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Computational intelligence approaches for classification of medical data: State-of-the-art, future challenges and research directions
Published 2018“…The results show that on the one hand Support Vector Machine (SVM) and Artificial Immune Recognition System (AIRS) as a single based computational intelligence approach were the best methods in medical applications. …”
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Intrusion Detection Systems, Issues, Challenges, and Needs
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Time series data intelligent clustering algorithm for landslide displacement prediction
Published 2018“…To address this problem, an intelligent clustering algorithm for time series data in landslide displacement prediction based on nonlinear dynamic time bending is proposed in this 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“…This thesis presents a practical and reliable approach for the prediction of PV power output using an intelligent-based technique namely Cuckoo Search Algorithm - Least Square Support Vector Machine (CS-LSSVM). …”
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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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Dual-tone multifrequency signal detection using support vector machines
Published 2023Subjects:Conference paper -
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Hybrid harmony search-artificial intelligence models in credit scoring
Published 2019“…Due to the increased computational effort from HS-SVM and HS-RF, a modified HS (MHS) hybridized with SVM and RF are proposed in this study for an effective yet efficient search. …”
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Artificial Intelligence (AI) to predict dental student academic performance based on pre-university results
Published 2022“…Objective: This study aims to predict the academic performance of dental students based on their admission results using Artificial Intelligence. …”
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Application of machine learning algorithms to predict removal efficiency in treating produced water via gas hydrate-based desalination
Published 2025“…In this context. ML algorithms provide powerful data driven means to model complex relationship within experimental datasets to improve process optimisation This study systematically evaluated several supervised ML models, including Random Forest (RF) Support Vector Machines (SVM), Ridge Regression, Lasso Regression, Decision Tree, Extra Tree Regression, Gradient Boost, and XGBoost, to predict removal efficiency in GHBD system. …”
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A preliminary lightweight random forest approach-based image classification for plant disease detection
Published 2022“…Random Forest is a special kind of ensemble learning technique and it turns out to perform very well compared to other classification algorithms such as Support Vector Machines (SVM) and Artificial Neural Networks (ANN). …”
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A hybrid approach for artificial immune recognition system / Mahmoud Reza Saybani
Published 2016“…The FSR-AIRS2 is a new hybrid algorithm that incorporates the FRA, RRC, and the SVM into AIRS2 in order to produce a stronger classifier. …”
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Performance improvement through optimal location and sizing of distributed generation / Zuhaila Mat Yasin
Published 2014“…To enhance the robustness of the algorithm, the QIEP technique is constructed based on multiobjective model in which the multiobjective functions consist of reducing power losses, increasing maximum loadability and cost minimisation. …”
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Prognostic Health Management of Pumps Using Artificial Intelligence in the Oil and Gas Sector: A Review
Published 2022“…This article present a critical analysis of machine learningâ��s most current advances in the field of artificial intelligence-based system health management, specifically in terms of pump applications in the oil and gas industries. …”
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Acoustic Emission and Artificial Intelligent Methods in Condition Monitoring of Rotating Machine – A Review
Published 2016“…Furthermore, the paper attempts to summarize and evaluate the recent condition monitoring research that utilizing AI includes fuzzy logic, artificial neural network (ANN), support vector machine (SVM), and genetic algorithms (GA) in fault diagnosis, fault classification, fault localization and fault size estimation in gear and bearing based on features extraction from AE signal. …”
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Conference or Workshop Item
