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Fuzzy adaptive teaching learning-based optimization for solving unconstrained numerical optimization problems
Published 2022“…Teaching learning-based optimization is one of the widely accepted metaheuristic algorithms inspired by teaching and learning within classrooms. …”
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An improve unsupervised discretization using optimization algorithms for classification problems
Published 2024“…Recognizing the critical role of discretization in enhancing classification performance, the study integrates equal width binning (EWB) with two optimization algorithms: the bat algorithm (BA), referred to as EB, and the whale optimization algorithm (WOA), denoted as EW. …”
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An improve unsupervised discretization using optimization algorithms for classification problems
Published 2024“…Recognizing the critical role of discretization in enhancing classification performance, the study integrates equal width binning (EWB) with two optimization algorithms: the bat algorithm (BA), referred to as EB, and the whale optimization algorithm (WOA), denoted as EW. …”
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The Evolutionary Convergent Algorithm: A Guiding Path of Neural Network Advancement
Published 2025“…In this study, a new idea centered on seed growth, Seed Growth Algorithm (SGA), as a conditional convergent evolutionary algorithm is proposed for optimizing several discrete and continuous optimization problems. …”
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Effective downlink resource management for wimax networks
Published 2018“…Our EDRM framework involves three functions: Class-Based Scheduling (CBS) algorithm, Dynamic Bandwidth Allocation (DBA) scheme and Link Session Management (LSM) policy. …”
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Hybrid harmony search algorithm for continuous optimization problems
Published 2020“…Taken together, the proposed hybrid algorithm, called IHS-GWO, aims to address continuous optimization problems. …”
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A New Quadratic Binary Harris Hawk Optimization For Feature Selection
Published 2019“…Harris hawk optimization (HHO) is one of the recently proposed metaheuristic algorithms that has proven to be work more effectively in several challenging optimization tasks. …”
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An improved teaching-learning-based optimization for extreme learning machine in floating photovoltaic power forecasting
Published 2025“…The proposed method achieved superior forecasting accuracy compared to benchmark algorithms including standard teaching-learning-based optimization with extreme learning machine, manta rays foraging optimization with extreme learning machine, moth flame optimization with extreme learning machine, ant colony optimization with extreme learning machine and salp swarm algorithm with extreme learning machine. …”
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Multi-Robot Learning with Bat Algorithm With Mutation (Bam)
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Identification of continuous-time model of hammerstein system using modified multi-verse optimizer
Published 2021“…his thesis implements a novel nature-inspired metaheuristic optimization algorithm, namely the modified Multi-Verse Optimizer (mMVO) algorithm, to identify the continuous-time model of Hammerstein system. …”
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Deep continual learning for predicting blast-induced overbreak in tunnel construction / He Biao
Published 2024“…The developed model is expected to possess the ability of continual learning, which is particularly advantageous in dynamic environments like tunnel blasting. …”
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Designing and Developing an Intelligent Congkak
Published 2011“…and “Can Min-Max algorithm (MM) be speeded up by using NN as a forward-pruning method?”. …”
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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“…Determination of high performance and lower computing time with simple algorithm is therefore continuously established. Shark Smell Optimization (SSO) algorithm has been proven to have high efficiency in many optimization applications. …”
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Integrated deep learning for cardiovascular risk assessment and diagnosis: An evolutionary mating algorithm-enhanced CNN-LSTM
Published 2025“…This study proposes a dual-output deep learning model based on a hybrid Convolutional Neural Network–Long Short-Term Memory (CNN-LSTM) model, optimized using the Evolutionary Mating Algorithm (EMA). …”
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Adaptive resource allocation algorithms with QoS support in OFDMA-based WiMAX networks
Published 2014“…The aim of this thesis is to develop a fair and effi- cient packet scheduling and adaptive multiuser frequency-time domain resources allocation algorithms to support QoS for a diverse service class in OFDMA based IEEE 802.16 network. …”
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Supervised deep learning algorithms for process fault detection and diagnosis under different temporal subsequence length of process data
Published 2025“…This study, therefore, aims to investigate the effects of varying subsequence lengths on the FDD performance of common deep learning algorithms, consisting of a multilayer perceptron, convolutional neural network, long short-term memory, transformer, industrial process optimization—vision transformer (IPO-Vitt) using two benchmark case studies, namely continuous stirred tank reactor (CSTR) and Tennessee Eastman Process (TEP). …”
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