Search Results - (( rule generation learning algorithm ) OR ( java simulation optimization algorithm ))

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  1. 1
    New Learning Models for Generating Classification Rules Based on Rough Set Approach

    New Learning Models for Generating Classification Rules Based on Rough Set Approach by Al Shalabi, Luai Abdel Lateef

    Published 2000
    “…Also, the proposed models for learning in data sets generated the classification rules faster than other methods. …”
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  2. 2
    A Hybrid of Ant Colony Optimization Algorithm and Simulated Annealing for Classification Rules

    A Hybrid of Ant Colony Optimization Algorithm and Simulated Annealing for Classification Rules by Rizauddin, Saian

    Published 2013
    “…Previous studies have shown that ACO is a promising machine learning technique to generate classification rules. …”
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  3. 3
    Frequent Lexicographic Algorithm for Mining Association Rules

    Frequent Lexicographic Algorithm for Mining Association Rules by Mustapha, Norwati

    Published 2005
    “…The primary concept of association rule algorithms consist of two phase procedure. In the first phase, all frequent patterns are found and the second phase uses these frequent patterns in order to generate all strong rules. …”
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  4. 4
    Attribute reduction based scheduling algorithm with enhanced hybrid genetic algorithm and particle swarm optimization for optimal device selection

    Attribute reduction based scheduling algorithm with enhanced hybrid genetic algorithm and particle swarm optimization for optimal device selection by Nwogbaga, Nweso Emmanuel, Latip, Rohaya, Affendey, Lilly Suriani, Abdul Rahiman, Amir Rizaan

    Published 2022
    “…The simulation is implemented with iFogSim and java programming language. …”
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  5. 5
    Twofold Integer Programming Model for Improving Rough Set Classification Accuracy in Data Mining.

    Twofold Integer Programming Model for Improving Rough Set Classification Accuracy in Data Mining. by Saeed, Walid

    Published 2005
    “…Total rules number, rules length and rules accuracy for the generation rules are recorded. …”
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  6. 6
    Forecasting hydrological parameters for reservoir system utilizing artificial intelligent models and exploring their influence on operation performance

    Forecasting hydrological parameters for reservoir system utilizing artificial intelligent models and exploring their influence on operation performance by Allawi, Mohammed Falah, Jaafar, Othman, Mohamad Hamzah, Firdaus, Koting, Suhana, Mohd, Nuruol Syuhadaa, El-Shafie, Ahmed

    Published 2019
    “…Several research efforts have been developed to generate optimal operation rules for dam and reservoir systems utilizing different optimization algorithms. …”
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  7. 7
    Self learning neuro-fuzzy modeling using hybrid genetic probabilistic approach for engine air/fuel ratio prediction

    Self learning neuro-fuzzy modeling using hybrid genetic probabilistic approach for engine air/fuel ratio prediction by Al-Himyari, Bayadir Abbas

    Published 2017
    “…The model was compared to other learning algorithms for NFS such as Fuzzy c-means (FCM) and grid partition algorithm. …”
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  8. 8
    Enhancement of Ant Colony Optimization for Grid Job Scheduling and Load Balancing

    Enhancement of Ant Colony Optimization for Grid Job Scheduling and Load Balancing by Husna, Jamal Abdul Nasir

    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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  9. 9
    Ant colony optimization algorithm for load balancing in grid computing

    Ant colony optimization algorithm for load balancing in grid computing by Ku-Mahamud, Ku Ruhana, Mohamed Din, Aniza

    Published 2012
    “…The proposed algorithm is known as the enhance ant colony optimization (EACO). …”
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  10. 10
    An Apriori-based Data Analysis on Suspicious Network Event Recognition

    An Apriori-based Data Analysis on Suspicious Network Event Recognition by Jian, Z., Sakai, H., Watada, J., Roy, A., Hassan, M.H.B.

    Published 2019
    “…Furthermore, two algorithms preserve the logical property 'completeness,' so they generate rules without excess and deficiency. …”
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  11. 11
    Enhancing predictive crime mapping model using association rule mining for geographical and demographic structure

    Enhancing predictive crime mapping model using association rule mining for geographical and demographic structure by Asmai, S. A.

    Published 2014
    “…The other 40% of the dataset is used to test generated rules. A simple program of C++ is implemented using Microsoft Visual Studio to test generated rules until accuracy of performance is obtained. …”
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  12. 12
    An ELM-based single input rule module and its application in power generation

    An ELM-based single input rule module and its application in power generation by Yaw C.T., Wong S.Y., Yap K.S.

    Published 2023
    “…Extreme Learning Machine (ELM) is widely known as an effective learning algorithm than the conventional learning methods from the point of learning speed as well as generalization. …”
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  13. 13
    Fuzzy rules reduction using rough set approach

    Fuzzy rules reduction using rough set approach by Yusof, Norazah, Hamdan, Abdul Razak

    Published 2003
    “…This paper presents the use of Rough Set approach to compute reducts and generate concise fuzzy rules from a fuzzy rule base system of a student model. …”
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  14. 14
    Hybrid ant colony optimization and genetic algorithm for rule induction

    Hybrid ant colony optimization and genetic algorithm for rule induction by Al-Behadili, Hayder Naser Khraibet, Ku-Mahamud, Ku Ruhana, Sagban, Rafid

    Published 2020
    “…In our proposed hybrid ACO/GA algorithm, the ACO is responsible for generating classification rules and the GA improves the classification rules iteratively using the principles of multi-neighborhood structure (i.e., mutation and crossover) procedures to overcome the local optima problem. …”
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  15. 15
    Operating a reservoir system based on the shark machine learning algorithm

    Operating a reservoir system based on the shark machine learning algorithm by Allawi, Mohammed Falah, Jaafar, Othman, Mohamad Hamzah, Firdaus, Ehteram, Mohammad, Hossain, Md Shabbir, El-Shafie, Ahmed

    Published 2018
    “…In the current study, the shark machine learning algorithm (SMLA) is proposed to develop an optimal rule for operating the reservoir. …”
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  16. 16
    Data mining reduction methods and performances of rules

    Data mining reduction methods and performances of rules by Ahmad, Faudziah, Basir, Mohammad Aizat

    Published 2009
    “…In data mining the accuracy of models are associated with the strength of the rules.However, most machine learning techniques produce a large number of rules.The consequence is with large number of rules generated,processing time is much longer. …”
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  17. 17
    Operating a reservoir system based on the shark machine learning algorithm

    Operating a reservoir system based on the shark machine learning algorithm by Allawi M.F., Jaafar O., Mohamad Hamzah F., Ehteram M., Hossain M.S., El-Shafie A.

    Published 2023
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  18. 18
    Penggunaan penggugusan subtraktif bagi menjana peraturan kabur

    Penggunaan penggugusan subtraktif bagi menjana peraturan kabur by Agus Priyono, Muhammad Ridwan, Ahmad Jais Alias, Riza Atiq O. K. Rahmat, Azmi Hassan, Mohd. Alauddin Mohd. Ali

    Published 2005
    “…The basic idea in this paper work is how to learn and generate the optimum rules that required controlling input without decreasing the control quality. …”
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  19. 19
    Comparing the knowledge quality in rough classifier and decision tree classifier

    Comparing the knowledge quality in rough classifier and decision tree classifier by Mohamad Mohsin, Mohamad Farhan, Abd Wahab, Mohd Helmy

    Published 2008
    “…Theoretically, different classifiers will generate different sets of rules via knowledge even though they are implemented to the same classification problem.Hence, the aim of this paper is to investigate the quality of knowledge produced by Rc and DTc when similar problems are presented to them.In this case, four important performance metrics are used as comparison, the accuracy of classification, rules quantity, rules length and rules coverage.Five dataset from UCI Machine Learning are chosen and then mined using Rc toolkit namely ROSETTA while C4.5 algorithm in WEKA application is chosen as DTc rule generator. …”
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  20. 20
    A Hybrid Rough Sets K-Means Vector Quantization Model For Neural Networks Based Arabic Speech Recognition

    A Hybrid Rough Sets K-Means Vector Quantization Model For Neural Networks Based Arabic Speech Recognition by Babiker, Elsadig Ahmed Mohamed

    Published 2002
    “…A vector quantization model that incorporate rough sets attribute reduction and rules generation with a modified version of the K-means clustering algorithm was developed, implemented and tested as a part of a speech recognition framework, in which the Learning Vector Quantization (LVQ) neural network model was used in the pattern matching stage. …”
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