Search Results - (( simulation optimization problem algorithm ) OR ( binary classification learning algorithm ))
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1
Selection and optimization of peak features for event-related eeg signals classification / Asrul bin Adam
Published 2017“…Next, four recently introduced optimization algorithms are employed as feature selector, namely as 1) angle modulated simulated Kalman filter (AMSKF), 2) binary simulated Kalman filter (BSKF), 3) local optimum distance evaluated simulated Kalman filter (LocalDESKF), and 4) global optimum distance evaluated simulated Kalman filter (GlobalDESKF). …”
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Information Theoretic-based Feature Selection for Machine Learning
Published 2018“…Three major factors that determine the performance of a machine learning are the choice of a representative set of features, choosing a suitable machine learning algorithm and the right selection of the training parameters for a specified machine learning algorithm. …”
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3
Performances of machine learning algorithms for binary classification of network anomaly detection system
Published 2018“…The finding showed that AODE algorithm is performed well in term of accuracy and processing time for binary classification towards UNSW-NB15 dataset.…”
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An improved algorithm for iris classification by using support vector machine and binary random machine learning
Published 2018“…The second objective is to conduct a supervised and binary ensemble machine learning technique for classification. …”
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5
A New Quadratic Binary Harris Hawk Optimization For Feature Selection
Published 2019“…A comparative study is conducted to compare the effectiveness of QBHHO with other feature selection algorithms such as binary differential evolution (BDE), genetic algorithm (GA), binary multi-verse optimizer (BMVO), binary flower pollination algorithm (BFPA), and binary salp swarm algorithm (BSSA). …”
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An ensemble learning method for spam email detection system based on metaheuristic algorithms
Published 2015“…In order to address the challenges that mentioned above in this study, in the first phase, a novel architecture based on ensemble feature selection techniques include Modified Binary Bat Algorithm (NBBA), Binary Quantum Particle Swarm Optimization (QBPSO) Algorithm and Binary Quantum Gravita tional Search Algorithm (QBGSA) is hybridized with the Multi-layer Perceptron (MLP) classifier in order to select relevant feature subsets and improve classification accuracy. …”
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7
Analysis Of Personal Protective Equipment Classification Method Using Deep Learning
Published 2022“…Based on the result, CNN algorithm is a good algorithm as the binary classification of PPE achieved high accuracy result.…”
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Undergraduates Project Papers -
8
Multi-Class Multi-Level Classification of Mental Health Disorders Based on Textual Data from Social Media
Published 2024“…The Multi-Class Multi-Level (MCML) classification algorithm was applied to perform detailed classification and address the limitations of the research scope using several approaches, including machine learning, deep learning, and transfer learning approaches. …”
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A discrete simulated kalman filter optimizer for combinatorial optimization problems
Published 2022“…Another type of algorithm is called numerical algorithms. These algorithms were built specifically to address numerical optimization problems. …”
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11
Binary whale optimization algorithm with logarithmic decreasing time-varying modified sigmoid transfer function for descriptor selection problem
Published 2023“…The new Binary Whale Optimization Algorithm is integrated with wrapper feature selection and validated on descriptor selection problem to improve Amphetamine-type stimulants drug classification result. …”
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Conference or Workshop Item -
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Simulated Kalman Filter algorithms for solving optimization problems
Published 2019“…In this research, two novel estimation-based metaheuristic optimization algorithms, named as Simulated Kalman Filter (SKF), and single-solution Simulated Kalman Filter (ssSKF) algorithms are introduced for global optimization problems. …”
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13
A Novel Aggregate Classification Technique Using Moment Invariants and Cascaded Multilayered Perceptron Network
Published 2009“…The c-MLP network consists of three MLPs which are arranged in a serial combination and trained with the same learning algorithm. The proposed method has been tested and compared with twelve machine learning algorithms namely Levenberg-Marquardt (LM), Broyden-Fletcher-Goldfarb-Shanno quasi-newton (BFG), Resilient back propagation (RP), Scaled conjugate gradient (SCG), Conjugate gradient with Powell-Beale restarts (CGB), Conjugate gradient with Fletcher-Reeves updates (CGF), Conjugate gradient with Polak-Ribiere updates (CGP), One step secant (OSS), Bayesian regularization (BR), Gradient descent (GD), Gradient descent with momentum and adaptive learning rate (GDX) and Gradient descent with momentum (GDM) algorithms. …”
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Rao-SVM machine learning algorithm for intrusion detection system
Published 2020“…This article presents the development of an improved intrusion detection method for binary classification. In the proposed IDS, Rao Optimization Algorithm, Support Vector Machine (SVM), Extreme Learning Machine (ELM), and Logistic Regression (LR) (feature selection and weighting) were combined with NTLBO algorithm with supervised ML techniques (for feature subset selection (FSS). …”
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Improved intrusion detection algorithm based on TLBO and GA algorithms
Published 2021“…The proposed method combined the New Teaching-Learning-Based Optimization Algorithm (NTLBO), Support Vector Machine (SVM), Extreme Learning Machine (ELM), and Logistic Regression (LR) (feature selection and weighting) NTLBO algorithm with supervised machine learning techniques for Feature Subset Selection (FSS). …”
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Simulated Kalman Filter: A Novel Estimation-based Metaheuristic Optimization Algorithm
Published 2016“…To evaluate the performance of the Simulated Kalman Filter algorithm, it is applied to 30 benchmark functions of CEC 2014 for real-parameter single objective optimization problems. …”
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Conference or Workshop Item -
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Angle Modulated Simulated Kalman Filter Algorithm for Combinatorial Optimization Problems
Published 2016“…However, the SKF is only capable to solve continuous numerical optimization problem. In order to solve discrete optimization problems, the SKF algorithm is combined with an angle modulated approach. …”
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Distance evaluated simulated kalman filter with state encoding for combinatorial optimization problems
Published 2018“…The SKF algorithm only capable to solve numerical optimization problems which involve continuous search space. …”
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Machine learning approach for stress detection based on alpha-beta and theta-beta ratios of EEG signals
Published 2021“…This study will ultimately contribute to society's development with improved robust machine learning algorithm for binary classification.…”
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Proceeding Paper -
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Hybrid firefly and particle swarm optimization algorithm for multi-objective optimal power flow with distributed generation
Published 2022“…This thesis proposes and simulates the three novel optimization algorithms to handle DG allocation, different single-objective, and multi-objective OPF problems. …”
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