Search Results - (( evolution identification method algorithm ) OR ( data classification using algorithm ))

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  1. 1
    Voltage stability margin identification using evolution programming learning algorithm / Zamzuhairi Darus

    Voltage stability margin identification using evolution programming learning algorithm / Zamzuhairi Darus by Darus, Zamzuhairi

    Published 2003
    “…This project proposed on an investigation on the voltage stability margin identification using evolution programming learning algorithm. …”
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  2. 2
    Hybrid DE and PEM algorithm for identification of small scale Autonomous helicopter model

    Hybrid DE and PEM algorithm for identification of small scale Autonomous helicopter model by Legowo, Ari

    Published 2012
    “…The proposed hybrid identification method explored the evolutionary search optimization strength of DE for parameter initialization for PEM identification algorithm…”
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  3. 3
    Mixed Unscented Kalman Filter and differential evolution for parameter identification

    Mixed Unscented Kalman Filter and differential evolution for parameter identification by Legowo, Ari, Mohamad, Zahratu H., Park, HoonCheol

    Published 2013
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  4. 4
    Autotuning PID Controllers for Quadplane Hybrid UAV using Differential Evolution Algorithm

    Autotuning PID Controllers for Quadplane Hybrid UAV using Differential Evolution Algorithm by Pairan, Mohammad Fahmi, Shamsudin, Syariful Syafiq

    Published 2024
    “…The paper presents a method for autotuning attitude PID for a quadplane UAV using differential evolution (DE), X-Plane simulation, and neural network (NN)-based system identification. …”
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  5. 5
    Autotuning PID Controllers for Quadplane Hybrid UAV using Differential Evolution Algorithm

    Autotuning PID Controllers for Quadplane Hybrid UAV using Differential Evolution Algorithm by Pairan, Mohammad Fahmi, Shamsudin, Syariful Syafiq, Yaakub, Mohd Fauzi

    Published 2024
    “…The paper presents a method for autotuning attitude PID for a quadplane UAV using differential evolution (DE), X-Plane simulation, and neural network (NN)-based system identification. …”
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  6. 6
    Improving Classification of Remotely Sensed Data Using Best Band Selection Index and Cluster Labelling Algorithms

    Improving Classification of Remotely Sensed Data Using Best Band Selection Index and Cluster Labelling Algorithms by Teoh, Chin Chuang

    Published 2005
    “…In cluster generating process, the developed BBSI algorithm was used to select the best band combination for generating cluster by using Iterative self- Organizing Data Analysis (ISODATA) technique. …”
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  7. 7
    Case Slicing Technique for Feature Selection

    Case Slicing Technique for Feature Selection by A. Shiba, Omar A.

    Published 2004
    “…Since the 1960s, many algorithms for data classification have been proposed. …”
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  8. 8
    Dengue classification system using clonal selection algorithm / Karimah Mohd

    Dengue classification system using clonal selection algorithm / Karimah Mohd by Mohd, Karimah

    Published 2012
    “…Some of the dengue data are used to test the dengue classification system to produce the classification accuracy. …”
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  9. 9
    Enhancing Classification Algorithms with Metaheuristic Technique

    Enhancing Classification Algorithms with Metaheuristic Technique by Cokro, Nurwinto, Tri Basuki, Kurniawan, Misinem, ., Tata, Sutabri, Yesi Novaria, Kunang

    Published 2024
    “…Implementing this process uses classification algorithms such asNaïve Bayes, Support Vector Machine,and Random Forest. …”
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  10. 10
    Classification of breast cancer disease using bagging fuzzy-id3 algorithm based on fuzzydbd

    Classification of breast cancer disease using bagging fuzzy-id3 algorithm based on fuzzydbd by Nur Farahaina, Idris

    Published 2022
    “…Classification is a data mining technique used to classify varied data types according to a specific criterion. …”
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  11. 11
    Attribute related methods for improvement of ID3 Algorithm in classification of data: A review

    Attribute related methods for improvement of ID3 Algorithm in classification of data: A review by Nur Farahaina, Idris, Mohd Arfian, Ismail

    Published 2020
    “…Nevertheless, there are some limitations in ID3 algorithm that can affect the performance in the classification of data. …”
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  12. 12
    Integration Of Unsupervised Clustering Algorithm And Supervised Classifier For Pattern Recognition

    Integration Of Unsupervised Clustering Algorithm And Supervised Classifier For Pattern Recognition by Leong, Shi Xiang

    Published 2017
    “…Phase 1 is mainly to evaluate the performance of clustering algorithm (K-Means and FCM). Phase 2 is to study the performance of proposed integration system which using the data clustered to be used as train data for Naïve Bayes classifier. …”
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  13. 13
    Comparison of expectation maximization and K-means clustering algorithms with ensemble classifier model

    Comparison of expectation maximization and K-means clustering algorithms with ensemble classifier model by Sulaiman, Md. Nasir, Mohamed, Raihani, Mustapha, Norwati, Zainudin, Muhammad Noorazlan Shah

    Published 2018
    “…Expectation maximization (EM) is one of the representatives clustering algorithms which have broadly applied in solving classification problems by improving the density of data using the probability density function. …”
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  14. 14
    Development of classification algorithms of human gait

    Development of classification algorithms of human gait by Koh, Chee Hong

    Published 2022
    “…Thus, this study aims to develop a classification algorithm that can effectively classify subjects with relatively simplified input data. …”
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  15. 15
    Text Extraction Algorithm for Web Text Classification

    Text Extraction Algorithm for Web Text Classification by Theab, Mustafa Muwafak

    Published 2010
    “…In this study, the experiment was conducted on five English educational websites. The created data sets are then classified using Naive-Bayes and C4.5 algorithms provided in WEKA application. …”
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  16. 16
    An improve unsupervised discretization using optimization algorithms for classification problems

    An improve unsupervised discretization using optimization algorithms for classification problems by Mohamed, Rozlini, Samsudin, Noor Azah

    Published 2024
    “…According to the experimental findings, the suggested EB has a major effect on the accuracy, recall, and F-measure of data classification. The classification performance using EB outperforms other existing approaches for all datasets.…”
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  17. 17
    An improve unsupervised discretization using optimization algorithms for classification problems

    An improve unsupervised discretization using optimization algorithms for classification problems by Mohamed, Rozlini, Samsudin, Noor Azah

    Published 2024
    “…According to the experimental findings, the suggested EB has a major effect on the accuracy, recall, and F-measure of data classification. The classification performance using EB outperforms other existing approaches for all datasets.…”
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  18. 18
    DATA CLASSIFICATION SYSTEM WITH FUZZY NEURAL BASED APPROACH

    DATA CLASSIFICATION SYSTEM WITH FUZZY NEURAL BASED APPROACH by LUONG, TRUNG TUAN

    Published 2005
    “…The project's objective is identifying the available data mining algorithms in data classification and applying new data mining algorithm to perform classification tasks. …”
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  19. 19
    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
    “…Testing of the application are using 10-Fold Cross Validation technique. 90% of the data be used as a training and another 10% be used for the testing part. …”
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  20. 20
    Sentiment classification for malay newspaper using clonal selection algorithm / Nur Fitri Nabila Mohamad Nasir

    Sentiment classification for malay newspaper using clonal selection algorithm / Nur Fitri Nabila Mohamad Nasir by Mohamad Nasir, Nur Fitri Nabila

    Published 2013
    “…The experimental results show that our method can achieve better performance in clonal selection algorithm sentiment classification and the data collected cannot be used at once in this model because training data is very time-consuming if using all the data. …”
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