Search Results - (( variable different learning algorithm ) OR ( java application mining algorithm ))

Search alternatives:

Refine Results
  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
    Get full text
    Get full text
    Thesis
    Save to List
    Saved in:
  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
    Get full text
    Get full text
    Thesis
    Save to List
    Saved in:
  3. 3
    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. …”
    Get full text
    Get full text
    Get full text
    Article
    Save to List
    Saved in:
  4. 4
    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. …”
    Get full text
    Get full text
    Get full text
    Conference or Workshop Item
    Save to List
    Saved in:
  5. 5
    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. …”
    Get full text
    Get full text
    Final Year Project / Dissertation / Thesis
    Save to List
    Saved in:
  6. 6
    Mining Sequential Patterns using I-PrefixSpan

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

    Published 2008
    Get full text
    Get full text
    Citation Index Journal
    Save to List
    Saved in:
  7. 7
    Predicting dengue transmission rates by comparing different machine learning models with vector indices and meteorological data

    Predicting dengue transmission rates by comparing different machine learning models with vector indices and meteorological data by Ong, Song Quan, Pradeep Isawasan, Ahmad Mohiddin Mohd Ngesom, Hanipah Shahar, As’malia Md Lasim, Gomesh Nair

    Published 2023
    Get full text
    Get full text
    Get full text
    Get full text
    Article
    Save to List
    Saved in:
  8. 8
    Ensemble Dual Recursive Learning Algorithms for Identifying Custom Tanks Flow with Leakage

    Ensemble Dual Recursive Learning Algorithms for Identifying Custom Tanks Flow with Leakage by Akib, Afifi, Saad , Nordin, Asirvadam , Vijanth Sagayan

    Published 2010
    “…This paper proposed that, combination of two algorithms into one learning algorithm for predicting mass flow rate of a flow with leakage resulting in a better mass prediction error as compared to a model with single learning algorithm.…”
    Get full text
    Get full text
    Conference or Workshop Item
    Save to List
    Saved in:
  9. 9
    Ensemble dual recursive learning algorithms for identifying flow with leakage

    Ensemble dual recursive learning algorithms for identifying flow with leakage by Akib, Afifi, Saad , Nordin, Asirvadam , Vijanth Sagayan

    Published 2010
    “…This paper proposed that, combination of two algorithms into one learning algorithm for predicting mass flow rate of a flow with leakage resulting in a better mass prediction error compare to a model with single learning algorithm.…”
    Get full text
    Get full text
    Conference or Workshop Item
    Save to List
    Saved in:
  10. 10
    SLIDING WINDOW TRAINING ALGORITHMS USING MLP-NETWORK FOR CORRELATED AND LOST PACKET DATA

    SLIDING WINDOW TRAINING ALGORITHMS USING MLP-NETWORK FOR CORRELATED AND LOST PACKET DATA by AHMED IZZELDIN, HUZAIFA TAWFEIG

    Published 2012
    “…This thesis gives a systematic investigation of various MLP learning mainly Sliding Window (SW) learning mode which is treated as the adaptation of offline algorithms into online application Consequently this thesis reviews various offline algorithms including: batch backpropagation, nonlinear conjugate gradient, limited memory and full-memory Broyden, Fletcher, Goldfarb and Shanno algorithms and different forms of the latest proposed bimary ensemble learning. …”
    Get full text
    Get full text
    Thesis
    Save to List
    Saved in:
  11. 11
    Ensemble-based machine learning algorithms for classifying breast tissue based on electrical impedance spectroscopy

    Ensemble-based machine learning algorithms for classifying breast tissue based on electrical impedance spectroscopy by Rahman, Sam Matiur, Ali, Md. Asraf, Altwijri, Omar, Alqahtani, Mahdi, Ahmed, Nasim, Ahamed, Nizam Uddin

    Published 2020
    “…In addition, the ranked order of the variables based on their importance differed across the ML algorithms. …”
    Get full text
    Get full text
    Get full text
    Conference or Workshop Item
    Save to List
    Saved in:
  12. 12
    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.…”
    Get full text
    Get full text
    Thesis
    Save to List
    Saved in:
  13. 13
    Prediction of hydropower generation via machine learning algorithms at three Gorges Dam, China

    Prediction of hydropower generation via machine learning algorithms at three Gorges Dam, China by Sattar Hanoon M., Najah Ahmed A., Razzaq A., Oudah A.Y., Alkhayyat A., Feng Huang Y., kumar P., El-Shafie A.

    Published 2024
    “…In this study, different supervised and unsupervised machine learning algorithms are proposed: artificial neural network (ANN), AutoRegressive Integrated Moving Aveage (ARIMA) and support vector machine (SVM). …”
    Article
    Save to List
    Saved in:
  14. 14
    The impact of the combat method on radiomics feature compensation and analysis of scanners from different manufacturers

    The impact of the combat method on radiomics feature compensation and analysis of scanners from different manufacturers by Zhang, Xiaolei, Iqbal bin Saripan, M., Wu, Yanjun, Wang, Zhongxiao, Wen, Dong, Cao, Zhendong, Wang, Bingzhen, Xu, Shiqi, Liu, Yanli, Marhaban, Mohammad Hamiruce, Dong, Xianling

    Published 2024
    “…Conclusions: The Combat algorithm has reduced variability in radiomic features from different scanners. …”
    Get full text
    Get full text
    Get full text
    Article
    Save to List
    Saved in:
  15. 15
    Age-based facial recognition using convoluted neural network deep learning algorithm

    Age-based facial recognition using convoluted neural network deep learning algorithm by Julius Yong Wu Jien, Aslina Baharum, Shaliza Hayati A. Wahab, Nordin Saad, Muhammad Omar, Noorsidi Aizuddin Mat Noor

    Published 2020
    Get full text
    Get full text
    Get full text
    Get full text
    Article
    Save to List
    Saved in:
  16. 16
    Dynamic Bayesian networks and variable length genetic algorithm for designing cue-based model for dialogue act recognition

    Dynamic Bayesian networks and variable length genetic algorithm for designing cue-based model for dialogue act recognition by Yahya, Anwar Ali, Mahmod, Ramlan, Ramli, Abd Rahman

    Published 2010
    “…In the second stage, the developed variable length genetic algorithm is used to select different sets of lexical cues to constitute the dynamic Bayesian networks' random variables. …”
    Get full text
    Get full text
    Article
    Save to List
    Saved in:
  17. 17
    Machine learning classifications of multiple organ failures in a malaysian intensive care unit

    Machine learning classifications of multiple organ failures in a malaysian intensive care unit by Norliyana, Nor Hisham Shah, Normy Norfiza, Abdul Razak, Athirah, Abdul Razak, Asma’, Abu-Samah, Fatanah, M. Suhaimi, Ummu Kulthum, Jamaludin

    Published 2024
    “…This study demonstrates the performances of different machine learning algorithms in the classification of multiple organ failures. …”
    Get full text
    Get full text
    Get full text
    Article
    Save to List
    Saved in:
  18. 18
    Machine Learning Classifications of Multiple Organ Failures in a Malaysian Intensive Care Unit

    Machine Learning Classifications of Multiple Organ Failures in a Malaysian Intensive Care Unit by Shah N.N.H., Razak N.N.A., Razak A.A., Abu-Samah A., Suhaimi F.M., Jamaluddin U.

    Published 2025
    “…This study demonstrates the performances of different machine learning algorithms in the classification of multiple organ failures. …”
    Article
    Save to List
    Saved in:
  19. 19
    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
    “…The three different optimization algorithms used in this study are the genetic algorithm (GA), particle swarm optimization (PSO) algorithm and shark machine learning algorithm (SMLA). …”
    Get full text
    Get full text
    Article
    Save to List
    Saved in:
  20. 20
    Modeling and validation of base pressure for aerodynamic vehicles based on machine learning models

    Modeling and validation of base pressure for aerodynamic vehicles based on machine learning models by Quadros, Jaimon Dennis, Khan, Sher Afghan, Aabid, Abdul, Baig, Muneer

    Published 2023
    “…As a result, the advantages of these results are two-fold, providing: (i) a detailed examination of the efficiency of different neural network algorithms in dealing with a genuine aerodynamic problem, and (ii) helpful insights for regulating process variables to improve technological, operational, and financial factors, simultaneously.…”
    Get full text
    Get full text
    Get full text
    Get full text
    Get full text
    Article
    Save to List
    Saved in:

Search Tools: