Search alternatives:
using function » using fusion (Expand Search)
algorithm goa » algorithm _ (Expand Search), algorithms a (Expand Search)
algorithm fa » algorithm _ (Expand Search), algorithms a (Expand Search), algorithms _ (Expand Search)
using function » using fusion (Expand Search)
algorithm goa » algorithm _ (Expand Search), algorithms a (Expand Search)
algorithm fa » algorithm _ (Expand Search), algorithms a (Expand Search), algorithms _ (Expand Search)
-
141
On the Optimization of Band Gaps in Periodic Waveguides
Published 2025“…For the first optimization scenario, distribution-free analysis showed that at intermediate function evaluation budgets, detectable differences emerge among algorithms, whereas in the second scenario, these differences diminish at higher evaluation budgets (with no significant pairwise contrasts), indicating convergence. …”
-
142
Modelling Exchange Rates during Currency Crisis using Neural Networks
Published 2006“…This paper presents an artificial neural network (ANN) approach to the forecasting of exchange rate movements during periods of currency crises characterized by excessive volatility. The models are built using the feedforward ANN structure trained by the backpropagation algorithm. …”
Get full text
Get full text
Get full text
conferenceObject -
143
-
144
Parameter Identification of Flexible Drive Systems using Particle Swarm Optimization
Published 2023Get full text
doctoralThesis -
145
Vibration suppression in a cantilever beam using a string-type vibration absorber
Published 2017“…In the first, the spring stiffness, the position of the second attachment point of the string and a preliminary damping constant are calculated using a genetic algorithm approach where the objective function is the maximum displacement on the beam. …”
Get full text
Get full text
Get full text
Get full text
conferenceObject -
146
Intelligent Bilateral Client Selection in Federated Learning Using Game Theory
Published 2022“…To overcome this problem, we present in this paper FedMint, an intelligent client selection approach for federated learning on IoT devices using game theory and bootstrapping mechanism. Our solution involves designing (1) preference functions for the client IoT devices and federated servers to allow them to rank each other according to several factors such as accuracy and price, (2) intelligent matching algorithms that take into account the preferences of both parties in their design, and (3) bootstrapping technique that capitalizes on the collaboration of multiple federated servers in order to assign initial accuracy value for the new connected IoT devices. …”
Get full text
Get full text
Get full text
masterThesis -
147
Joint distributed synchronization and positioning in UWB ad hoc networks using TOA
Published 2006“…Finally, the proposed distributed maximum log-likelihood algorithm proves to preserve a reasonable level of complexity in each node by approximating asynchronously the positive gradient direction of the log-likelihood function. …”
Get full text
Get full text
Get full text
article -
148
Distinguishing Between Fake and Real Smiles Using EEG Signals and Deep Learning
Published 2020Get full text
doctoralThesis -
149
A Hybrid Transfer Learning Approach to Teeth Diagnosis Using Orthopantomogram Radiographs
Published 2024“…Fortunately, the availability of modern computing devices has made the automated diagnosis of teeth readily possible using deep learning. Despite this, concerns about the accuracy and function of automated diagnosis remain among patients. …”
Get full text
article -
150
The Use of Enumerative Techniques in Topological Optimization of Computer Networks Subject to Fault Tolerance and Reliability
Published 2003“…Experimental results obtained from a set of randomly generated networks using the proposed algorithms are presented and compared to those obtained using the existing techniques [1], [2]. …”
Get full text
article -
151
Modeling and Identification of Nonlinear DC Motor Drive Systems Using Recurrent Wavelet Networks
Published 2013Get full text
doctoralThesis -
152
Optimization of Commercially Off the Shelf (COTS) Electric Propulsion System for Low Speed Fuel Cell UAV
Published 2013Get full text
doctoralThesis -
153
-
154
Isolating Physical Replacement of Identical IoT Devices Using Machine and Deep Learning Approaches
Published 2021Get full text
doctoralThesis -
155
Adaptive Secure Pipeline for Attacks Detection in Networks with set of Distribution Hosts
Published 2022“…So far none addresses the use of Threat Intelligence (IT) data in Ensemble Learning algorithms to improve the detection process, nor does it work as a function of time, that is, taking into account what happens on the network in a limited time interval. …”
Get full text
-
156
Autism Detection of MRI Brain Images Using Hybrid Deep CNN With DM-Resnet Classifier
Published 2023“…The hyper parameters are optimized with DM optimization algorithm which improves the accuracy of classifier. …”
Get full text
Get full text
-
157
Fleet sizing of trucks for an inter-facility material handling system using closed queueing networks
Published 2022“…<p>Material handling systems (MHS) are integral to logistics functions by providing various supports such as handling, moving, and storing materials in manufacturing and service organisations. …”
-
158
StackDPPred: Multiclass prediction of defensin peptides using stacked ensemble learning with optimized features
Published 2024“…Additionally, we applied the local interpretable model-agnostic explanations (LIME) algorithm to understand the contribution of selected features to the overall prediction. …”
-
159
Energy utilization assessment of a semi-closed greenhouse using data-driven model predictive control
Published 2021“…The proposed method consists of a multilayer perceptron model representing the greenhouse system integrated with an objective function and an optimization algorithm. The multilayer perceptron model is trained using historical data from the greenhouse with solar radiation, outside temperature, humidity difference, fan speed, HVAC control as the input parameters to predict the temperature. …”
-
160
Crashworthiness optimization of composite hexagonal ring system using random forest classification and artificial neural network
Published 2024“…Advanced machine learning algorithms are used in this study to figure out the complicated relationship between the crashworthiness parameters of the hexagonal composite ring specimens under lateral compressive, energy absorption, and failure modes. …”