Search Results - (( parallel generation learning algorithm ) OR ( java application mining algorithm ))

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  1. 1
    Direct approach for mining association rules from structured XML data

    Direct approach for mining association rules from structured XML data by Abazeed, Ashraf Riad

    Published 2012
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  2. 2
    Separator Database and SPM Tree Framework for Mining Sequential Patterns Using Prefixspan with Pseudoprojection

    Separator Database and SPM Tree Framework for Mining Sequential Patterns Using Prefixspan with Pseudoprojection by Saputra , Dhany, Rambli, Dayang R.A., Foong, Oi Mean

    Published 2008
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  3. 3
    PMT : opposition based learning technique for enhancing metaheuristic algorithms performance

    PMT : opposition based learning technique for enhancing metaheuristic algorithms performance by Hammoudeh, S. Alamri

    Published 2020
    “…Addressing these OBL limitations, this research proposes a new general OBL technique inspired by a natural phenomenon of parallel mirrors systems called the Parallel Mirrors Technique (PMT). …”
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  4. 4
    Study and Implementation of Data Mining in Urban Gardening

    Study and Implementation of Data Mining in Urban Gardening by Mohana, Muniandy, Lee, Eu Vern

    Published 2019
    “…Attached sensors generate data and send these data to the Java Servlet application through a WIFI module. These data are processed and stored in appropriate formats in a MySQL server database. …”
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  5. 5
    PMT: opposition-based learning technique for enhancing meta-heuristic performance

    PMT: opposition-based learning technique for enhancing meta-heuristic performance by Alamri, Hammoudeh S., Kamal Z., Zamli

    Published 2019
    “…Addressing these issues, this research proposes a new general opposition-based learning (OBL) technique inspired by a natural phenomenon of parallel mirrors systems called the parallel mirrors technique (PMT). …”
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  6. 6
    Parallel power load abnormalities detection using fast density peak clustering with a hybrid canopy-K-means algorithm

    Parallel power load abnormalities detection using fast density peak clustering with a hybrid canopy-K-means algorithm by Al-Jumaili A.H.A., Muniyandi R.C., Hasan M.K., Singh M.J., Paw J.K.S., Al-Jumaily A.

    Published 2025
    “…Parallel power loads anomalies are processed by a fast-density peak clustering technique that capitalizes on the hybrid strengths of Canopy and K-means algorithms all within Apache Mahout's distributed machine-learning environment. …”
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  7. 7
    Mining Sequential Patterns Using I-PrefixSpan

    Mining Sequential Patterns Using I-PrefixSpan by Dhany , Saputra, Rambli Dayang, R.A., Foong, Oi Mean

    Published 2007
    “…Sequential pattern mining is a relatively new data-mining problem with many areas of application. …”
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  8. 8
    A web-based implementation of k-means algorithms

    A web-based implementation of k-means algorithms by Lee, Quan

    Published 2022
    “…This stinginess of proximity measures in data mining tools is stifling the performance of the algorithm. …”
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  9. 9
    Mining Sequential Patterns using I-PrefixSpan

    Mining Sequential Patterns using I-PrefixSpan by Saputra , Dhany, Dayang R.A. Rambli, Foong, Oi Mean

    Published 2008
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    Citation Index Journal
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  10. 10
    A study of the high-performance computing parallelism in solving complexity of meteorology data and calculations

    A study of the high-performance computing parallelism in solving complexity of meteorology data and calculations by Noor Affendi, Mohd Ridhuan, Hussin, Masnida, Hasan, Dana

    Published 2024
    “…Our investigation elaborates on, identifies, and analyzes the features and characteristics of parallel computing that are utilized in it. The paper also focuses on examining parallelization modeling, the algorithms involved, and optimization strategies employed in HPC-enabled meteorological simulations. …”
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  11. 11
    Model of Improved a Kernel Fast Learning Network Based on Intrusion Detection System

    Model of Improved a Kernel Fast Learning Network Based on Intrusion Detection System by Ali, Mohammed Hasan, Mohamed Fadli, Zolkipli

    Published 2019
    “…The incorporation of a single parallel hidden layer feed-forward neural network to the Fast Learning Network (FLN) architecture gave rise to the improved Extreme Learning Machine (ELM). …”
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  12. 12
    Hyper-heuristic approaches for data stream-based iIntrusion detection in the Internet of Things

    Hyper-heuristic approaches for data stream-based iIntrusion detection in the Internet of Things by Hadi, Ahmed Adnan

    Published 2022
    “…Most importantly, algorithms that suffer from a limited capability to adapt to the evolving nature of data generated from network traffic are called concept drift. …”
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  13. 13
    Features selection for intrusion detection system using hybridize PSO-SVM

    Features selection for intrusion detection system using hybridize PSO-SVM by Tabaan, Alaa Abdulrahman

    Published 2016
    “…The simulation will be carried on WEKA tool, which allows us to call some data mining methods under JAVA environment. The proposed model will be tested and evaluated on both NSL-KDD and KDD-CUP 99 using several performance metrics.…”
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  14. 14
    Adaptive genetic algorithm to improve negotiation process by agents e-commerce

    Adaptive genetic algorithm to improve negotiation process by agents e-commerce by Ebadi, Sahar

    Published 2011
    “…The proposed negotiation algorithm employs Bayesian learning and similarity functions in order to predict opponent agent’s type and preferences. …”
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  15. 15
    Acquisition of context-based word recognition by reinforcement learning using a recurrent neural network

    Acquisition of context-based word recognition by reinforcement learning using a recurrent neural network by Ahmad Afif, Mohd Faudzi

    Published 2012
    “…The developed learning system has a 4-layered RNN and it was trained by BPTT method based on teaching signal that was generated by Q-Learning algorithm. …”
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  16. 16
    Acquisition of context-based word recognition by reinforcement learning using a recurrent neural network

    Acquisition of context-based word recognition by reinforcement learning using a recurrent neural network by Ahmad Afif, Mohd Faudzi

    Published 2012
    “…The developed learning system has a 4-layered RNN and it was trained by BPTT method based on teaching signal that was generated by Q-Learning algorithm. …”
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  17. 17
    Simulation of Orthogonal Frequency Division Multiplexing (OFDM) signaling

    Simulation of Orthogonal Frequency Division Multiplexing (OFDM) signaling by Mastura, Ibrahim

    Published 2008
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    Learning Object
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  18. 18
    Auxiliary-based extension of multi-tasking sequence-to-sequence model for chatbot answers

    Auxiliary-based extension of multi-tasking sequence-to-sequence model for chatbot answers by Palasundram, Kulothunkan

    Published 2021
    “…“MTL-BC” executes response generation and binary question-response categorization in parallel. …”
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  19. 19
    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. The accuracy for rules and classification resulted from the TIP method are compared with other methods such as Standard Integer Programming (SIP) and Decision Related Integer Programming (DRIP) from Rough Set, Genetic Algorithm (GA), Johnson reducer, HoltelR method, Multiple Regression (MR), Neural Network (NN), Induction of Decision Tree Algorithm (ID3) and Base Learning Algorithm (C4.5); all other classifiers that are mostly used in the classification tasks. …”
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  20. 20
    A modified artificial neural network (ANN) algorithm to control shunt active power filter (SAPF) for current harmonics reduction

    A modified artificial neural network (ANN) algorithm to control shunt active power filter (SAPF) for current harmonics reduction by Sabo, Aliyu, Abdul Wahab, Noor Izzri, Mohd Radzi, Mohd Amran, Mailah, Nashiren Farzilah

    Published 2013
    “…The novelty control design is an artificial neural network (ANN) adopting a modified mathematical algorithm (a modified delta rule weight-updating W-H) and a suitable alpha value (learning rate value) which determines the filters optimal operation. …”
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