Search Results - (( data evaluation method algorithm ) OR ( data validation study algorithm ))

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  1. 1
    Evaluation of Lightning Current Using Inverse Procedure Algorithm.

    Evaluation of Lightning Current Using Inverse Procedure Algorithm. by Ab Kadir, Mohd Zainal Abidin, Izadi, Mahdi, Askari, Mohamad Tolou, Hajikhani, Maryam

    Published 2013
    “…In order to validate the proposed method, a set of measured electromagnetic fields are applied on proposed algorithm and the evaluated currents are compared to the corresponding measured current as well as the results are discussed accordingly. …”
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  2. 2
    Integrated combined layer algorithm of jamming detection and classification in manet / Ahmad Yusri Dak

    Integrated combined layer algorithm of jamming detection and classification in manet / Ahmad Yusri Dak by Dak, Ahmad Yusri

    Published 2019
    “…Finally, both algorithms are validated against the findings in various literatures. …”
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  3. 3
    On density-based data streams clustering algorithms: A survey

    On density-based data streams clustering algorithms: A survey by Teh, Y.W.

    Published 2017
    “…It is hoped that this survey will serve as a steppingstone for researchers studying data streams clustering, particularly density-based algorithms.…”
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  4. 4
    Efficient genetic partitioning-around-medoid algorithm for clustering

    Efficient genetic partitioning-around-medoid algorithm for clustering by Garib, Sarmad Makki Mohammed

    Published 2019
    “…Lastly, in order to externally judge the validity of these types of clustering algorithms, there is a need for a method to correctly and efficiently evaluate their variant multiclass clustering results. …”
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  5. 5
    Evaluations of oil palm fresh fruit bunches maturity degree using multiband spectrometer

    Evaluations of oil palm fresh fruit bunches maturity degree using multiband spectrometer by Tuerxun, Adilijiang

    Published 2017
    “…Furthermore, the Lazy-IBK algorithm have been validated to produce the best classifier model, with the machine learning algorithm performance of 65.26%, recall of 65.3%, and 65.4% F-measured as compared to other evaluated machine learning classifier algorithms proposed within the WEKA data mining algorithm. …”
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  6. 6
    Using algorithmic taxonomy to evaluate lecturer workload

    Using algorithmic taxonomy to evaluate lecturer workload by Hashim, Ruhil Hayati, Abdul Hamid, Jamaliah, Selamat, Mohd Hasan, Ibrahim, Hamidah, Abdullah, Rusli, Mohayidin, Mohd Ghazali

    Published 2006
    “…Results of the study highlight the contributions of this algorithmic method in better evaluation of teaching workload for lecture.…”
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  7. 7
    Classification of credit card holder behavior using K Nearest Neighbor algorithm / Ahmad Faris Rahimi

    Classification of credit card holder behavior using K Nearest Neighbor algorithm / Ahmad Faris Rahimi by Rahimi, Ahmad Faris

    Published 2017
    “…The highest accuracy is 78.33% ofthe 10-fold Cross Validation method are found in data is 80% training and 20% testing when k is equal to 5. …”
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  8. 8
    Algorithm Development of Bidirectional Agglomerative Hierarchical Clustering Using AVL Tree with Visualization

    Algorithm Development of Bidirectional Agglomerative Hierarchical Clustering Using AVL Tree with Visualization by Hussain Mohammad Yousef Abu Dalbouh

    Published 2024
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  9. 9
    Using algorithmic taxonomy to evaluate lecture workload: a case study of services application prototype in the UPM KM Portal

    Using algorithmic taxonomy to evaluate lecture workload: a case study of services application prototype in the UPM KM Portal by Abdul Hamid, Jamaliah, Mohayidin, Mohd Ghazali, Selamat, Mohd Hasan, Ibrahim, Hamidah, Abdullah, Rusli, Hashim, Ruhil Hayati

    Published 2006
    “…Results of the study highlight the contributions of this algorithmic method in better evaluation of teaching workload for lecture.…”
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  10. 10
    The Parallel Fuzzy C-Median Clustering Algorithm Using Spark for the Big Data

    The Parallel Fuzzy C-Median Clustering Algorithm Using Spark for the Big Data by Mallik, Moksud Alam, Zulkurnain, Nurul Fariza, Siddiqui, Sumrana, Sarkar, Rashel

    Published 2024
    “…The analysis, processing, and storing of big data is a challenging research concern due to data imperfection, massive data size, computational difficulty, and lengthy evaluation time. …”
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  11. 11
    Discovering decision algorithm from a distance relay event report

    Discovering decision algorithm from a distance relay event report by Othman, Mohammad Lutfi, Aris, Ishak, Abdullah, Senan Mahmood, Ali, Md. Liakot, Othman, Mohammad Ridzal

    Published 2009
    “…In this study rough-set-based data mining strategy was formulated to discover distance relay decision algorithm from its resident event report. …”
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  12. 12
    Pashto language stemming algorithm

    Pashto language stemming algorithm by Aslamzai, Sebghatullah, Saidah Saad

    Published 2015
    “…Furthermore, the accuracy and strength of the proposed algorithm is evaluated using word count method. To validate the function of the developed algorithm, two native speakers of Pashto were recruited to evaluate the algorithm in terms of its accuracy and strength. …”
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  13. 13
    Using algorithmic taxonomy to evaluate lecture workload: A case study of services application prototype in the UPM KM portal

    Using algorithmic taxonomy to evaluate lecture workload: A case study of services application prototype in the UPM KM portal by Abdul Hamid, Jamaliah, Mohayidin, Mohd Ghazali, Selamat, Mohd Hassan, Ibrahim, Hamidah, Abdullah, Rusli, Hashim, Ruhil Hayati

    Published 2006
    “…Lecturer workload at universities includes three major categories: teaching, research and services.Teaching workload is influence by various factors such as level taught courses, number of student, credit and contact hour and off campus or on campus course design.The UPM has a KM Portal that contains sets of metadata on lecturer profile and knowledge assets.The Lecturer profile contains information lecturer teaching, research, publication and many more.We constructed an algorithmic taxonomy based at the lecturer profile data to measure lecturer teaching workload.This method measures the lecturer teaching workload.The taxonomy is a dynamic hierarchy that extracts validated parameters from the dataset.Results of the study highlight the contributions of this algorithmic method in better evaluation of teaching workload for lecture.…”
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  14. 14
    Improved criteria determination of an automated negative lightning return strokes characterisation using Brute-Force search algorithm

    Improved criteria determination of an automated negative lightning return strokes characterisation using Brute-Force search algorithm by Abdul Haris, Faranadia

    Published 2021
    “…A total of 206 negative lightning return strokes waveforms were analysed and automatically characterised using the proposed algorithm. Comparisons of different data, including the manual data (i.e. obtained through the conventional method), data (automated) from a previous study, and the automated data (i.e. obtained using the proposed algorithm), were also carried out by evaluating the percentage difference, arithmetic mean, and standard deviation. …”
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  15. 15
    Energy Management in Integrated Microgrids: An Optimal Schedule Controller Utilizing Gradient Descent Algorithm

    Energy Management in Integrated Microgrids: An Optimal Schedule Controller Utilizing Gradient Descent Algorithm by Abdolrasol M.G.M., Ker P.J., Hannan M.A., Ayob A., Tiong S.K.

    Published 2024
    “…The developed BGD algorithm's effectiveness is further validated through a comparative analysis with conventional methods…”
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  16. 16
    Extended multiple models selection algorithms based on iterative feasible generalized least squares (IFGLS) and expectation-maximization (EM) algorithm

    Extended multiple models selection algorithms based on iterative feasible generalized least squares (IFGLS) and expectation-maximization (EM) algorithm by Nur Azulia, Kamarudin

    Published 2019
    “…Simulation and empirical studies are conducted in validating the performance of the two algorithms. …”
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  17. 17
    Characterization of PV panel and global optimization of its model parameters using genetic algorithm

    Characterization of PV panel and global optimization of its model parameters using genetic algorithm by Ismail M.S., Moghavvemi M., Mahlia T.M.I.

    Published 2023
    “…The results of the simulation are compared with the Data Sheet information, which is obtained via experimentation in order to validate the reliability of the approach. …”
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  18. 18
    Enhanced dimensionality reduction methods for classifying malaria vector dataset using decision tree

    Enhanced dimensionality reduction methods for classifying malaria vector dataset using decision tree by Arowolo, Micheal Olaolu, Adebiyi, Marion Olubunmi, Adebiyi, Ayodele Ariyo

    Published 2021
    “…In this study, a novel optimized dimensionality reduction algorithm is proposed, by combining an optimized genetic algorithm with Principal Component Analysis and Independent Component Analysis (GA-O-PCA and GAO-ICA), which are used to identify an optimum subset and latent correlated features, respectively. …”
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  19. 19
    Confidence intervals (CI) for concentration parameter in von Mises distribution and analysis of missing values for circular data / Siti Fatimah binti Hassan

    Confidence intervals (CI) for concentration parameter in von Mises distribution and analysis of missing values for circular data / Siti Fatimah binti Hassan by Hassan, Siti Fatimah

    Published 2015
    “…In this study, three imputation methods are considered namely expectation-maximization (EM) algorithm and data augmentation (DA) algorithm. …”
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  20. 20
    A Novel Wrapper-Based Optimization Algorithm for the Feature Selection and Classification

    A Novel Wrapper-Based Optimization Algorithm for the Feature Selection and Classification by Talpur, N., Abdulkadir, S.J., Hasan, M.H., Alhussian, H., Alwadain, A.

    Published 2023
    “…To address this issue, various data pre-processing methods called Feature Selection (FS) techniques have been presented in the literature. …”
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