Get full text
Get full text
Get full text
Get full text

Editorial on the Special Section on Algorithms, Circuits, and Systems for Signal Processing at the Edge by Leonel Sousa (19645372)

“…This special Section is exactly focused on addressing challenges raised by moving computation to the edge in a holistic way, by examining not only challenges related to algorithmic consideration and computational requirements but also circuits and systems and hardware platforms suitable for such implementation. …”

Integrating genetic algorithms, tabu search, and simulatedannealing for the unit commitment problem by Mantawy, A.H.

“…This paper presents a new algorithm based on integrating genetic algorithms, tabu search and simulated annealing methods to solve the unit commitment problem. …”
Get full text
Get full text