Search Results - (( based applications acs algorithm ) OR ( based application using (algorithmic OR algorithms) ))*
Search alternatives:
- based applications »
- based application »
- applications acs »
- acs algorithm »
-
1
-
2
-
3
Improvement DACS3 Searching Performance using Local Search
Published 2009Get full text
Get full text
Conference or Workshop Item -
4
-
5
Fast algorithm for VQ-based wavelet coding system
Published 2003Get full text
Get full text
Get full text
Proceeding Paper -
6
A New Near Optimal Harmonics Elimination PWM Algorithm For AC Traction Drives
Published 2002“…However, the application of HEPWM has been somewhat limited by the fact that the switching angles cannot be calculated online by a microprocessor-based waveform generator. …”
Get full text
Get full text
Get full text
Article -
7
Neural Networks based fault diagnosis of ac motors
Published 2008Get full text
Get full text
Conference or Workshop Item -
8
Ant colony optimization in dynamic environments
Published 2010“…In order to achieve this objective, six ant algorithms namely Ant System (AS), Ant Colony System (ACS), Best-Worst Ant System (BWAS), Elitist Ant System (EAS), Max-Min Ant System (MMAS) and Rank-Based Ant System (RBAS) were implemented to solve a dynamic optimization problem in the form of the dynamic Traveling Salesman Problem (TSP). …”
Get full text
Get full text
Get full text
Thesis -
9
-
10
-
11
Modified ACS centroid memory for data clustering
Published 2019“…Ant Colony Optimization (ACO) is a generic algorithm, which has been widely used in different application domains due to its simplicity and adaptiveness to different optimization problems. …”
Get full text
Get full text
Get full text
Article -
12
-
13
Facial image retrieval on semantic features using adaptive mean genetic algorithm
Published 2019“…Finally, the features are selected using Adaptive Mean Genetic Algorithm (AMGA). In this study, the average PSNR value obtained after applying Wiener filter was 45.29. …”
Get full text
Get full text
Get full text
Get full text
Article -
14
-
15
Multi-label learning based on positive label correlations using predictive apriori
Published 2019“…Along with that, two algorithms have been constructed by capturing the positive correlations where the first algorithm (MLR-PC) captures the positive global correlations and the second algorithm (MLCBA) proposes an adaption of AC algorithm to handle MLC based on the positive local correlations. …”
Get full text
Get full text
Get full text
Get full text
Thesis -
16
-
17
Adaptive Traffic Prioritization Algorithm Over Ad Hoc Network Using IEEE 802.11e
Published 2016“…This thesis proposes an adaptive traffic prioritization algorithm over ad hoc network using IEEE 802.11e standard that defines a set of Quality of Service enhancements for wireless LAN applications through modifications to the Media Access Control (MAC) layer. …”
Get full text
Get full text
Get full text
Get full text
Thesis -
18
Evolutionary mating algorithm
Published 2023Get full text
Get full text
Get full text
Get full text
Article -
19
Efficient back-off mechanism for multimedia support in IEEE 802.11E
Published 2012“…The current research proposes a new algorithm so-called Dynamic Fast Adaptation of back-off algorithm for contention-based EDCA (DFA-EDCA) mechanism. …”
Get full text
Get full text
Thesis -
20
Performance comparison of classification algorithms for EEG-based remote epileptic seizure detection in wireless sensor networks
Published 2014“…Identification of epileptic seizure remotely by analyzing the electroencephalography (EEG) signal is very important for scalable sensor-based health systems.Classification is the most important technique for wide-ranging applications to categorize the items according to its features with respect to predefined set of classes.In this paper, we conduct a performance evaluation based on the noiseless and noisy EEG-based epileptic seizure data using various classification algorithms including BayesNet, DecisionTable, IBK, J48/C4.5, and VFI.The reconstructed and noisy EEG data are decomposed with discrete cosine transform into several sub-bands.In addition, some of statistical features are extracted from the wavelet coefficients to represent the whole EEG data inputs into the classifiers.Benchmark on widely used dataset is utilized for automatic epileptic seizure detection including both normal and epileptic EEG datasets.The classification accuracy results confirm that the selected classifiers have greater potentiality to identify the noisy epileptic disorders.…”
Get full text
Get full text
Get full text
Conference or Workshop Item
