Search Results - (( java simulation optimization algorithm ) OR ( frequency classification learning algorithm ))
Search alternatives:
- frequency classification »
- classification learning »
- learning algorithm »
- java simulation »
-
1
Classification of JPEG files by using extreme learning machine
Published 2018“…The algorithm automatically classifies the files based on evaluation measures of three methods Entropy, Byte Frequency Distribution and Rate of Change. …”
Get full text
Get full text
Article -
2
Attribute reduction based scheduling algorithm with enhanced hybrid genetic algorithm and particle swarm optimization for optimal device selection
Published 2022“…The simulation is implemented with iFogSim and java programming language. …”
Get full text
Get full text
Article -
3
A two-stage learning convolutional neural network for sleep stage classification using a filterbank and single feature
Published 2022“…Due to the complications in manual sleep staging by the physician, computer-aided sleep stage classification algorithms are gaining attention. In this study, a novel approach was introduced to extract distinctive representations from single-channel EEG signal for automatic sleep staging. …”
Get full text
Get full text
Get full text
Get full text
Get full text
Article -
4
Enhancement of Ant Colony Optimization for Grid Job Scheduling and Load Balancing
Published 2011“…Global pheromone update is performed after the completion of processing the jobs in order to reduce the pheromone value of resources. A simulation environment was developed using Java programming to test the performance of the proposed EACO algorithm against existing grid resource management algorithms such as Antz algorithm, Particle Swarm Optimization algorithm, Space Shared algorithm and Time Shared algorithm, in terms of processing time and resource utilization. …”
Get full text
Get full text
Get full text
Thesis -
5
Extreme learning machine classification of file clusters for evaluating content-based feature vectors
Published 2018“…This paper studies the effects of three content-based features extraction methods in improving the classification of JPEG File clusters. The methods are Byte Frequency Distribution, Entropy, and Rate of Change. …”
Get full text
Article -
6
Ant colony optimization algorithm for load balancing in grid computing
Published 2012“…The proposed algorithm is known as the enhance ant colony optimization (EACO). …”
Get full text
Get full text
Get full text
Monograph -
7
Source code classification using latent semantic indexing with structural and frequency term weighting
Published 2012“…Based on the undertaken experiment the LSI classifier is noted to generate a higher precision and recall compared to the C4.5 algorithm. Furthermore,it is also learned that the use of structural information in the weighting scheme contribute to a better classification.…”
Get full text
Get full text
Get full text
Article -
8
Arabic Speaker Identification System for Forensic Authentication Using K-NN Algorithm
Published 2023“…Classification (of information); Data mining; Digital forensics; Forestry; Learning algorithms; Loudspeakers; Motion compensation; Nearest neighbor search; Speech recognition; Trees (mathematics); K-near neighbor; Logistic model tree; Logistics model; Mel frequency cepstral co-efficient; Mel frequency cepstral coefficient; Mel-frequency cepstral coefficients; Mining classification; Model trees; Nearest-neighbour; Speaker identification systems; Authentication…”
Conference Paper -
9
Task-state EEG signal classification for spatial cognitive evaluation based on multiscale high-density convolutional neural network
Published 2022“…By comparing the classification results of six frequency band combinations, it was found that the combination of the Theta-Beta2-Gamma band had the best classification effect. …”
Get full text
Get full text
Article -
10
Development of a syncope classification algorithm from physiological signals acquired in tilt-table test
Published 2023“…Syncope also known as transient loss of consciousness which caused problem to human daily life. Since machine learning is much more advanced, classification of syncope can be done with machine learning. …”
Get full text
Get full text
Final Year Project / Dissertation / Thesis -
11
-
12
-
13
Multi-label learning based on positive label correlations using predictive apriori
Published 2019“…Multi-label Learning (MLL) is a general task in data mining that consists of three main tasks: classification, label ranking, and multi-label ranking. …”
Get full text
Get full text
Get full text
Get full text
Thesis -
14
A Machine Learning Classification Approach To Detect Tls-Based Malware Using Entropy-Based Flow Set Features
Published 2022“…This study also investigates TLSMalDetect detection performance using seven ML classification algorithms and identifies the one with the highest accuracy.…”
Get full text
Get full text
Thesis -
15
Hybrid weight deep belief network algorithm for anomaly-based intrusion detection system
Published 2022“…In future, the HW-DBN algorithm can be proposed as an integrated deep Learning for the classification performance of attack detection models.…”
Get full text
Get full text
Get full text
Get full text
Thesis -
16
-
17
OPTIMIZED MIN-MIN TASK SCHEDULING ALGORITHM FOR SCIENTIFIC WORKFLOWS IN A CLOUD ENVIRONMENT
Published 2023“…To achieve this, we propose a new noble mechanism called Optimized Min-Min (OMin-Min) algorithm, inspired by the Min-Min algorithm. …”
Review -
18
Automatic detection and indication of pallet-level tagging from rfid readings using machine learning algorithms
Published 2020“…The ensemble learning technique, changes of activation function in Neural Network as well as the unsupervised learning (k-means clustering algorithm and Friis Transmission Equation) was also applied to classify the multiclass classification in pallet-level. …”
Get full text
Get full text
Thesis -
19
An Improved Network Intrusion Detection Method Based On CNN-LSTM-SA
Published 2025“…Using the NSL-KDD dataset for evaluation, the proposed method demonstrates superior performance compared to conventional algorithms and related deep learning techniques, achieving higher precision, recall, F1 scores and overall accuracy in both binary and multi-class classification tasks. …”
Get full text
Get full text
Get full text
Thesis -
20
