Search Results - (( based classification based algorithm ) OR ( time optimization method algorithm ))
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Mussels wandering optimization algorithmn based training of artificial neural networks for pattern classification
Published 2013“…Traditional training algorithms have some drawbacks such as local minima and its slowness.Therefore, evolutionary algorithms are utilized to train neural networks to overcome these issues.This research tackles the ANN training by adapting Mussels Wandering Optimization (MWO) algorithm.The proposed method tested and verified by training an ANN with well-known benchmarking problems.Two criteria used to evaluate the proposed method were overall training time and classification accuracy.The obtained results indicate that MWO algorithm is on par or better in terms of classification accuracy and convergence training time.…”
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Improving amphetamine-type stimulants drug classification using chaotic-based time-varying binary whale optimization algorithm
Published 2022“…A new chaotic time-varying binary whale optimization algorithm (CBWOATV) is introduced in this paper to optimize the feature selection process in Amphetamine-type Stimulants (ATS) and non-ATS drugs classification. …”
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Inversed Control Parameter in Whale Optimization Algorithm and Grey Wolf Optimizer for Wrapper-Based Feature Selection: A Comparative Study
Published 2023“…Yet, the slow convergence speed issue in the Whale Optimization Algorithm and Grey Wolf Optimizer could demote the performance of feature selection and classification accuracy. …”
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Inversed Control Parameter in Whale Optimization Algorithm and Grey Wolf Optimizer for Wrapper-Based Feature Selection: A Comparative Study
Published 2023“…Yet, the slow convergence speed issue in the Whale Optimization Algorithm and Grey Wolf Optimizer could demote the performance of feature selection and classification accuracy. …”
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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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Enhancing Classification Algorithms with Metaheuristic Technique
Published 2024“…However, the classification algorithm cannotclassify data optimally due to the challenges in dealing with variousdata sets. …”
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Fair bandwidth distribution marking and scheduling algorithm in network traffic classification
Published 2019“…Second, an Optimized time sliding window packet marker (OTSWTCM) algorithm. …”
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Improved cuckoo search based neural network learning algorithms for data classification
Published 2014“…This research proposed an improved CS called hybrid Accelerated Cuckoo Particle Swarm Optimization algorithm (HACPSO) with Accelerated particle Swarm Optimization (APSO) algorithm. …”
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Logistic regression methods for classification of imbalanced data sets
Published 2012“…However, the imbalanced LR-based methods are not extensively developed such as imbalanced SVM-based methods. …”
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Feature Selection Based on Grey Wolf Optimizer for Oil Gas Reservoir Classification
Published 2020“…In addition, to examine the efficiency of the proposed method, two recent algorithms namely: Whale Optimization algorithm (WAO) and Dragonfly Algorithm (DA) are implemented for comparison. …”
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An ensemble learning method for spam email detection system based on metaheuristic algorithms
Published 2015“…Feature subset selection and classifier ensemble learning are familiar techniques with high ability to optimize above problems. Recently, various techniques based on different algorithms have been developed. …”
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BAT-BP: A new BAT based back-propagation algorithm for efficient data classification
Published 2016“…One of the nature inspired meta-heuristic Bat algorithm is becoming a popular method in solving many complex optimization problems. …”
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Rao-SVM machine learning algorithm for intrusion detection system
Published 2020“…Most of the intrusion detection systems are developed based on optimization algorithms as a result of the increase in audit data features; optimization algorithms are also considered for IDS due to the decline in the performance of the human-based methods in terms of their training time and classification accuracy. …”
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Selection and optimization of peak features for event-related eeg signals classification / Asrul bin Adam
Published 2017“…At first, a peak classification algorithm is developed based on the general following processes including peak candidate identification, feature extraction, and classification. …”
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Finite impulse response optimizers for solving optimization problems
Published 2019“…The classification of estimation-based metaheuristic algorithms has been introduced for solving optimization problems. …”
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Finite impulse response optimizers for solving optimization problems
Published 2019“…The classification of estimation-based metaheuristic algorithms has been introduced for solving optimization problems. …”
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Adapting and enhancing mussels wandering optimization algorithm for supervised training of neural networks
Published 2015“…The major objective of this thesis is to achieve better performance in terms of convergence training time and classification accuracy for pattern classification by proposing new supervised training methods for Artificial Neural Networks (ANN) based on the MWO algorithm. …”
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Sauvola Segmentation and Support Vector Machine-Salp Swarm Algorithm Approach for Identifying Nutrient Deficiencies in Citrus Reticulata Leaves
Published 2024“…The proposed method integrates colour and texture feature-based image analysis with machine learning algorithms for classification. …”
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