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Talent classification using support vector machine technique / Hamidah Jantan, Norazmah Mat Yusof and Mohd Hanapi Abdul Latif
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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Artificial Intelligence (AI) to predict dental student academic performance based on pre-university results
Published 2022“…Classifiers employed for the system include Logistic Regression (LR), Decision Tree (DT), Random Forest (RF), and Support Vector Machine (SVM) techniques. …”
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Proceeding Paper -
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Geospatial AI-based approach to assess the spatiotemporal suitability of onshore wind-solar farms in Iraq
Published 2023“…In this context, global geospatial data for 13 conditioning factors were collected, and 55,619 inventory samples of wind and solar stations worldwide were prepared to train three machine learning (ML) algorithms, namely Random Forest (RF), Support Vector Machine (SVM), and Multi-Layer Perceptron (MLP). …”
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Thesis -
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Optimization of least squares support vector machine technique using genetic algorithm for electroencephalogram multi-dimensional signals
Published 2016“…Since emotion plays a vital role in human daily life, the ability of computer to interpret and response to human emotion is a crucial element for future intelligent system.Accordingly, several studies have been conducted to recognise human emotion using different technique such as facial expression, speech, galvanic skin response (GSR), or heart rate (HR).However, such techniques have problems mainly in terms of credibility and reliability as people can fake their feeling and response. …”
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Internet of Things-based Home Automation with Network Mapper and MQTT Protocol
Published 2025“…Emerging technical concepts like Web3 and Industry 5.0 require decentralised and intelligent systems near the network's edge. Petabytes of IoT sensor-generated data cause a shortage of storage on the Cloud servers, adding a delay factor to the IoT system. …”
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Global spatial suitability mapping of wind and solar systems using an explainable aI-based approach
Published 2022“…This study presents a global wind and solar mapping approach based on eXplainable Artificial Intelligence (XAI). To the best of the author’s knowledge, the current study is the first attempt to create global maps for siting onshore wind and solar power systems and formulate novel weights for decision criteria. …”
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Multi-label risk diabetes complication prediction model using deep neural network with multi-channel weighted dropout
Published 2025“…This study addresses this gap by leveraging data from the Behavioral Risk Factor Surveillance System (BRFSS)from 2016 to 2021 to categorize seven diabetes complications simultaneously. …”
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Abnormalities and fraud electric meter detection using hybrid support vector machine & genetic algorithm
Published 2023Subjects:Conference Paper -
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Computational intelligence approaches for classification of medical data: State-of-the-art, future challenges and research directions
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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Intrusion Detection Systems, Issues, Challenges, and Needs
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Intelligent decision support systems: transforming smart cities management
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
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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Identification of transformer fault based on dissolved gas analysis using hybrid support vector machine-modified evolutionary particle swarm optimisation
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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Development of colorization of grayscale images using CNN-SVM
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Book Chapter -
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Real-time human activity recognition using external and internal spatial features
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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Dual-tone multifrequency signal detection using support vector machines
Published 2023Subjects:Conference paper -
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