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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
    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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  7. 7
    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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  8. 8
    Novel direct and self-regulating approaches to determine optimum growing multi-experts network structure

    Novel direct and self-regulating approaches to determine optimum growing multi-experts network structure by Loo, C.K., Rajeswari, M., Rao, M.V.C.

    Published 2004
    “…However, GMN is not ergonomic due to too many network control parameters. Therefore, a self-regulating GMN (SGMN) algorithm is proposed. SGMN adopts self-adaptive learning rates for gradient-descent learning rules. …”
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  9. 9
    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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  10. 10
    Edge assisted crime prediction and evaluation framework for machine learning algorithms

    Edge assisted crime prediction and evaluation framework for machine learning algorithms by Adhikary, Apurba, Murad, Saydul Akbar, Munir, Md Shirajum, Choong Seon, Hong Seong

    Published 2022
    “…To anticipate occurrences, ML methods such as Decision Trees, Neural Networks, K-Nearest Neighbors, and Impact Learning are being utilized, and their performance is compared based on the data processing and modification used. …”
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  11. 11
    A deep reinforcement learning hybrid algorithm for the computational discovery and characterization of small proteins utilizing mycobacterium tuberculosis as a model

    A deep reinforcement learning hybrid algorithm for the computational discovery and characterization of small proteins utilizing mycobacterium tuberculosis as a model by Ouwabunmi, Babalola AbdulHafeez

    Published 2025
    “…The accurate prediction and characterization of small open reading frames (smORFs) are critical for understanding their functional roles in gene regulation and cellular processes. This study presents the development and evaluation of a novel hybrid machine learning algorithm that integrates the strengths of Random Forest and Gradient Boosting models to enhance the prediction of smORFs. …”
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  12. 12
    Nonlinear dynamic system identification and control via self-regulating modular neural network

    Nonlinear dynamic system identification and control via self-regulating modular neural network by Kiong, L.C., Rajeswari, M., Rao, M.V.C.

    Published 2003
    “…In addition, the Fully Self-Organized Simplified Adaptive Resonance Theory (FOSART) is modified and adopted to generate an induced Delaunay triangulation that is highly desired for optimal function approximation. Self-adaptive learning rates Gradient Descent learning rules are employed in a supervised learning phase. …”
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  13. 13
    Artificial Intelligence (AI) in the art and design industry / Fahmi Samsudin

    Artificial Intelligence (AI) in the art and design industry / Fahmi Samsudin by Samsudin, Fahmi

    Published 2023
    “…It encompasses different types, such as rule-based AI using if-then statements for decision-making, machine learning which employs algorithms to analyze and learn from data, and deep learning utilizing artificial neural networks to learn from extensive datasets. …”
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  14. 14
    Water level forecasting using feed forward neural networks optimized by African Buffalo Algorithm (ABO)

    Water level forecasting using feed forward neural networks optimized by African Buffalo Algorithm (ABO) by Ahmed, Ehab Ali

    Published 2019
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  15. 15
    DNA enhancer prediction using machine learning techniques with novel feature representation

    DNA enhancer prediction using machine learning techniques with novel feature representation by Fong, Pui Kwan

    Published 2016
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  16. 16
    A hybrid residue based sequential encoding mechanism with XGBoost improved ensemble model for identifying 5-hydroxymethylcytosine modifications

    A hybrid residue based sequential encoding mechanism with XGBoost improved ensemble model for identifying 5-hydroxymethylcytosine modifications by Uddin I., Awan H.H., Khalid M., Khan S., Akbar S., Sarker M.R., Abdolrasol M.G.M., Alghamdi T.A.H.

    Published 2025
    “…Among the applied machine learning algorithms, the XGBoost ensemble model using the tenfold cross-validation test achieved improved results than existing state-of-the-art models. …”
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  17. 17
    ANN-Based Binary Backtracking Search Algorithm for VPP Optimal Scheduling and Cost-Effective Evaluation

    ANN-Based Binary Backtracking Search Algorithm for VPP Optimal Scheduling and Cost-Effective Evaluation by Hannan M.A., Abdolrasol M.G., Mohamed R., Al-Shetwi A., Ker P., Begum R., Muttaqi K.

    Published 2023
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  18. 18
    Performance comparison of feedforward neural network training algorithms in modeling for synthesis of polycaprolactone via biopolymerization

    Performance comparison of feedforward neural network training algorithms in modeling for synthesis of polycaprolactone via biopolymerization by Wong, Yong Jie, Arumugasamy, Senthil Kumar, Jewaratnam, Jegalakshimi

    Published 2018
    “…This paper compares mean absolute error, mean square error, and mean absolute percentage error (MAPE) in the PCL biopolymerization process for 11 different training algorithms that belong to six classes, namely (1) additive momentum, (2) self-adaptive learning rate, (3) resilient backpropagation, (4) conjugate gradient backpropagation, (5) quasi-Newton, and (6) Bayesian regulation propagation. …”
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  19. 19
    Internet of Things (IoT) intrusion detection by Machine Learning (ML): a review

    Internet of Things (IoT) intrusion detection by Machine Learning (ML): a review by Dehkordi, Iman Farhadian, Manochehri, Kooroush, Aghazarian, Vahe

    Published 2023
    “…For example, it could be used to keep an eye on and regulate industrial services, or it could be used to improve corporate operations. …”
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  20. 20
    Base pressure control through micro jets at supersonic Mach numbers using experimental and machine learning approach

    Base pressure control through micro jets at supersonic Mach numbers using experimental and machine learning approach by Aabid, Abdul, Khan, Sher Afghan, Yasir, Javed

    Published 2026
    “…This study presents active control methods using microjets to regulate base pressure, employing experimental and machine learning approaches. …”
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