Search Results - (( basic evaluation clustering algorithm ) OR ( using codification machine algorithm ))

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  1. 1
    New approaches to normalization techniques to enhance k-means clustering algorithm

    New approaches to normalization techniques to enhance k-means clustering algorithm by Dalatu, Paul Inuwa, Midi, Habshah

    Published 2020
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  2. 2
    Group consumers' preference recommendation algorithm model for online apparel's colour based on Kansei engineering

    Group consumers' preference recommendation algorithm model for online apparel's colour based on Kansei engineering by Ge, Baoru, Shaari, Nazlina, Mohd Yunos, Mohd Yazid, Zainal Abidin, Sazrinee

    Published 2023
    “…Thus, this study took the colour design of men's plain-colour shirts as an example in China, established the basic colour calculation scale and an algorithm model of group consumers' product preferences based on Kansei Engineering and scientific mathematics, to provide new sales ideas and methods for retailers and markets online. …”
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  3. 3
    Cluster-based spectrum sensing scheme in heterogeneous network

    Cluster-based spectrum sensing scheme in heterogeneous network by Hasan, Mohammad Kamrul, Ismail, Ahmad Fadzil, Hassan Abdalla Hashim, Aisha, Mohd. Ramli, Huda Adibah, Hashim, Wahidah, Islam, Shayla, Badron, Khairayu

    Published 2014
    “…To detect spectrums from nearby macrocell (macro-eNodeB) HeNodeBs are grouped in to cluster. A cluster formation algorithm is also proposed in where, cluster head (CH) and signaling node (SN) will detect implies the multi-channel SS technique. …”
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    Proceeding Paper
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  4. 4
    Cluster-based spectrum sensing scheme in heterogeneous network

    Cluster-based spectrum sensing scheme in heterogeneous network by Hasan, Mohammad Kamrul, Ismail, Ahmad Fadzil, Mohd. Ramli, Huda Adibah, Hassan Abdalla Hashim, Aisha, Islam, Shayla, Hashim, Wahidah, Badron, Khairayu

    Published 2015
    “…To detect spectrums from nearby macrocell (macro-eNodeB) HeNodeBs are grouped in to cluster. A cluster formation algorithm is also proposed in where, cluster head (CH) and signaling node (SN) will detect implies the multi-channel SS technique. …”
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  5. 5
    Communication and computational cost on parallel algorithm of PDE elliptic type

    Communication and computational cost on parallel algorithm of PDE elliptic type by Alias, Norma

    Published 2009
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  6. 6
    Instance matching framework for heterogeneous semantic web content over linked data environment

    Instance matching framework for heterogeneous semantic web content over linked data environment by Mansir, Abubakar

    Published 2021
    “…The output of each algorithm is evaluated, the results have shown that each algorithm performs well and outperforms the existing algorithms on all test cases in terms better output generation and effective handling of heterogeneity from different domains, which is a necessary concern in all data-intensive problems. …”
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  7. 7
    Cluster-based spectrum sensing scheme in heterogeneous network

    Cluster-based spectrum sensing scheme in heterogeneous network by Hasan M.K., Ismail A.F., Abdalla A.-H., Ramli H.A.M., Islam S., Hashim W., Badron K.

    Published 2023
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  8. 8
    Application of clustering in managing unstructured textual data in relational database / Wael Mohamed Shaher Yafooz

    Application of clustering in managing unstructured textual data in relational database / Wael Mohamed Shaher Yafooz by Yafooz, Wael Mohamed Shaher

    Published 2014
    “…Three experiments have been conducted on textual Reuters corpus, Classic and WAP dataset. The clustering results have been validated using the F-measure, Entropy and Purity methods of measurement and compared with two common methods, which are information extraction and textual document clustering, for example, K-means, Frequent Item-Set, Hierarchical Clustering Algorithms and Oracle Text. …”
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  9. 9
    Extracting crown morphology with a low-cost mobile LiDAR scanning system in the natural environment

    Extracting crown morphology with a low-cost mobile LiDAR scanning system in the natural environment by Wang, Kai, Zhou, Jun, Zhang, Wenhai, Zhang, Baohua

    Published 2021
    “…The algorithm defined in this study was evaluated with manual measurements as reference, and the morphological parameters of the canopy obtained using the LOAM and LeGO-LOAM algorithms as the basic framework were compared. …”
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  10. 10
    Even-odd scheduling based energy efficient routing for wireless sensor network (WSN) / Muhammad Zafar Iqbal Khan

    Even-odd scheduling based energy efficient routing for wireless sensor network (WSN) / Muhammad Zafar Iqbal Khan by Khan, Muhammad Zafar Iqbal

    Published 2022
    “…The performance of the proposed routing algorithm has been evaluated through simulations of well-known software MATLAB. …”
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  11. 11
    Defect Detection And Classification Of Silicon Solar Wafer Featuring Nir Imaging And Improved Niblack Segmentation

    Defect Detection And Classification Of Silicon Solar Wafer Featuring Nir Imaging And Improved Niblack Segmentation by Mahdavipour, Zeinab

    Published 2016
    “…Meanwhile, a set of descriptors corresponding to Elliptic Fourier Features shape description is extracted for each defect and is evaluated for each cluster to use for clustering and classification part. …”
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  12. 12
    Hybrid-discrete multi-objective particle swarm optimization for multi-objective job-shop scheduling

    Hybrid-discrete multi-objective particle swarm optimization for multi-objective job-shop scheduling by Anuar, Nurul Izah

    Published 2022
    “…This research first proposes an improved continuous MOPSO to address the rapid clustering problem that exists in the basic PSO algorithm using three improvement strategies: re-initialization of particles, systematic switch of best solutions and mutation on global best selection. …”
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  13. 13
    Bottleneck-based heuristic for permutation flowshop scheduling

    Bottleneck-based heuristic for permutation flowshop scheduling by Isa, Noor Amira

    Published 2017
    “…There are four potential dominant machines (M1, M2, M3, M4) clustered as bottleneck machines. A total 1000 set random processing time for each job sizes was tested using Excel simple programming with built in Visual Basic for Application (VBA). …”
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