Search Results - (( parameter classification based algorithm ) OR ( using solution using algorithm ))
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Finite impulse response optimizers for solving optimization problems
Published 2019“…Simulated Kalman filter (SKF) algorithm is one of the algorithms under this classification. …”
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Finite impulse response optimizers for solving optimization problems
Published 2019“…Simulated Kalman filter (SKF) algorithm is one of the algorithms under this classification. …”
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Enhanced grey wolf optimisation algorithm for feature selection in anomaly detection
Published 2022“…The second modification develops a new position update mechanism using the Bat Algorithm movement. The third modification improves the controlled parameter of the MBGWO algorithm using indicators from the search process to refine the solution. …”
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Accelerated mine blast algorithm for ANFIS training for solving classification problems
Published 2016“…Keeping in view the drawbacks of gradients based learning of ANFIS using gradient descent and least square methods in two-pass learning algorithm, many have trained ANFIS using metaheuristic algorithms. …”
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Symmetric Key Size for Different Level of Information Classification
Published 2006“…Therefore confidential information is normally protected by using cryptographic algorithms. In these algorithms, key is an important element since it is one of the parameters that determine the level of security that the algorithms can provide. …”
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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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An enhanced soft set data reduction using decision partition order technique
Published 2017“…Furthermore, the decomposition based on previous algorithms could not achieve better parameter reduction in available domain space. …”
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8
Algorithmic design issues in adaptive differential evolution schemes: Review and taxonomy
Published 2018“…The performance of most metaheuristic algorithms depends on parameters whose settings essentially serve as a key function in determining the quality of the solution and the efficiency of the search. …”
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Measuring height of high-voltage transmission poles using unmanned aerial vehicle (UAV) imagery
Published 2017“…The authors propose an UAV approach that utilises a digital surface model and incorporates a stereo matching algorithm based on UAV stereo images. The proposed algorithm was based on a graph-cut (GC) algorithm that measured the disparity map. …”
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Different mutation and crossover set of genetic programming in an automated machine learning
Published 2020“…One of the progressing works for automated machine learning improvement is the inclusion of evolutionary algorithm such as Genetic Programming. The function of Genetic Programming is to optimize the best combination of solutions from the possible pipelines of machine learning modelling, including selection of algorithms and parameters optimization of the selected algorithm. …”
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Different mutation and crossover set of genetic programming in an automated machine learning
Published 2020“…One of the progressing works for automated machine learning improvement is the inclusion of evolutionary algorithm such as Genetic Programming. The function of Genetic Programming is to optimize the best combination of solutions from the possible pipelines of machine learning modelling, including selection of algorithms and parameters optimization of the selected algorithm. …”
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Optimizing in-car-abandoned children’s sounds detection using deep learning algorithms / Nur Atiqah Izzati Md Fisol
Published 2023“…To address this problem, an optimized in-car-abandoned children's sounds detection model using deep learning algorithms is proposed. The objective of this study is to develop an accurate and efficient model capable of recognizing the presence of children in cars based on sound data. …”
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Student Project -
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Tree-based contrast subspace mining method
Published 2020“…Genetic algorithm has been widely used to find global solution to optimization and search problem. …”
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15
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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16
Differential evolution for neural networks learning enhancement
Published 2008“…Evolutionary computation is the name given to a collection of algorithms based on the evolution of a population toward a solution of a certain problem. …”
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The effect of pre-processing techniques and optimal parameters on BPNN for data classification
Published 2015“…It’s data-driven, self-adaptive, and non-linear capabilities channel it for use in processing at high speed and ability to learn the solution to a problem from a set of examples. …”
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19
Machine-learning-based adaptive distance protection relay to eliminate zone-3 protection under-reach problem on statcom-compensated transmission lines
Published 2020“…These parameters are used to develop a standalone intelligently machine learning adaptive distance relay (ML-ADR) modification. …”
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An enhanced gated recurrent unit with auto-encoder for solving text classification problems
Published 2020“…Classification has become an important task for categorizing documents automatically based on their respective groups. …”
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