Search Results - (( using feature learning algorithm ) OR ( java simulation optimization algorithm ))
Search alternatives:
- learning algorithm »
- feature learning »
- java simulation »
-
1
Features selection for intrusion detection system using hybridize PSO-SVM
Published 2016“…Features selection process can be considered a problem of global combinatorial optimization in machine learning. …”
Get full text
Get full text
Thesis -
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
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 -
4
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 -
5
Improved Salp Swarm Algorithm based on opposition based learning and novel local search algorithm for feature selection
Published 2020“…These problems will occur because these fields are mainly used machine learning classifiers. However, machine learning accuracy is affected by the noisy and irrelevant features. …”
Get full text
Get full text
Article -
6
Semi-supervised learning for feature selection and classification of data / Ganesh Krishnasamy
Published 2019“…The proposed algorithm is compared with the state-of-the-art feature selection algorithms using three different datasets. …”
Get full text
Get full text
Get full text
Thesis -
7
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 -
8
Case Slicing Technique for Feature Selection
Published 2004“…CST was compared to other selected classification methods based on feature subset selection such as Induction of Decision Tree Algorithm (ID3), Base Learning Algorithm K-Nearest Nighbour Algorithm (k-NN) and NaYve Bay~sA lgorithm (NB). …”
Get full text
Get full text
Thesis -
9
Phylogenetic tree classification system using machine learning algorithm
Published 2015“…A study is conducted to develop an automated phylogenetic tree image classification system by using machine learning algorithm. This study adopted supervised machine learning algorithm which is the Support Vector Machine (SVM) for classification. …”
Get full text
Get full text
Get full text
Final Year Project Report / IMRAD -
10
Embedded system for indoor guidance parking with Dijkstra’s algorithm and ant colony optimization
Published 2019“…This study proposes a car parking management system which applies Dijkstra’s algorithm, Ant Colony Optimization (ACO) and Binary Search Tree (BST) in structuring a guidance system for indoor parking. …”
Get full text
Get full text
Thesis -
11
An ensemble learning method for spam email detection system based on metaheuristic algorithms
Published 2015“…In the second phase, a classifier ensemble learning model is proposed consisting of separate outputs: (i) To select a relevant subset of original features based on Binary Quantum Gravitational Search Algorithm (QBGSA), (ii) To mine data streams using various data chunks and overcome a failure of single classifiers based on SVM, MLP and K-NN algorithms. …”
Get full text
Get full text
Thesis -
12
Impact learning : A learning method from feature’s impact and competition
Published 2023“…A variety of well-known machine learning algorithms have been developed for use in the field of computer science to analyze data. …”
Get full text
Get full text
Get full text
Get full text
Article -
13
Opposition-Based Learning Binary Bat Algorithm as Feature Selection Approach in Taguchi's T-Method
Published 2024“…Thus, this study proposed an Opposition-based Learning Binary Bat Algorithm as the feature selection technique in the T-method. …”
Conference Paper -
14
Automated feature selection using boruta algorithm to detect mobile malware
Published 2020“…Boruta algorithm is used to select features automatically for assisting the machine learning. …”
Get full text
Get full text
Get full text
Article -
15
Impact learning: A learning method from feature's impact and competition
Published 2023“…A variety of well-known machine learning algorithms have been developed for use in the field of computer science to analyze data. …”
Get full text
Get full text
Get full text
Article -
16
Impact learning: A learning method from feature’s impact and competition
Published 2023“…A variety of well-known machine learning algorithms have been developed for use in the field of computer science to analyze data. …”
Get full text
Get full text
Get full text
Get full text
Article -
17
Improved whale optimization algorithm for feature selection in Arabic sentiment analysis
Published 2019“…The proposed algorithm is compared with six well-known optimization algorithms and two deep learning algorithms. …”
Get full text
Get full text
Article -
18
Performance comparison of feature selection methods for prediction in medical data
Published 2023“…Thus, feature selection should be fully utilized and applied when building machine learning algorithm. …”
Get full text
Get full text
Get full text
Get full text
Get full text
Proceeding Paper -
19
Privacy Preserving Features Selection for Data Mining using Machine Learning Algorithms
Published 2023Conference Paper -
20
Information Theoretic-based Feature Selection for Machine Learning
Published 2018“…Three major factors that determine the performance of a machine learning are the choice of a representative set of features, choosing a suitable machine learning algorithm and the right selection of the training parameters for a specified machine learning algorithm. …”
Get full text
Get full text
Get full text
Get full text
Thesis
