Search Results - (( based applications optimized algorithm ) OR ( parameter classification problems algorithm ))
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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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Improvement of fuzzy neural network using mine blast algorithm for classification of Malaysian Small Medium Enterprises based on strength
Published 2015“…Many researchers have trained ANFIS parameters using metaheuristic algorithms but very few have considered optimizing the ANFIS rule-base. …”
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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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Optimization of k-Nearest Neighbour to categorize Indonesian’s news articles
Published 2021“…The stages are tuning the parameter of k-NN, the parameter of PSO, and measuring the testing performance. …”
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Taylor-Bird Swarm Optimization-Based Deep Belief Network For Medical Data Classification
Published 2022“…However, finding the most appropriate deep learning algorithm for a medical classification problem along with its optimal parameters becomes a difficult task. …”
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8
Comprehensive review of the development of the harmony search algorithm and its applications
Published 2019“…Second, we describe HS classifications based on the well-known HS variants and hybrid algorithms, along with their applications. …”
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Adaptive differential evolution algorithm with fitness based selection of parameters and mutation strategies / Rawaa Dawoud Hassan Al-Dabbagh
Published 2015“…ARDE algorithm makes use of JADE strategy and the MDE_pBX parameters adaptive schemes as frameworks. …”
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Recent advances in meta-heuristic algorithms for training multilayer perceptron neural networks
Published 2025“…Key contributions include a comparative analysis of evolutionary, swarm intelligence, physics-based, human-inspired algorithms, and hybrid approaches benchmarked on classification datasets. …”
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Hyper-heuristic framework for sequential semi-supervised classification based on core clustering
Published 2020“…Hence, the algorithm must overcome the problem of dynamic update in the internal parameters or countering the concept drift. …”
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Differential evolution for neural networks learning enhancement
Published 2008“…These algorithms can be used successfully in many applications requiring the optimization of a certain multi-dimensional function. …”
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A new hybrid deep neural networks (DNN) algorithm for Lorenz chaotic system parameter estimation in image encryption
Published 2023“…Lastly, a new hybrid technique suggests tackling the current image encryption application problem by using the estimated parameters of chaotic systems with an optimization algorithm, the SKF algorithm. …”
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Activity recognition using optimized reduced kernel extreme learning machine (OPT-RKELM) / Yang Dong Rui
Published 2019“…One of the major research problems is the computation resources required by machine learning algorithm used for classification for HAR. …”
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Class binarization with self-adaptive algorithm to improve human activity recognition
Published 2018“…In order to improve recognition of high interclass similarity activities, One-Versus- All (OVA) binarization strategy is introduced by transforming original multi-class classification problems into a series of two-class classification problems. …”
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Development of cost reduction mathematical model for natural gas transmission network system
Published 2012“…The results obtained from problem were analyzed based on the objective function, and the design parameters of the network. …”
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Hybrid ACO and SVM algorithm for pattern classification
Published 2013“…This study presents four algorithms for tuning the SVM parameters and selecting feature subset which improved SVM classification accuracy with smaller size of feature subset. …”
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Development of compound clustering techniques using hybrid soft-computing algorithms
Published 2006“…Initially, the heuristics needs user intervention to select optimal values, which give poor results. To overcome this problem, fuzzy memberships have been employed to find optimal parameters. …”
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