Search Results - (( java implementation new algorithm ) OR ( based evaluation learning algorithm ))
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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. …”
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Thesis -
2
Application of genetic algorithm and JFugue in an evolutionary music generator
Published 2025“…This project explores the application of Genetic Algorithms (GA) with JFugue, which is a Java-based music programming library to develop an Evolutionary Music Generator. …”
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Final Year Project / Dissertation / Thesis -
3
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 -
4
Fitness value based evolution algorithm approach for text steganalysis model
Published 2013“…In this paper, we present a new alternative method for text steganalysis based on an evolution algorithm, implemented using the Java Evolution Algorithms Package (JEAP).The main objective of this paper is to detect the existence of hidden messages ased on fitness values of a text description.It is found that the detection performance has been influenced by two groups of fitness values which are good fitness value and bad fitness value. …”
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Article -
5
Classification System for Heart Disease Using Bayesian Classifier
Published 2007“…This system was developing base on to three main part which is data processing, testing and implementation of the algorithm. In this system a Bayesian algorithm was used in order to implement the system. …”
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6
Biometrics electronic purse
Published 1999“…This paper looked into using biometrics as a mean of authentication, thus requiring a new generation of Smart Card technology to be implemented in banking and multiple applications environment. …”
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Proceeding Paper -
7
A Systematic Literature Review of Machine Learning Methods for Short-term Electricity Forecasting
Published 2023Conference Paper -
8
Case Slicing Technique for Feature Selection
Published 2004“…This technique with k = 10 has been used in this thesis to evaluate the proposed approach. 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). …”
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9
Modeling time series data using Genetic Algorithm based on Backpropagation Neural network
Published 2018“…This study showed the task of optimizing the topology structure and the parameter values (e.g., weights) used in the BPNN learning algorithm by using the GA. Based on the results obtained, a better prediction result can be produced by the proposed GA-BPNN learning algorithm.…”
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10
The Implementation of a Machine Learning-based Routing Algorithm in a Lab-Scale Testbed
Published 2024“…Due to network complexity, conventional QoS-improving routing algorithms (RAs) may be impractical. Thus, researchers are developing intelligent RAs, including machine learning (ML)-based algorithms to meet traffic Q oS r equirements. …”
Conference Paper -
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A New Machine Learning-based Hybrid Intrusion Detection System and Intelligent Routing Algorithm for MPLS Network
Published 2024“…The ML-based routing algorithm is compared to the conventional routing algorithm, Routing Information Protocol version 2 (RIPv2). …”
Article -
12
Evaluation of the Transfer Learning Models in Wafer Defects Classification
Published 2022“…Transfer Learning is one of the common methods. Various algorithms under Transfer Learning had been developed for different applications. …”
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Conference or Workshop Item -
13
Priority and dynamic quantum time algorithms for central processing unit scheduling
Published 2018“…The proposed algorithms (Priority Dynamic Quantum Time and Multi Priority Dynamic Quantum Time Algorithms) are implemented using JAVA programming language and validated using Key Performance Indicators equations. …”
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14
Modified Opposition Based Learning to Improve Harmony Search Variants Exploration
Published 2020“…Opposition-based learning variants enhanced the explorations and help optimization algorithms to avoid local optima falling. …”
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Conference or Workshop Item -
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PMT : opposition based learning technique for enhancing metaheuristic algorithms performance
Published 2020“…To evaluate the PMT’s performance and adaptability, the PMT was applied to four contemporary metaheuristic algorithms, Differential Evolution, Particle Swarm Optimization, Simulated Annealing, and Whale Optimization Algorithm, to solve 15 well-known benchmark functions as well as 2 real world problems based on the welded beam design and pressure vessel design. …”
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16
Face recognition and identification system (FaceRec) / Khew Jye Huei
Published 2004“…It describes the implementation and functions of a working system that performs the recognition and identification of human faces using the implement algorithms. …”
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17
Clustering ensemble learning method based on incremental genetic algorithms
Published 2012“…In the first and second phases, a threshold fuzzy c-means clustering algorithm as a clusterer and a pattern ensemble learning method based on the incremental genetic-based algorithms are proposed respectively. …”
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18
Web-based clustering tool using fuzzy k-mean algorithm / Ahmad Zuladzlan Zulkifly
Published 2019“…This project will use fuzzy k-means clustering algorithm to cluster the data because it is easy to implement and have many advantages. …”
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19
Analytical Study Of Machine Learning Models For Stock Trading In Malaysian Market
Published 2024“…By setting the ML algorithms and their parameter along with using Walk-Forward Analysis (WFA) method, the algorithm design of trading signal was evaluated based on two groups of evaluation indicators, namely directional and performance. …”
thesis::master thesis -
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Information Theoretic-based Feature Selection for Machine Learning
Published 2018“…Thus, this thesis has developed and evaluated a filter based Information Theoretic-based Feature Selection (IFS) for machine learning. …”
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