Search Results - (( intelligence based svm algorithm ) OR ( intelligence ((based rsa) OR (based data)) algorithm ))
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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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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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Autism Spectrum Disorder Classification Using Deep Learning
Published 2021“…Finally, the effectiveness of the algorithm is evaluated based on the accuracy performance. …”
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Intrusion Detection Systems, Issues, Challenges, and Needs
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Comparative performance of machine learning algorithms for cryptocurrency forecasting
Published 2018“…Machine Learning is part of Artificial Intelligence that has the ability to make future forecastings based on the previous experience. …”
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A hybrid approach for artificial immune recognition system / Mahmoud Reza Saybani
Published 2016“…Many researchers, who have developed methods and algorithms within the field of artificial intelligence, machine learning and data mining, have addressed extracting useful information from the data. …”
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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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Identification of transformer fault based on dissolved gas analysis using hybrid support vector machine-modified evolutionary particle swarm optimisation
Published 2018“…Thus, the proposed technique can be one of the potential solutions to identify the transformer fault type based on DGA data on site.…”
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Data mining for structural damage identification using hybrid artificial neural network based algorithm for beam and slab girder / Meisam Gordan
Published 2020“…In the modeling phase, amongst all DM algorithms, the applicability of machine learning, artificial intelligence and statistical data mining techniques were examined using Support Vector Machine (SVM), Artificial Neural Network (ANN) and Classification and Regression Tree (CART) to detect the hidden patterns in vibration data. …”
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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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GA optimization-based BRB AI reasoning algorithm for determining the factors affecting customer churn for operators
Published 2024“…Therefore, in this paper, a belief rule base (BRB) artificial intelligence inference algorithm based on GA optimization to determine the factors affecting customer churn for operators proposed. …”
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Prognostic Health Management of Pumps Using Artificial Intelligence in the Oil and Gas Sector: A Review
Published 2022“…In comparison to the algorithmic approach, the data approach has not received significant research attention. …”
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A comparative study of clonal selection algorithm for effluent removal forecasting in septic sludge treatment plant
Published 2015“…The test results of the case study showed that the prediction of the CSA-based SSTP model worked well and provided model performance as satisfactory as the LS-SVM model. …”
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Hybrid harmony search-artificial intelligence models in credit scoring
Published 2019“…Statistical models are the main approaches but recently, Artificial Intelligence (AI) techniques have been popular due to their ability to account for flexible data patterns. …”
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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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