Search Results - (( (variable OR variables) extractions _ algorithm ) OR ( java application based algorithm ))

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  1. 1
    Classification for large number of variables with two imbalanced groups

    Classification for large number of variables with two imbalanced groups by Ahmad Hakiim, Jamaluddin

    Published 2020
    “…This study proposed two algorithms of classification namely Algorithm 1 and Algorithm 2 which combine resampling, variable extraction, and classification procedure. …”
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  2. 2
    RSA Encryption & Decryption using JAVA

    RSA Encryption & Decryption using JAVA by Ramli, Marliyana

    Published 2006
    “…The implementation of this project will be based on Rapid Application Design Methodology (RAD) and will be more focusing on research and finding, ideas and the implementation of the algorithm, and finally running and testing the algorithm. …”
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  3. 3
    Using a fatigue data editing approach for analysing cycle sequence effects in variable amplitude road loadings

    Using a fatigue data editing approach for analysing cycle sequence effects in variable amplitude road loadings by S., Abdullah, J. C., Choi

    Published 2011
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  4. 4
    Strategies of Handling Different Variables Reduction for LDA

    Strategies of Handling Different Variables Reduction for LDA by Hamid, Hashibah, Mahat, Nor Idayu

    Published 2012
    “…The variables selection technique with local searching algorithm is manipulated. …”
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  5. 5
    Development Of Fall Risk Clustering Algorithm In Older People

    Development Of Fall Risk Clustering Algorithm In Older People by Wong, Kam Kang

    Published 2020
    “…A total of 1279 subjects and 9 variables from dataset (1411 subjects and 139 variables) are selected for clustering. t-Distributed Stochastic Neighbour Embedding (t-SNE) for feature extraction and K-means clustering algorithm achieved the highest performance in clustering, which grouping the subjects into Low (13%), Intermediate A (19%), Intermediate B (21%) and High (31%) fall risk group. …”
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  6. 6
    Optimized clustering with modified K-means algorithm

    Optimized clustering with modified K-means algorithm by Alibuhtto, Mohamed Cassim

    Published 2021
    “…In dealing with correlated variables, PCA was embedded in the proposed algorithm. …”
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  7. 7
    Optimal timber transportation planning in tropical hill forest using bees algorithm

    Optimal timber transportation planning in tropical hill forest using bees algorithm by Jamaluddin, Jamhuri

    Published 2022
    “…This study proposed a multi-objective linear programming model with Bees algorithm (BA) to find an optimal cost TTP for extraction, forest road, and landing locations. …”
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  8. 8
    One-Dimensional Convolutional Neural Network with Variable Weights Grey Wolf Optimizer for Modeling of Sand Retention Test

    One-Dimensional Convolutional Neural Network with Variable Weights Grey Wolf Optimizer for Modeling of Sand Retention Test by Abd Razak, Nurul Nadhirah

    Published 2022
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  9. 9
    Coronary artery stenosis detection and visualization / Tang Sze Ling

    Coronary artery stenosis detection and visualization / Tang Sze Ling by Tang, Sze Ling

    Published 2015
    “…The performance evaluation results show that the stenosis detection algorithm performs better average sensitivity than several state-of-the-art algorithms.…”
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  10. 10
    Optimizing timber transportation planning for timber harvesting using bees algorithm in Malaysia

    Optimizing timber transportation planning for timber harvesting using bees algorithm in Malaysia by Jamaluddin, Jamhuri, Kamarudin, Norizah, Ismail, Mohd Hasmadi, Ahmad, Siti Azfanizam

    Published 2023
    “…A Bees Algorithm (BA) was proposed to find an optimum TTP for timber extraction, forest road, and landing locations with grid cell-sized 10 m × 10 m and attributed with fixed and variable costs. …”
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  11. 11
    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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  12. 12
    Development of an effective clustering algorithm for older fallers

    Development of an effective clustering algorithm for older fallers by Goh, Choon Hian, Wong, Kam Kang, Tan, Maw Pin *, Ng, Siew Cheok, Chuah, Yea Dat, Kwan, Ban Hoe

    Published 2022
    “…Using feature extraction with the t-SNE and the K-means clustering algorithm, subjects were clustered into low, intermediate A, intermediate B and high fall risk groups which corresponded with fall occurrence of 13%, 19%, 21% and 31% respectively. …”
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  13. 13
    Prediction of electronic cigarette and vape use among Malaysian: decision tree analysis

    Prediction of electronic cigarette and vape use among Malaysian: decision tree analysis by Kartiwi, Mira, Ab Rahman, Jamalludin, Nik Mohamed, Mohamad Haniki, Draman, Samsul, Ab Rahman, Norny Syafinaz

    Published 2017
    “…Results: By using the ID3 algorithm, it is possible to consider the relationship among variables and to identify the most informative variables for predicting the classification of the instance. …”
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  14. 14
    Adaptive Step Size Based Hill-Climb Search Algorithm for MPPT Control of DFIG-WECS With Reduced Power Fluctuation and Improved Tracking Performance

    Adaptive Step Size Based Hill-Climb Search Algorithm for MPPT Control of DFIG-WECS With Reduced Power Fluctuation and Improved Tracking Performance by Uddin M.N., Amin I.K.

    Published 2023
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  15. 15
    Application of genetic algorithm and JFugue in an evolutionary music generator

    Application of genetic algorithm and JFugue in an evolutionary music generator by Tang, Jia Rou

    Published 2025
    “…This project explores the application of Genetic Algorithms (GA) with JFugue, which is a Java-based music programming library to develop an Evolutionary Music Generator. …”
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  16. 16
    Java based expert system for selection of natural fibre composite materials

    Java based expert system for selection of natural fibre composite materials by Ahmed Ali, Basheer A., Salit, Mohd Sapuan, Zainudin, Edi Syams, Othman, Mohamed

    Published 2013
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  17. 17
    Characteristics of electronic cigarette and vape users in Malaysia: Lessons from decision tree analysis

    Characteristics of electronic cigarette and vape users in Malaysia: Lessons from decision tree analysis by Kartiwi, Mira, Nik Mohamed, Mohamad Haniki, Ab Rahman, Jamalludin, Draman, Samsul, Ab Rahman, Norny Syafinaz

    Published 2020
    “…Several predictor variables included in this study were: seven demographics variables (i.e., age, gender, race, residence, marital, occupation and education) and twenty variables on the perception of ECV use. …”
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  18. 18
    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. …”
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  19. 19
    Automatic Number Plate Recognition on android platform: With some Java code excerpts

    Automatic Number Plate Recognition on android platform: With some Java code excerpts by ., Abdul Mutholib, Gunawan, Teddy Surya, Kartiwi, Mira

    Published 2016
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  20. 20
    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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