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Landslide risk zoning using support vector machine algorithm
Published 2024“…The weighted maps were then combined using the support vector machine algorithm. For the training and testing of the machine, 81 slippery ground points and 81 non-sliding points were used. …”
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Smoothed functional algorithm with norm-limited update vector for identification of continuous-time fractional-order Hammerstein Models
Published 2024“…This article proposes an identification method of continuous-time fractional-order Hammerstein model using smoothed functional algorithm with a norm-limited update vector (NL-SFA). …”
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Forecasting FTSE Bursa Malaysia KLCI Trend with Hybrid Particle Swarm Optimization and Support Vector Machine Technique
Published 2013“…The SVM algorithm uses the Radial Basis Function (RBF) kernel function and optim ization of the gam ma and large margin parameters are done using the PSO algorithm. …”
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Semi-supervised learning for feature selection and classification of data / Ganesh Krishnasamy
Published 2019“…The proposed algorithm is compared with the state-of-the-art feature selection algorithms using three different datasets. …”
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Sentiment Analysis on COVID-19 Vaccine Tweets using Machine Learning and Deep Learning Algorithms
Published 2023“…Machine learning algorithms like Logistic Regression, Naïve Bayes, Support Vector Machine (SVM) and others, and Deep Learning algorithms like LSTM and Bert were used to train the predictive models. …”
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Sentiment Analysis on COVID-19 Vaccine Tweets using Machine Learning and Deep Learning Algorithms
Published 2023“…Machine learning algorithms like Logistic Regression, Naïve Bayes, Support Vector Machine (SVM) and others, and Deep Learning algorithms like LSTM and Bert were used to train the predictive models. …”
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Sentiment Analysis on COVID-19 Vaccine Tweets using Machine Learning and Deep Learning Algorithms
Published 2023“…Machine learning algorithms like Logistic Regression, Naïve Bayes, Support Vector Machine (SVM) and others, and Deep Learning algorithms like LSTM and Bert were used to train the predictive models. …”
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8
State-dependent sliding mode control for three-phase induction motor drives
Published 2014“…A fast sigmoid function with varying boundary layer algorithm is designed as a state-dependent to replace the discontinuous function in conventional sliding mode control as well as to avoid steady state error compare with the use of fixed boundary layer. …”
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9
Indoor positioning using weighted magnetic field signal distance similarity measure and fuzzy based algorithms
Published 2021“…Additionally, the effect of signal weighting function is investigated further using multiple K values of K nearest neighbour (KNN) algorithm. …”
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10
Sentiment Analysis on COVID-19 Vaccine Tweets using Machine Learning and Deep Learning Algorithms
Published 2023“…Machine learning algorithms like Logistic Regression, Naïve Bayes, Support Vector Machine (SVM) and others, and Deep Learning algorithms like LSTM and Bert were used to train the predictive models. …”
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Sentiment Analysis on COVID-19 Vaccine Tweets using Machine Learning and Deep Learning Algorithms
Published 2023“…Machine learning algorithms like Logistic Regression, Naïve Bayes, Support Vector Machine (SVM) and others, and Deep Learning algorithms like LSTM and Bert were used to train the predictive models. …”
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Sliding Mode Speed Control for Induction Motor Drives with State-Dependent Gain Method
Published 2013“…In this research, the chattering phenomenon is significantly reduced by a newly developed algorithm. …”
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Simulated kalman filter with modified measurement, substitution mutation and hamming distance calculation for solving traveling salesman problem
Published 2022“…Research limitations – The experiment of this research only uses 15 types of TSP function which are TSP functions that are evaluated using Euclidean distance. …”
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14
Widely linear dynamic quaternion valued least mean square algorithm for linear filtering
Published 2017“…Thus, the proposed algorithms proved to be superior over the other algorithms in all aspects.…”
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AI recommendation penetration testing tool for cross-site scripting: support vector machine algorithm
Published 2025“…This research introduces a new approach to enhancing cybersecurity by integrating Support Vector Machine (SVM) algorithms with penetration testing to develop a recommendation system focused on Cross-Site Scripting (XSS) attack detection. …”
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Named entity recognition using a new fuzzy support vector machine.
Published 2008“…Some of the Machine learning algorithms used in NER methods are, support vector machine(SVM), Hidden Markov Model, Maximum Entropy Model (MEM) and Decision Tree. …”
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Feedforward neural network for solving particular fractional differential equations
Published 2024“…This study also focuses on solving fractal-fractional differential equations in the Caputo sense with a power-law kernel (FFDEsCP) using FNN in two hidden layers with a vectorized algorithm alongside Adam (FNN2HLVA-Adam). …”
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Enhancement of new smooth support vector machines for classification problems
Published 2011“…The smooth function is used to replace the plus function to obtain a smooth support vector machine (SSVM). …”
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Optimal network reconfiguration and intelligent service restoration prediction technique based on Cuckoo search spring algorithm / Mohamad Izwan Zainal
Published 2022“…In addition, objective function using the same CSSA algorithm were applied i.e., Vmin and Ploss as the objective function, and multi-objective involves Vmin and Ploss as the objective function. …”
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