Search Results - (( simulation optimization svm algorithm ) OR ( variable learning process algorithm ))
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Features selection for intrusion detection system using hybridize PSO-SVM
Published 2016“…Hybridize Particle Swarm Optimization (PSO) as a searching algorithm and support vector machine (SVM) as a classifier had been implemented to cope with this problem. …”
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Fault classification in smart distribution network using support vector machine
Published 2023“…Right setting parameters are important to learning results and generalization ability of SVM. Gaussian radial basis function (RBF) kernel function has been used for training of SVM to accomplish the most optimized classifier. …”
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Performance improvement through optimal location and sizing of distributed generation / Zuhaila Mat Yasin
Published 2014“…Finally, a novel hybrid Quantum-Inspired Evolutionary Programming - Least-Squares Support Vector Machine (QIEP-SVM) was presented. The results showed that the QIEP-SVM model had shown better prediction performance as compared to classical ANN, LS-SVM and QIEP-ANN.…”
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Modelling of optimized hybrid debris flow using airborne laser scanning data in Malaysia
Published 2019“…The general objective of the study was the development of optimized hybrid debris flow models using airborne laser scanning data and Machine learning algorithms in Malaysia. …”
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Efficient and low complexity modulation classification algorithm for MIMO systems
Published 2015“…The classification performance of the proposed algorithm was evaluated via extensive simulations under different operating conditions and was also compared with the one obtained with the optimal Hybrid Likelihood Ratio Test (HLRT) approach. …”
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Reactive power planning for maximum load margin improvement using Fast Artificial Immune Support Vector Machine (FAISVM)
Published 2023“…It also proposes a fast optimization algorithm for reactive power planning problem (RPP) through Fast Artificial Immune Support Vector Machine (FAISVM). …”
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Ensemble dual recursive learning algorithms for identifying flow with leakage
Published 2010“…This paper proposed that, combination of two algorithms into one learning algorithm for predicting mass flow rate of a flow with leakage resulting in a better mass prediction error compare to a model with single learning algorithm.…”
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Open phase fault-tolerant support vector machine predictive power control for six-phase induction generator WECS
Published 2025“…Then, open-phase localization is achieved using the Support Vector Machine (SVM) with hyperparameter Bayesian Optimization (BO). …”
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Hybrid ANN and Artificial Cooperative Search Algorithm to Forecast Short-Term Electricity Price in De-Regulated Electricity Market
Published 2019“…Actual data sets are collected from Ontario electricity market of the year 2017 for the verification of simulation results. Finally, the simulation results validated the premise of the proposed hybrid method through enhanced accuracy compared to the results acquired by implementing hybrid support vector machine (SVM) and hybrid ANN optimization methods. © 2013 IEEE.…”
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Ensemble Dual Recursive Learning Algorithms for Identifying Custom Tanks Flow with Leakage
Published 2010“…This paper proposed that, combination of two algorithms into one learning algorithm for predicting mass flow rate of a flow with leakage resulting in a better mass prediction error as compared to a model with single learning algorithm.…”
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Conference or Workshop Item -
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Evaluating enhanced predictive modeling of foam concrete compressive strength using artificial intelligence algorithms
Published 2025Subjects:Article -
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Weather prediction in Kota Kinabalu using linear regressions with multiple variables
Published 2021“…Numerical weather prediction is the process of using existing numerical data on weather conditions to forecast the weather using machine learning algorithms. …”
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Modeling and validation of base pressure for aerodynamic vehicles based on machine learning models
Published 2023“…The process variables (Mach number (M), nozzle pressure ratio (η), area ratio (α), and length-to-diameter ratio (γ )) were numerically explored to address several aspects of this process, namely base pressure (β) and base pressure with the cavity (βcav). …”
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Prediction of Machine Failure by Using Machine Learning Algorithm
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Feasibility analysis for predicting the compressive and tensile strength of concrete using machine learning algorithms
Published 2024Subjects:Article
