Search Results - (( time classification rules algorithm ) OR ( java simulation optimization algorithm ))
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1
Ant colony optimization algorithm for rule based classification: Issues and potential
Published 2018“…This paper presents a review of related work of ACO rule classification which emphasizes the types of ACO algorithms and issues. …”
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Article -
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New Learning Models for Generating Classification Rules Based on Rough Set Approach
Published 2000“…Thus, the challenge is how to develop an efficient model that can decrease the learning time without affecting the quality of the generated classification rules. …”
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Thesis -
3
Real-time Traffic Classification Algorithm Based on Hybrid of Signature Statistical and Port to Identify Internet Applications
Published 2014“…In addition, as demonstrated in the real time online experiments done, SSPC algorithm uses a short time to classify traffic and thus it is suitable to be used for online classification.…”
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4
Classification of stock market index based on predictive fuzzy decision tree
Published 2005“…The experimental results show that the predictive FDT algorithm and fuzzy reasoning method provides the reasonable performance for comprehensibility (no of rules), complexity (no of nodes) and predictive accuracy of WFPRs for stock market time series data.…”
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Thesis -
5
DATA CLASSIFICATION SYSTEM WITH FUZZY NEURAL BASED APPROACH
Published 2005“…The project's objective is identifying the available data mining algorithms in data classification and applying new data mining algorithm to perform classification tasks. …”
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Final Year Project -
6
Irrelevant feature and rule removal for structural associative classification
Published 2015“…In the classification task, the presence of irrelevant features can significantly degrade the performance of classification algorithms,in terms of additional processing time, more complex models and the likelihood that the models have poor generalization power due to the over fitting problem.Practical applications of association rule mining often suffer from overwhelming number of rules that are generated, many of which are not interesting or not useful for the application in question.Removing rules comprised of irrelevant features can significantly improve the overall performance.In this paper, we explore and compare the use of a feature selection measure to filter out unnecessary and irrelevant features/attributes prior to association rules generation.The experiments are performed using a number of real-world datasets that represent diverse characteristics of data items.Empirical results confirm that by utilizing feature subset selection prior to association rule generation, a large number of rules with irrelevant features can be eliminated.More importantly, the results reveal that removing rules that hold irrelevant features improve the accuracy rate and capability to retain the rule coverage rate of structural associative association.…”
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7
Compressing and improving fuzzy rules using genetic algorithm and its application to fault detection
Published 2023“…Therefore, it reveals the efficacy of DC-GA in eliciting a set of compact and yet easily comprehensible rules while sustaining a high classification performance. � 2013 IEEE.…”
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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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10
Direct least squares fitting of ellipses segmentation and prioritized rules classification for curve-shaped chart patterns
Published 2021“…To further enhance the efficiency of classifying chart patterns from real-time streaming data, we propose a novel algorithm called Accelerating Classification with Prioritized Rules (ACPR). …”
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Predicting heart disease using ant colony optimization / Siti Aisyah Ismail
Published 2021“…Thus, this study used the Ant Colony Optimization algorithm with data mining called Ant-Miner to predict heart disease because it is said that Ant-Miner’s rule list is simpler than other rule induction algorithms. …”
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Student Project -
12
Power quality problem classification based on Wavelet Transform and a Rule-Based method
Published 2010“…This paper describes a Wavelet Transform and Rule-Based method for detection and classification of various events of power quality disturbances. …”
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13
FURIA stacking ensemble for ASD classification
Published 2022“…Instead of relying on conventional domain expert rules, one possible solution is adapting fuzzy rules by proposing the Fuzzy Unordered Rule Induction Algorithm (FURIA) and the machine learning algorithms by collaborating them into the stacking ensemble framework. …”
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Prediction of breast cancer relapse time in continuous scale based on type-2 TSK fuzzy model
Published 2010“…In the first objective of the thesis, a lemma has been proven and a new hybrid algorithm based on Fuzzy Association Rule Mining has been proposed to gather some selected genes and generate fuzzy rules for classification. …”
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Thesis -
15
Dingle's Model-based EEG Peak Detection using a Rule-based Classifier
Published 2015“…The algorithm is developed into three stages: peak candidate detection, feature extraction, and classification. …”
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Stock market turning points rule-based prediction / Lersak Photong … [et al.]
Published 2021“…Simultaneously, news sentiment analysis techniques were used to discover the polarity of news according to each factor. From news classification and news sentiment, a rule-based algorithm was used to predict the stock market turning points. …”
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Book Section -
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Power Quality Problem Classification Based on Wavelet Transform and a Rule-Based method
Published 2010“…This paper describes a Wavelet Transform and Rule-Based method for detection and classification of various events of power quality disturbances. …”
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18
Power Quality Problem Classification Based on Wavelet Transform and a Rule-Based method
Published 2010“…This paper describes a Wavelet Transform and Rule-Based method for detection and classification of various events of power quality disturbances. …”
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19
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. …”
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Thesis -
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Ant colony optimization algorithm for load balancing in grid computing
Published 2012“…The proposed algorithm is known as the enhance ant colony optimization (EACO). …”
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