Search Results - (( java implementation modified algorithm ) OR ( using samples learning algorithm ))
Search alternatives:
- implementation modified »
- java implementation »
- learning algorithm »
- using samples »
-
1
Direct approach for mining association rules from structured XML data
Published 2012“…The thesis also provides a two different implementation of the modified FLEX algorithm using a java based parsers and XQuery implementation. …”
Get full text
Get full text
Thesis -
2
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. The objectives of this work are: i) to provide a comprehensive review of the cloud and scheduling process; ii) to classify the scheduling strategies and scientific workflows; iii) to implement our proposed algorithm with various scheduling algorithms (i.e., Min-Min, Round-Robin, Max-Min, and Modified Max-Min) for performance comparison, within different cloudlet sizes (i.e., small, medium, large, and heavy) in three scientific workflows (i.e., Montage, Epigenomics, and SIPHT); and iv) to investigate the performance of the implemented algorithms by using CloudSim. …”
Review -
3
Prevention And Detection Mechanism For Security In Passive Rfid System
Published 2013“…The proposed protocol is designed with lightweight cryptographic algorithm, including XOR, Hamming distance, rotation and a modified linear congruential generator (MLCG). …”
Get full text
Get full text
Thesis -
4
Automatic generation of content security policy to mitigate cross site scripting
Published 2016“…It can be extended to support generating CSP for contents that are modified by JavaScript after loading. Current approach inspects the static contents of URLs.…”
Get full text
Get full text
Conference or Workshop Item -
5
Alternate methods for anomaly detection in high-energy physics via semi-supervised learning
Published 2020“…In this paper, we introduce two new algorithms called EHRA and C-EHRA, which use machine learning regression and clustering to detect anomalies in samples. …”
Get full text
Get full text
Get full text
Article -
6
-
7
Evolutionary deep belief networks with bootstrap sampling for imbalanced class datasets
Published 2019“…However, when handling imbalanced class data, DBN encounters low performance as other machine learning algorithms. In this paper, the genetic algorithm (GA) and bootstrap sampling are incorporated into DBN to lessen the drawbacks occurs when imbalanced class datasets are used. …”
Get full text
Get full text
Get full text
Article -
8
-
9
-
10
Clustering ensemble learning method based on incremental genetic algorithms
Published 2012“…Moreover, experiments demonstrate that final clustering solution generated by the proposed incremental genetic-based clustering ensemble algorithm using the pattern ensemble learning method possess comparative or better clustering accuracy than clustering solutions generated by the incremental genetic-based clustering ensemble algorithms using other recombination operators. …”
Get full text
Get full text
Thesis -
11
Small Dataset Learning In Prediction Model Using Box-Whisker Data Transformation
Published 2020“…To test the effectiveness of the proposed algorithm, the real and generated samples is added to training phase to build a prediction model using M5 Model Tree. …”
Get full text
Get full text
Get full text
Get full text
Thesis -
12
Adaptive persistence layer for synchronous replication (PLSR) in heterogeneous system
Published 2011“…The PLSR architecture model, workflow and algorithms are described. The PLSR has been developed using Java Programming language. …”
Get full text
Get full text
Thesis -
13
A Comparative Analysis of Machine Learning and Deep Learning Algorithms for Image Classification
Published 2024“…CNN is a type of convolution neural network that has an unpredictable development and uses convolution calculations. It is one of the most well-known deep learning algorithms. …”
Conference Paper -
14
Advanced flood prediction at forest with rainfall data using various machine learning algorithms
Published 2024Get full text
Get full text
Conference or Workshop Item -
15
A Reference Based Surface Defect Segmentation Algorithm For Automatic Optical Inspection System
Published 2020“…Results show that the proposed algorithm required a learning dataset size as small as 5 samples and was resistant to learning labelling error up to 50%.…”
Get full text
Get full text
Thesis -
16
Hybrid sampling and random forest machine learning approach for software detect prediction
Published 2019“…Cross validation is used to remove overriding problem. Scikit-learn library is used for machine learning algorithms. …”
Get full text
Get full text
Get full text
Conference or Workshop Item -
17
Wavelet network based online sequential extreme learning machine for dynamic system modeling
Published 2013“…The main advantage of OSELM over conventional algorithms is the ability of updating network weights sequentially through data sample-by-sample in a single learning step. …”
Get full text
Conference or Workshop Item -
18
Predicting Customer Buying Decisions for Online Shopping with Unbalanced Data Set
Published 2022“…Weka, a data mining tool, provides the facility to classify the data set with different machine learning algorithms. Six machine learning algorithms were applied and compared based on the classification evaluation methods. …”
Get full text
Get full text
Final Year Project / Dissertation / Thesis -
19
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 -
20
