Search alternatives:
processing algorithm » processing algorithms (Expand Search)
research algorithm » search algorithm (Expand Search)
method algorithm » mould algorithm (Expand Search)
element » elements (Expand Search)
processing algorithm » processing algorithms (Expand Search)
research algorithm » search algorithm (Expand Search)
method algorithm » mould algorithm (Expand Search)
element » elements (Expand Search)
-
201
Economic load dispatch using memetic sine cosine algorithm
Published 2022“…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
-
202
An efficient method for the open-shop scheduling problem using simulated annealing
Published 2016“…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
conferenceObject -
203
Power Control Algorithms for Media Transmission in Remote Healthcare Systems
Published 2018“…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. …”
-
204
Multiclass feature selection with metaheuristic optimization algorithms: a review
Published 2022“…Datasets can be classified using various methods. Nevertheless, metaheuristic algorithms attract substantial attention to solving different problems in optimization. …”
Get full text
-
205
Exploring Semi-Supervised Learning Algorithms for Camera Trap Images
Published 2022Get full text
doctoralThesis -
206
Interval-Valued SVM Based ABO for Fault Detection and Diagnosis of Wind Energy Conversion Systems
Published 2022“…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. …”
-
207
A new minimum curvator multi-step method for unconstrained optimization
Published 1998“…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
conferenceObject -
208
An efficient approach for textual data classification using deep learning
Published 2022“…Textual data contains much useless information that must be pre-processed. …”
-
209
Bee colony algorithm for assigning proctors to exams. (c2013)
Published 2013Get full text
Get full text
masterThesis -
210
Parameter Estimation Of Wiener-Hammerstein Models Via Genetic Algorithms
Published 2020“…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
article -
211
Deep Learning-Based Short-Term Load Forecasting Approach in Smart Grid With Clustering and Consumption Pattern Recognition
Published 2021“…Whilst different models are proposed for STLF, they are based on small historical datasets and are not scalable to process large amounts of big data as energy consumption data grow exponentially in large electric distribution networks. …”
-
212
Methods for system-on-chip test design, scheduling and optimization. (c2006)
Published 2006Get full text
Get full text
masterThesis -
213
-
214
Development of a cerebral aneurysm segmentation method to prevent sentinel hemorrhage
Published 2023“…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. …”
-
215
Combinatorial method for bandwidth selection in wind speed kernel density estimation
Published 2019“…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
-
216
Extended Behavioral Modeling of FET and Lattice-Mismatched HEMT Devices
Published 2016Get full text
doctoralThesis -
217
The Frontiers of Deep Reinforcement Learning for Resource Management in Future Wireless HetNets: Techniques, Challenges, and Research Directions
Published 2022“…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. …”
-
218
Assessment of static pile design methods and non-linear analysis of pile driving
Published 2006“…The pile/soil interaction system is described by a mass/spring/dashpot system where the properties of each component are derived from rigorous analytical solutions or finite element analysis. The outcome of this research is an algorithm that can be used to predict pile displacement and driving stresses. …”
Get full text
Get full text
Get full text
masterThesis -
219
Wearable wrist to finger photoplethysmogram translation through restoration using super operational neural networks based 1D-CycleGAN for enhancing cardiovascular monitoring
Published 2024“…<h3>Background and Motivations</h3><p dir="ltr">Physiological signals, such as the Photoplethysmogram (PPG) collected through wearable devices, consistently encounter significant motion artifacts. Current signal processing techniques, and even state-of-the-art machine learning algorithms, frequently struggle to effectively restore the inherent bodily signals amidst the array of randomly generated distortions. …”
-
220
Cryptocurrency Exchange Market Prediction and Analysis Using Data Mining and Artificial Intelligence
Published 2020“…One of the best algorithms in terms of the result is the Long Short Term Memory (LSTM) since it is based on recurrent neural networks which uses loop as a method to learn from heuristics data. …”
Get full text