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Improving amphetamine-type stimulants drug classification using chaotic-based time-varying binary whale optimization algorithm by Draman @ Muda, Azah Kamilah, Mohd Yusof, Norfadzlia, Pratama, Satrya Fajri, Carbo-Dorca, Ramon, Abraham, Ajith

“…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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Mussels wandering optimization algorithmn based training of artificial neural networks for pattern classification by Abusnaina, Ahmed A., Abdullah, Rosni

“…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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Inversed Control Parameter in Whale Optimization Algorithm and Grey Wolf Optimizer for Wrapper-Based Feature Selection: A Comparative Study by Li Yu Yab, Li Yu Yab, Wahid, Noorhaniza, A Hamid, Rahayu

“…—Whale Optimization Algorithm (WOA) and Grey Wolf Optimizer (GWO) are well-perform metaheuristic algorithms used by various researchers in solving feature selection problems. …”
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Inversed Control Parameter in Whale Optimization Algorithm and Grey Wolf Optimizer for Wrapper-Based Feature Selection: A Comparative Study by Li Yu Yab, Li Yu Yab, Wahid, Noorhaniza, A Hamid, Rahayu

“…Whale Optimization Algorithm (WOA) and Grey Wolf Optimizer (GWO) are well-perform metaheuristic algorithms used by various researchers in solving feature selection problems. …”
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Enhancing Classification Algorithms with Metaheuristic Technique by Cokro, Nurwinto, Tri Basuki, Kurniawan, Misinem, ., Tata, Sutabri, Yesi Novaria, Kunang

“…Meta-heuristic algorithms are search techniques used to solve complexoptimization problems, and these algorithms can help provide reasonable solutions in a shorter time thanexact methods. …”
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Formulating new enhanced pattern classification algorithms based on ACO-SVM by Alwan, Hiba Basim, Ku-Mahamud, Ku Ruhana

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Improved intrusion detection algorithm based on TLBO and GA algorithms by Aljanabi, Mohammad, Mohd Arfian, Ismail

“…Optimization algorithms are widely used for the identification of intrusion. …”
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Fair bandwidth distribution marking and scheduling algorithm in network traffic classification by Al-Kharasani, Ameen Mohammed Abdulkarem

“…Second, an Optimized time sliding window packet marker (OTSWTCM) algorithm. …”
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BAT-BP: A new BAT based back-propagation algorithm for efficient data classification by Mohd. Nawi, Nazri, M. Z., Rehman, Hafifi, Nurfarian, Khan, Abdullah, Siming, Insaf Ali

“…One of the nature inspired meta-heuristic Bat algorithm is becoming a popular method in solving many complex optimization problems. …”
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Sauvola Segmentation and Support Vector Machine-Salp Swarm Algorithm Approach for Identifying Nutrient Deficiencies in Citrus Reticulata Leaves by Lia, Kamelia

“…In the next phase, the datasets are optimized using the Salp Swarm Algorithm (SSA), which improves classification accuracy. …”
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Improved cuckoo search based neural network learning algorithms for data classification by Abdullah, Abdullah

“…Specifically, 6 benchmark classification datasets are used for training the hybrid Artificial Neural Network algorithms. …”
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Logistic regression methods for classification of imbalanced data sets by Santi Puteri Rahayu, -

“…These results can be seen as further explanation on the success of Truncated Newton method in TR-KLR and TR Iteratively Re-weighted Least Square (TR-IRLS) algorithm respectively, because of the equivalence of iterative method used by these algorithms. …”
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Selection and optimization of peak features for event-related eeg signals classification / Asrul bin Adam by Asrul, Adam

“…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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Fuzzy clustering for genetic algorithm based optimized ellipse data in classifying face emotion by Muthukaruppan, Karthigayan, Mohd Rizon, Mohamed Juhari, Sazali, Yaacob, Ramachandran, Nagarajan, Masanori, Sugisaka, Mohd Rozailan, Mamat

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Rao-SVM machine learning algorithm for intrusion detection system by Abd, Shamis N., Alsajri, Mohammad, Ibraheem, Hind Raad

“…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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An ensemble learning method for spam email detection system based on metaheuristic algorithms by Behjat, Amir Rajabi

“…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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Feature Selection Based on Grey Wolf Optimizer for Oil Gas Reservoir Classification by Al-Tashi, Q., Rais, H.M., Abdulkadir, S.J., Mirjalili, S.

“…The wrapper K-Nearest Neighbors (KNN) classifier is used to evaluate the selected features. 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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Ant colony algorithm for text classification in multicore-multithread environment / Ahmad Nazmi Fadzal by Fadzal, Ahmad Nazmi

“…ACO classification accuracy is compared to Genetic Algorithm classifier which also a wrapper method. …”
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Design Of Feature Selection Methods For Hand Movement Classification Based On Electromyography Signals by Too, Jing Wei

“…The first method is the Binary Tree Growth Algorithm (BTGA), which implements a hyperbolic tangent function to convert the Tree Growth Algorithm into the binary version. …”
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Optimization and discretization of dragonfly algorithm for solving continuous and discrete optimization problems by Bibi Amirah Shafaa, Emambocus

“…The trained network is then applied to benchmark classification problems. Based on the experimental results, the optimized DA algorithm is a much better training algorithm for ANNs as compared to the usual gradient-descent backpropagation algorithm since the resultant ANNs trained by the optimized DA achieve higher accuracy. …”
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