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A class skew-insensitive ACO-based decision tree algorithm for imbalanced data sets
Published 2021“…This study proposed an enhanced algorithm called hellingerant-tree-miner (HATM) which is inspired by ant colony optimization (ACO) metaheuristic for imbalanced learning using decision tree classification algorithm. …”
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A review of training methods of ANFIS for applications in business and economic
Published 2016“…Moreover, the standard gradient based learning via two pass learning algorithm is prone slow and prone to get stuck in local minima. …”
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Deriving Optimal Operation Rule for Reservoir System Using Enhanced Optimization Algorithms
Published 2025“…This study delves into the exploration of different algorithms, including Artificial Bee Colony (ABC), Particle Swarm Optimization (PSO), Genetic Algorithm (GA), Firefly Algorithm (FA), Invasive Weed Optimization (IWO), Teaching Learning-Based Optimization (TLBO), and Harmony Search (HS). …”
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A review of training methods of ANFIS for applications in business and economics
Published 2016“…Moreover, the standard gradient based learning via two pass learning algorithm is prone slow and prone to get stuck in local minima. …”
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Optimal parameters of an ELM-based interval type 2 fuzzy logic system: a hybrid learning algorithm
Published 2018“…A disadvantage of ELM is the random generation of its hidden neuron that causes additional uncertainty, in both approximation and learning. In order to overcome this limitation in an ELM-based IT2FLS, artificial bee colony optimization algorithm is utilized to obtain its antecedent parts parameters. …”
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RLMD-PA: A Reinforcement Learning-Based Myocarditis Diagnosis Combined with a Population-Based Algorithm for Pretraining Weights
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Transfer learning in near infrared spectroscopy for stingless bee honey quality prediction across different months
Published 2024“…Near infrared spectroscopy (NIRS) coupled with machine learning has demonstrated its capability as an efficient secondary measurement method in various applications. …”
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Adaptive mechanism for enhanced performance of shark smell optimization / Nur Atharah Kamarzaman, Shahril Irwan Sulaiman and Intan Rahayu Ibrahim
Published 2021“…Numerical results indicate that the ASSO algorithm strategy outperforms the basic SSO algorithm, Genertic Algorithm (GA), Particle Swarm Intelligence (PSO), Firefly Algorithm (FA), Artificial Bee Colony (ABC) and Teaching Learning Based Optimization (TBLO) in term of reaching for global solution.…”
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Towards enhanced remaining useful life prediction of lithium-ion batteries with uncertainty using optimized deep learning algorithm
Published 2025“…In addition, to validate the prediction performance of the proposed LSA + LSTM model, extensive comparisons are performed with other popular optimization-based deep learning methods including artificial bee colony (ABC) based LSTM (ABC + LSTM), gravitational search algorithm (GSA) based LSTM (GSA + LSTM), and particle swarm optimization (PSO) based LSTM (PSO + LSTM) model using different error matrices. …”
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Machine Learning and Dyslexia-Diagnostic and Classification System (DCS) for Kids with Learning Disabilities
Published 2018“…This research proposes such a machine learning based diagnostic and classification system. …”
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Evaluating JA-ABC5 hyperparameter optimisation with classifiers
Published 2024“…Because of its simplicity, flexibility, and robustness, the Artificial Bee Colony (ABC) algorithm, a swarm intelligence-based optimisation method, has been widely applied in a variety of fields. …”
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Application of nature-inspired algorithms and artificial intelligence for optimal efficiency of horizontal axis wind turbine / Md. Rasel Sarkar
Published 2019“…In this study, the performance of these three algorithms in obtaining the optimal blade design based on the �436�45D are investigated and compared. …”
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Using the bees algorithm to optimise a support vector machine for wood defect classification
Published 2007“…This paper describes a new application of the Bees Algorithm to the optimization of a Support Vector Machine (SVM) for the problem of classifying defects in plywood. …”
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Application of the bees algorithm to the selection features for manufacturing data
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