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1
Aco-based feature selection algorithm for classification
Published 2022“…However, the MGCACO algorithm has three main drawbacks in producing a features subset because of its clustering method, parameter sensitivity, and the final subset determination. …”
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2
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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3
Feature extraction and selection algorithm based on self adaptive ant colony system for sky image classification
Published 2023“…The ant colony optimisation (ACO) algorithm have been used to select feature subset. …”
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4
Fair bandwidth distribution marking and scheduling algorithm in network traffic classification
Published 2019“…Finally, propose a new method of obtaining optimal parameters dropping functions for Random Early Detection (RED) algorithm. …”
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5
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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6
Class binarization with self-adaptive algorithm to improve human activity recognition
Published 2018“…Therefore, feature selection using Relief-f with self-adaptive Differential Evolution (rsaDE) algorithm is proposed to select the most significant features. …”
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7
Utilisation of Exponential-Based Resource Allocation and Competition in Artificial Immune Recognition System
Published 2011“…Artificial Immune Recognition System is one of the several immune inspired algorithms that can be used to perform classification, a data mining task. …”
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8
Affect classification using genetic-optimized ensembles of fuzzy ARTMAPs
Published 2015“…Speciation was implemented using subset selection of classification data attributes, as well as using an island model genetic algorithms method. …”
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9
Condition diagnosis of bearing system using multiple classifiers of ANNs and adaptive probabilities in genetic algorithms
Published 2014“…Therefore, finding the best weights in learning process is an important task for obtaining good performance of ANNs.Previous researchers have proposed some methods to get the best weights such as simple average and majority voting.However, these methods have some limitations in providing the best weights especially in condition diagnosis of bearing systems.In this paper, we propose a hybrid technique of multiple classifier-ANNs (mANNs) and adaptive probabilities in genetic algorithms (APGAs) to obtain the best weights of ANNs in order to increase the classification performance of ANNs in condition diagnosis of bearing systems. …”
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10
Modified anfis architecture with less computational complexities for classification problems
Published 2018“…Furthermore, researchers have mainly used metaheuristic algorithms to avoid the problem of local minima in standard learning method. …”
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11
Heart disease prediction using artificial neural network with ADAM optimization and harmony search algorithm
Published 2025“…This performance is validated through rigorous comparative assessments against various classification algorithms and state-of-the-art methods, revealing notable advantages in terms of predictive precision, computational efficiency, and adaptability to real-world clinical scenarios. …”
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12
Fractional Stochastic Gradient Descent Based Learning Algorithm For Multi-layer Perceptron Neural Networks
Published 2021“…The proposed FBP-MLP method outperformed the conventional BP-MLP algorithm both in terms of convergence rate and test accuracy. …”
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13
A new descriptor for smile classification based on cascade classifier in unconstrained scenarios
Published 2021“…In this paper, an adaptive model for smile classification is suggested that integrates a row-transform-based feature extraction algorithm and a cascade classifier to increase the precision of facial recognition. …”
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14
A new LoRa based positioning algorithm utilizing sequence based deep learning technique
Published 2023“…Furthermore, an analysis of classification using different sequence length is done. …”
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15
Predicting noise-induced hearing loss (NIHL) in TNB workers using GDAM algorithm
Published 2012“…This research proposed an algorithm for improving the current working performance of Back-propagation algorithm by adaptively changing the momentum value and at the same time keeping the ‘gain’ parameter fixed for all nodes in the neural network. …”
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16
RMIL/AG: A new class of nonlinear conjugate gradient for training back propagation algorithm
Published 2018“…The results show that the computational efficiency of the proposed method was better than the conventional BP algorithm.…”
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17
Face expression recognition using artificial neural network (ANN) / Mazuraini Ghani
Published 2005“…In this project, the suitable method of segmentation is local adaptive threshold. …”
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18
Computational intelligence approach for classification and risk quantification of metabolic syndrome / Habeebah Adamu Kakudi
Published 2019“…Genetic Algorithm(GA) is used to optimize the order of sequence of the input sample and the parameters of the Bayesian ARTMAP (BAM). …”
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19
Development of collision avoidance warning system for heavy vehicles featuring adaptive minimum safe distance / Airul Sharizli Abdullah
Published 2017“…This result is the first major contribution of this dissertation. To represent the adaptive minimum safe distance which will be used in activation algorithm for CAWS, the new distance-based CAWS model, namely Minimum Safe Distance Gap (MSDG) is introduced. …”
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20
A new hybrid deep neural networks (DNN) algorithm for Lorenz chaotic system parameter estimation in image encryption
Published 2023“…In addition, the hyperparameter tuning problem is considered in this research to improve the developed hybrid model by using the AOA algorithm. 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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