Search Results - (( java implementation among algorithm ) OR ( program solution mining algorithm ))*
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1
Plagiarism Detection System for Java Programming Assignments by Using Greedy String-Tilling Algorithm
Published 2008“…The prototype system, known as Java Plagiarism Detection System (JPDS) implements the Greedy-String-Tiling algorithm to detect similarities among tokens in a Java source code files. …”
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Thesis -
2
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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A Toolkit for Simulation of Desktop Grid Environment
Published 2014“…A simulator for desktop grid environment has been developed using Java as the implementation language due to its wide popularity. …”
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Measuring GPU-accelerated parallel SVM performance using large datasets for multi-class machine learning problem
Published 2023Conference Paper -
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Talent classification using support vector machine technique / Hamidah Jantan, Norazmah Mat Yusof and Mohd Hanapi Abdul Latif
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Research Reports -
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OPTIMIZED MIN-MIN TASK SCHEDULING ALGORITHM FOR SCIENTIFIC WORKFLOWS IN A CLOUD ENVIRONMENT
Published 2023“…According to the simulation results, the proposed algorithm produces the best solution among all algorithms in the proposed cases. � 2021 Little Lion Scientific…”
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Network game (Literati) / Chung Mei Kuen
Published 2003“…The main aspect of this thesis is to produce a networked gaming system, which process players. requested to play the game and enabling users to play the graphical game with people through the network. The algorithm design and implementation method must not only be workable, but also highly efficient in terms of execution speed and response time. …”
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8
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. …”
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Comparison of performances of Jaya Algorithm and Cuckoo Search algorithm using benchmark functions
Published 2022“…CS and JA have implemented in the same platform (Intellij IDEA Community Edition 2020.2.3) using the same language (Java). …”
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10
Towards a better feature subset selection approach
Published 2010“…The selection of the optimal features subset and the classification has become an important issue in the data mining field.We propose a feature selection scheme based on slicing technique which was originally proposed for programming languages.The proposed approach called Case Slicing Technique (CST).Slicing means that we are interested in automatically obtaining that portion 'features' of the case responsible for specific parts of the solution of the case at hand.We show that our goal should be to eliminate the number of features by removing irrelevant once.Choosing a subset of the features may increase accuracy and reduce complexity of the acquired knowledge.Our experimental results indicate that the performance of CST as a method of feature subset selection is better than the performance of the other approaches which are RELIEF with Base Learning Algorithm (C4.5), RELIEF with K-Nearest Neighbour (K-NN), RELIEF with Induction of Decision Tree Algorithm (ID3) and RELIEF with Naïve Bayes (NB), which are mostly used in the feature selection task.…”
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11
Long-term electrical energy consumption: Formulating and forecasting via optimized gene expression programming / Seyed Hamidreza Aghay Kaboli
Published 2018“…To assess the applicability and accuracy of the proposed method for long-term electrical energy consumption, its estimates are compared with those obtained from artificial neural network (ANN), support vector regression (SVR), adaptive neuro-fuzzy inference system (ANFIS), rule-based data mining algorithm, GEP, linear, quadratic and exponential models optimized by particle swarm optimization (PSO), cuckoo search algorithm (CSA), artificial cooperative search (ACS) algorithm and backtracking search algorithm (BSA). …”
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12
Problem restructuring in interger programming for reduct searching
Published 2003“…In effect, they are very useful in generating rules when solving the classification problem that is inherent in data mining. The thesis emphasizes mainly on the improvement of the original SIP/DRIP algorithm in term of performance. …”
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Web page design for electronic commerce / Lee Fong Wai
Published 2003“…The sixth part covers the system implementation that involved the transformation of modules and algorithm into implementable commands by using the specified programming languages. …”
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14
Classification models for higher learning scholarship award decisions
Published 2018“…In this study, a data mining approach was used to propose a classification model of scholarship award result determination. …”
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Network monopoly / Tan Kean Yeap
Published 2002“…The main aspect of this thesis is to produce a network monopoly system, which process multiple game sessions concurrently, enabling users to play the graphical game with people within the network. The algorithm design and implementation method mustnot only be workable, but also highly efficient in terms of execution speed and respond time. …”
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16
Batch mode heuristic approaches for efficient task scheduling in grid computing system
Published 2016“…Many algorithms have been implemented to solve the grid scheduling problem. …”
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Dynamic and adaptive execution models for data stream mining applications in mobile edge cloud computing systems / Muhammad Habib Ur Rehman
Published 2016“…At application level, the program components need to handle continuously streaming data in order to perform knowledge discovery operations. …”
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19
K Nearest Neighbor Joins And Mapreduce Process Enforcement For The Cluster Of Data Sets In Bigdata
Published 2018“…K Nearest Neighbor Joins (KNN join) are regarded as highly primitive and expensive operations in the data mining.The efficient use of KNN join has proven good results in finding the objects from two data sets prevailed in the huge databases.This has been achieved with the combination of K-Nearest Neighbor query and join operation to find the distinct objects from different data sets.MapReduce is a newly introduced program with the combination of Map Procedure method and Reduce Method widely used in BigData.MapReduce is enriched with parallel distributed algorithm to find the results on a cluster of data sets in BigData.In this paper,the combination of KNN join and MapReduce methods are utilized on the cluster of data sets in BigData for knowledge discovery.Exploring the pinpoint data from huge data sets stored in Big Data demands the distributed large scale data processing.The present research paper is focusing on generic steps for KNN joins exploration operations on MapReduce.The operations of KNN Join are targeted to perform the data partitioning and data pre-processing and necessary calculations.By utilizing the combination of KNN joins with MapReduce methods on BigData data sets will demonstrate a solution for complex computational analysis. …”
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Smart student timetable planner
Published 2025“…To achieve these objectives, the system adopts the Rapid Application Development (RAD) methodology, ensuring iterative design, prototyping, and user feedback integration throughout the process. The system is implemented using Node.js with Express for server-side development, HTML, CSS, and JavaScript for the frontend, and Socket.IO for real-time collaboration. …”
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Final Year Project / Dissertation / Thesis
