Search Results - (( using function search algorithm ) OR ( simulation classification using algorithm ))
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Improved cuckoo search based neural network learning algorithms for data classification
Published 2014“…Specifically, 6 benchmark classification datasets are used for training the hybrid Artificial Neural Network algorithms. …”
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Weight Optimization in Recurrent Neural Networks with Hybrid Metaheuristic Cuckoo Search Techniques for Data Classification
Published 2015“…The proposed CSERN and CSBPERN algorithms are compared with artificial bee colony using BP algorithm and other hybrid variants algorithms. …”
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An improved bat algorithm with artificial neural networks for classification problems
Published 2016“…Metaheuristic search algorithms have been used for quite a while to optimally solve complex searching problems with ease. …”
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Optimal placement and sizing of FACTS devices for optimal power flow using metaheuristic optimizers
Published 2022“…Thus, seven metaheuristic algorithms: Barnacles Mating Optimizer (BMO), Marine Predators Algorithm (MPA), Moth–Flame Optimization (MFO), Particle Swarm Optimization (PSO), Gravitational Search Algorithm (GSA), Teaching–Learning-Based Optimization (TLBO) and Heap-Based Optimizer (HBO) are used to solve two objective functions: power loss and cost minimizations. …”
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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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6
RMIL/AG: A new class of nonlinear conjugate gradient for training back propagation algorithm
Published 2018“…The efficiency of the proposed method is verified by means of simulation on four classification problems. The results show that the computational efficiency of the proposed method was better than the conventional BP algorithm.…”
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The effect of pre-processing techniques and optimal parameters on BPNN for data classification
Published 2015“…In this research, a performance analysis based on different activation functions; gradient descent and gradient descent with momentum, for training the BP algorithm with pre-processing techniques was executed. …”
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The classification of wink-based eeg signals by means of transfer learning models
Published 2021“…The implementation of pre-processing algorithms has been demonstrated to be able to mitigate the signal noises that arises from the winking signals without the need for the use signal filtering algorithms. …”
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10
Gravitational search – bat algorithm for solving single and bi-objective of non-linear functions
Published 2018“…The second technique is to solve bi-objective functions by using the BOBAT algorithm. The third technique is an integration of BOGSA with BOBAT to produce a BOGSBAT algorithm. …”
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A Hybrid of Ant Colony Optimization Algorithm and Simulated Annealing for Classification Rules
Published 2013“…Thus, this thesis proposed two variants of hybrid ACO with simulated annealing (SA) algorithm for solving problem of classification rule induction. …”
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Feature Selection using Binary Simulated Kalman Filter for Peak Classification of EEG Signals
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Protein Conformantional Search Using Bees Algorithm
Published 2008“…To this end, an energy function is used to calculate its energy and a conformational search algorithm is used to search the conformational search space to find the lowest free energy corformation.…”
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Optimization of modified Bouc–Wen model for magnetorheological damper using modified cuckoo search algorithm
Published 2021“…The newly proposed algorithm was tested using a set of standard benchmark functions with different searching space and global optima placement. …”
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Enhancing the cuckoo search with levy flight through population estimation
Published 2016“…The algorithm is tested on five benchmark functions such as Ackley function, Griewank function, Rastrigin function, Rosenbrock function and Schwefel function. …”
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Enhancing harmony search parameters based on step and linear function for bus driver scheduling and rostering problems
Published 2018“…Therefore,it is of great interest that we find adjustments for these parameters in this research.There are two contributions to this research.The first one is having HMCR parameter using step function and the linear increase function while the second is applying the fret spacing concept on guitars that is associated with mathematical formulae is also applied in the BW parameter.There are three proposed models on the alteration of HMCR parameters based on the use of the fundamental step function;namely,the constant interval of step function, and its dynamic increase and decrease interval functions.The experimental results revealed that our proposed approach is superior to other state of the art harmony searches either in specific or generic cases. …”
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Selection and optimization of peak features for event-related eeg signals classification / Asrul bin Adam
Published 2017“…At first, a peak classification algorithm is developed based on the general following processes including peak candidate identification, feature extraction, and classification. …”
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Assessing the symbiotic organism search variants using standard benchmark functions
Published 2019“…Symbiotic Organism Search (SOS) is one of the latest meta-heuristic algorithms created to solve optimization problems. …”
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Ringed seal search for global optimization via a sensitive search model / Younes Saadi
Published 2018“…The quality of the algorithm is comprehensively evaluated on various standard benchmark test functions using variety of quality metrics and using three baseline algorithms for comparison. …”
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Ant colony optimization for rule induction with simulated annealing for terms selection
Published 2012“…This paper proposes a sequential covering based algorithm that uses an ant colony optimization algorithm to directly extract classification rules from the data set.The proposed algorithm uses a Simulated Annealing algorithm to optimize terms selection, while growing a rule.The proposed algorithm minimizes the problem of a low quality discovered rule by an ant in a colony, where the rule discovered by an ant is not the best quality rule, by optimizing the terms selection in rule construction. …”
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