Search Results - (( intelligence based e algorithm ) OR ( intelligence system svm algorithm ))*

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    Identification of transformer fault based on dissolved gas analysis using hybrid support vector machine-modified evolutionary particle swarm optimisation by Illias, Hazlee Azil, Wee, Zhao Liang

    Published 2018
    “…In this work, a hybrid support vector machine (SVM) with modified evolutionary particle swarm optimisation (EPSO) algorithm was proposed to determine the transformer fault type. …”
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    Article
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    Hybrid harmony search-artificial intelligence models in credit scoring by Goh, Rui Ying

    Published 2019
    “…The discussions are based on discriminating ability, model explainability and computational time. …”
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    Thesis
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    Magnetic resonance imaging sense reconstruction system using FPGA / Muhammad Faisal Siddiqui by Muhammad Faisal , Siddiqui

    Published 2016
    “…Complex multiplier, complex matrix multiplier and pseudo-inverse modules are designed according to the algorithmic needs to increase the efficiency of the system. …”
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    Thesis
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    Feature extraction and supervised learning for volatile organic compounds gas recognition by Mohd Tombel, Nor Syahira, Mohd Zaki, Hasan Firdaus, Mohd Fadglullah, Hanna Farihin

    Published 2023
    “…This research project aims to investigate effective feature extraction techniques that can be employed as discriminative features for machine learning algorithms. A preliminary dataset was used to predict VOC classification through the application of five supervised machine learning algorithms: k-Nearest Neighbors (kNN), Random Forest (RF), Support Vector Machines (SVM), Logistic Regression (LR), and Artificial Neural Networks (ANN). …”
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    Article
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    Geospatial AI-based approach to assess the spatiotemporal suitability of onshore wind-solar farms in Iraq by Sachit, Mourtadha Sarhan Almushattat

    Published 2023
    “…Second, eXplainable Artificial Intelligence (XAI) was introduced to formulate novel global weights for those criteria. …”
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    Thesis
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    Computational intelligence approaches for classification of medical data: State-of-the-art, future challenges and research directions by Kalantari, Ali, Kamsin, Amirrudin, Shamshirband, Shahaboddin, Gani, Abdullah, Alinejad-Rokny, Hamid, Chronopoulos, Anthony T.

    Published 2018
    “…On the other hand, the hybridization of SVM with other methods such as SVM-Genetic Algorithm (SVM-GA), SVM-Artificial Immune System (SVM-AIS), SVM-AIRS and fuzzy support vector machine (FSVM) had great performances achieving better results in terms of accuracy, sensitivity and specificity.…”
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    Article
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    Talent classification using support vector machine technique / Hamidah Jantan, Norazmah Mat Yusof and Mohd Hanapi Abdul Latif by Jantan, Hamidah, Mat Yusof, Norazmah, Abdul Latif, Mohd Hanapi

    Published 2014
    “…By implementing soft computing techniques in data mining especially in HR field can enhance the knowledge discovery process for intelligent decision system. Support Vector Machine (SVM) is among the popular learning algorithm for classification in soft computing techniques. …”
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    Research Reports
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    Intelligent decision support systems: transforming smart cities management by Ahmed, Zeinab E., Hassan Abdalla Hashim, Aisha, Mokhtar, Rania A., Saeed, Mamoon M.

    Published 2024
    “…A comparison of the energy used by promised by these algorithms including LSTM, SVM, KNN, and the OPTIMUS, a system is developed that enables smart cities to significantly save energy hence highlighting its efficiency. …”
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    Proceeding Paper
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    Prediction of photovoltaic system output using hybrid Cuckoo Search Least Square Support Vector Machine / Muhammad Aidil Adha Aziz by Aziz, Muhammad Aidil Adha

    Published 2019
    “…Therefore, Cuckoo Search Algorithm (CS) is hybrid with LS-SVM in order to optimize the RBF parameters for a better prediction performance. …”
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    Thesis
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    Real-time human activity recognition using external and internal spatial features by Htike@Muhammad Yusof, Zaw Zaw, Egerton, Simon, Kuang, Ye Chow

    Published 2010
    “…The system is feasible to operate efficiently in real-time and deployable in intelligent environments.…”
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    Proceeding Paper
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