Search Results - (( java implementation among algorithm ) OR ( program selection mining algorithm ))
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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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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). …”
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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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Twofold Integer Programming Model for Improving Rough Set Classification Accuracy in Data Mining.
Published 2005“…The first task is to introduce a new rough model for minimum reduct selection and default rules generation, which is known as a Twofold Integer Programming (TIP). …”
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Genetic Algorithm for Web Data Mining
Published 2001“…By doing so, it could assist the process of data mining for information in the World Wide Web. This study used a prototype program based on genetic algorithm to manipulate the initial set of data. …”
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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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IP algorithms in compact rough classification modeling
Published 2001“…The paper presents the Integer Programming (IP) algorithms in mining a compact rough classification model. …”
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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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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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Study Of Modified Training Algorithm For Optimized Convergence Speed Of Neural Network
Published 2016“…First proposed algorithm is the combination of momentum algorithm with adaptive learning rate (ALR) algorithm, and second proposed algorithm is the combination of momentum algorithm with automatic learning rate selection (ALRS) algorithm. …”
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Exploring frogeye leaf spot disease severity in soybean through hyperspectral data analysis and machine learning with Orange Data Mining
Published 2025“…No previous study has investigated Orange mining tool as visual programming approach in analysing hyperspectral reflectance data, especially in crop disease detection. …”
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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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Long-term electrical energy consumption: Formulating and forecasting via optimized gene expression programming / Seyed Hamidreza Aghay Kaboli
Published 2018“…In the developed feature selection approach, multi-objective binary-valued backtracking search algorithm (MOBBSA) is used as an efficient evolutionary search algorithm to search within different combinations of input variables and selects the non-dominated feature subsets, which minimize simultaneously both the estimation error and the number of features. …”
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An efficient and effective case classification method based on slicing
Published 2006“…This paper introduces a new classification method based on slicing techniques that was proposed for procedural programming languages. The paper also discusses two of common classification algorithms that are used either in data mining or in general AI. …”
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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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A Data Mining-Based Model for Assessing Guangzhou's Higher Vocational Colleges 'New Energy Automobile Majors' Vocational Skills
Published 2024“…The approach employs algorithms for data mining to enhance the accuracy and accessibility of results through the use of Random Forest (RF) and Generalized Additive Models (GAM) in a layering architecture. …”
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Classification model for hotspot occurrences using spatial decision tree algorithm
Published 2013“…As the ID3 algorithm that uses information gain in the attribute selection, the proposed algorithm uses spatial information gain to choose the best splitting layer from a set of explanatory layers. …”
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