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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
    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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  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. …”
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  6. 6
    Structural optimization of 4-DOF agricultural robot arm

    Structural optimization of 4-DOF agricultural robot arm by Nurul Emylia Natasya Ahmad Zakey, Mohd Hairi Mohd Zaman, Mohd Faisal Ibrahim

    Published 2024
    “…The best algorithm, i.e., the PSO algorithm, is evaluated by calculating mean square error (MSE of 0.00108527), root mean square error (RMSE of 0.01678), mean absolute error (MAE of 0.004286081), and end-effector position error (error of 0.080557045), where the best algorithm has the lowest value of error.…”
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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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  8. 8
    Feedback slew algorithms for prolate spinners using Single–Thruster

    Feedback slew algorithms for prolate spinners using Single–Thruster by Yang, Gao, Abadi, Chanik

    Published 2018
    “…This paper proposed two novel feedback slew algorithms, Feedback Half-Cone and Feedback Sector-Arc Slew, built on the existing open-loop algorithms and they use attitude and angular velocity feedback to compensate the errors in knowledge of spin rate, without external torques. …”
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  9. 9
    Application and evaluation of the evolutionary algorithms combined with conventional neural network to determine the building energy consumption of the residential sector

    Application and evaluation of the evolutionary algorithms combined with conventional neural network to determine the building energy consumption of the residential sector by Wang G., Mukhtar A., Moayedi H., Khalilpoor N., Tt Q.

    Published 2025
    “…Residential uses a significant amount of energy; hence, encouraging sustainability and lessening environmental effects requires minimizing energy consumption in this sector. …”
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  10. 10
    Development of an intelligent information system for financial analysis depend on supervised machine learning algorithms

    Development of an intelligent information system for financial analysis depend on supervised machine learning algorithms by Lei, X., Mohamad, U.H., Sarlan, A., Shutaywi, M., Daradkeh, Y.I., Mohammed, H.O.

    Published 2022
    “…When it comes to financial analysis, there are numerous risk-related concerns to contend with today (FI). In the financial sector, machine learning algorithms are used to detect fraud, automate trading, and provide financial advice to investors. …”
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  11. 11
    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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  12. 12
    A Mobile Application For Stock Price Prediction

    A Mobile Application For Stock Price Prediction by Choy, Yi Tou

    Published 2021
    “…These prediction algorithms were evaluated using 6 sectors of Bursa Malaysia stocks which are in total 216 stocks. …”
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  13. 13
    Kelantan daily water level prediction model using hybrid deep-learning algorithm for flood forecasting

    Kelantan daily water level prediction model using hybrid deep-learning algorithm for flood forecasting by Loh, Eng Chuen

    Published 2021
    “…Therefore, this present study had imputed the missing hydrological data using five imputation methods, namely Neural Network (NN), Moving Median (MM), Iterative Algorithm (IA), Nonlinear Iterative Partial Least Square (NIPALS), and Combined Correlation with Inversed Distance (CCID) imputation methods. …”
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  14. 14
    Improving earth surface temperature forecasting through the optimization of deep learning hyper-parameters using barnacles mating optimizer

    Improving earth surface temperature forecasting through the optimization of deep learning hyper-parameters using barnacles mating optimizer by Zuriani, Mustaffa, Mohd Herwan, Sulaiman, Muhammad 'Arif, Mohamad

    Published 2024
    “…Additionally, a comparison is made with the Autoregressive Moving Average (ARIMA) method. Evaluation using Mean Absolute Error (MAE), Root Mean Square Error (RMSE), and the coefficient of determination (R2) demonstrates the superior performance of DL optimized by BMO, showing minimal errors.…”
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  15. 15
    Estimation Of Weibull Parameters Using Simulated Annealing As Applied In Financial Data

    Estimation Of Weibull Parameters Using Simulated Annealing As Applied In Financial Data by Hamza, Abubakar

    Published 2023
    “…The performance of the SA algorithm has been explored in terms of accuracies and estimation errors. …”
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  16. 16
    Understanding the Causes of Design Errors in Construction Projects: A DEMATEL-Based Framework

    Understanding the Causes of Design Errors in Construction Projects: A DEMATEL-Based Framework by Lee, Chia Kuang, Chai, Changsaar, Bujna, Marián, Muhammad Ashraf, Fauzi, Boo, Ying Qi

    Published 2024
    “…The conclusions of this study can assist major players in the construction sector, as well as the government sector in establishing intervening strategies to mitigate errors and improve the quality of design.…”
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  17. 17
    A hybrid novel SVM model for predicting CO2 emissions using Multiobjective Seagull Optimization

    A hybrid novel SVM model for predicting CO2 emissions using Multiobjective Seagull Optimization by Ehteram M., Sammen S.S., Panahi F., Sidek L.M.

    Published 2023
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  18. 18
    Comparison between Secant method, Newton method and Bisection method in solving nonlinear equation / Nurul Ashsyikin Yasir

    Comparison between Secant method, Newton method and Bisection method in solving nonlinear equation / Nurul Ashsyikin Yasir by Yasir, Nurul Ashsyikin

    Published 2021
    “…The method that will be used in this research are Secant method, Bisection method and newton method. …”
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  19. 19
    Performance analyses of adaptive handover decision algorithm using spectrum aggregation in long term evolution - advanced network

    Performance analyses of adaptive handover decision algorithm using spectrum aggregation in long term evolution - advanced network by Usman, I. H., Nordin, N. K., Omizegba, E. E., Sali, A., Rasid, M. F. A., Hashim, F.

    Published 2021
    “…This implied that the network operating under the proposed TVWS algorithm presented low radio link decoding errors when compared with the validation algorithms MIF and CONV. …”
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  20. 20
    Forecasting export of selected timber products from Peninsular Malaysia using time series analysis

    Forecasting export of selected timber products from Peninsular Malaysia using time series analysis by Emang, Diana

    Published 2011
    “…The data were divided into two portions where the first 100 quarterly observations (calibration data set or within-sample data) were used in the modelling process. The remaining ten quarterly observations (validation data set or out-of-sample data)were used to assess the forecasting abilities based on the measures of accuracy including mean absolute error (MAE), root mean square error (RMSE) and mean absolute percentage error (MAPE). …”
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