Search Results - (( variable equations 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
    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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  4. 4
    Weather prediction in Kota Kinabalu using linear regressions with multiple variables

    Weather prediction in Kota Kinabalu using linear regressions with multiple variables by Teong, Khan Vun, Chung, Gwo Chin, Jedol Dayou

    Published 2021
    “…Numerical weather prediction is the process of using existing numerical data on weather conditions to forecast the weather using machine learning algorithms. This study employs machine learning algorithms, a linear regression model using statistics, and two optimization approaches, the normal equation approach, and gradient descent approach to predict the weather based on a few variables. …”
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  5. 5
    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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  6. 6
    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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  7. 7
    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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  8. 8
    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
    “…The data for training and testing the algorithms was derived using the regression equation developed using the Box-Behnken Design (BBD). …”
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  9. 9
    Classification of students' performance in computer programming course according to learning style

    Classification of students' performance in computer programming course according to learning style by Norwawi N.M., Abdusalam S.F., Hibadullah C.F., Shuaibu B.M.

    Published 2024
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  10. 10
    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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  11. 11
    Long-term electrical energy consumption: Formulating and forecasting via optimized gene expression programming / Seyed Hamidreza Aghay Kaboli

    Long-term electrical energy consumption: Formulating and forecasting via optimized gene expression programming / Seyed Hamidreza Aghay Kaboli by 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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  12. 12
    Tangible interaction learning model to enhance learning activity processes among children with dyslexia

    Tangible interaction learning model to enhance learning activity processes among children with dyslexia by Jamalai@Jamali, Siti Nurliana

    Published 2024
    “…To find optimum variables, Machine Learning approach needs to be utilized. …”
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  13. 13
    Intelligent imputation method for mix data-type missing values to improve data quality

    Intelligent imputation method for mix data-type missing values to improve data quality by Alabadla, Mustafa R. A.

    Published 2024
    “…To find optimum variables, Machine Learning approach needs to be utilized. …”
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  14. 14
    Strategic capabilities, innovation strategy and the performance of food and beverage small and medium enterprises

    Strategic capabilities, innovation strategy and the performance of food and beverage small and medium enterprises by Salisu, Yakubu

    Published 2019
    “…Consequently, the significant positive impacts of top management, technological, learning and relational capabilities postulate that these variables are valuable in influencing performance directly and indirectly through innovation strategy. …”
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  15. 15
    Operational matrix based on orthogonal polynomials and artificial neural networks methods for solving fractal-fractional differential equations

    Operational matrix based on orthogonal polynomials and artificial neural networks methods for solving fractal-fractional differential equations by Shloof, Aml Melad Asan

    Published 2024
    “…Finally, ANNs employing a combination of power series methods in the GCFFD are developed to approximate solutions of higher-order linear FFDEs with both constant and variable coefficients. Initially, the algorithm utilized a truncated series. …”
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  16. 16
    Prediction on the mechanical strength of coal ash concrete using artificial neural network

    Prediction on the mechanical strength of coal ash concrete using artificial neural network by Muhammad Nor Syahrul, Zaimi, Nur Farhayu, Ariffin, Sharifah Maszura, Syed Mohsin, Abdul Muiz, Hasim, Nurul Natasha, Nasrudin

    Published 2022
    “…This type of analysis involves one or more independent variables that may most accurately predict the value of the dependent variable and calculates the coefficients of the linear equation. …”
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  17. 17
    Enhancing reservoir simulation models with genetic algorithm optimized neural networks across diverse climatic zones / Saad Mawlood Saab

    Enhancing reservoir simulation models with genetic algorithm optimized neural networks across diverse climatic zones / Saad Mawlood Saab by Saad Mawlood , Saab

    Published 2025
    “…The research improved the predictive models by integrating them with the Genetic Algorithm (GA). The optimizer algorithm (i.e., GA) determines the optimal input variables and internal parameters in the prediction models. …”
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  18. 18
    DEVELOPMENT AND TESTING OF UNIVERSAL PRESSURE DROP MODELS IN PIPELINES USING ABDUCTIVE AND ARTIFICIAL NEURAL NETWORKS

    DEVELOPMENT AND TESTING OF UNIVERSAL PRESSURE DROP MODELS IN PIPELINES USING ABDUCTIVE AND ARTIFICIAL NEURAL NETWORKS by AYOUB MOHAMMED, MOHAMMED ABDALLA

    Published 2011
    “…The ANN model has been developed using resilient back-propagation learning algorithm. The purpose for generating another model using the polynomial Group Method of Data Handling technique was to reduce the problem of dimensionality that affects the accuracy of ANN modeling. …”
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  19. 19
    Production and characterization of biochar derived from oil palm wastes, and optimization for zinc adsorption

    Production and characterization of biochar derived from oil palm wastes, and optimization for zinc adsorption by Zamani, Seyed Ali

    Published 2015
    “…The incremental back propagation algorithm demonstrated the best results and which has been used as learning algorithm for ANN in combination with Genetic Algorithm in the optimization. …”
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