A Modified Cuckoo Optimization Algorithm for Engineering Optimization

Kahramanlı, Humar

doi:10.7763/ijfcc.2012.v1.52

Cited by 32 publications

(12 citation statements)

References 7 publications

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“…A ω of π/6 is supposed to be enough for good convergence. Kahramanli [27] presented a modified COA that yielded better solutions to engineering problems. In the modified COA, a new ELR equation was proposed.…”

Section: Number Of Current Cuckoo S Eggs Total Number Of Eggsmentioning

confidence: 99%

Predicting Student Academic Performance: A Comparison of Two Meta-Heuristic Algorithms Inspired by Cuckoo Birds for Training Neural Networks

2014

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Predicting student academic performance with a high accuracy facilitates admission decisions and enhances educational services at educational institutions. This raises the need to propose a model that predicts student performance, based on the results of standardized exams, including university entrance exams, high school graduation exams, and other influential factors. In this study, an approach to the problem based on the artificial neural network (ANN) with the two meta-heuristic algorithms inspired by cuckoo birds and their lifestyle, namely, Cuckoo Search (CS) and Cuckoo Optimization Algorithm (COA) is proposed. In particular, we used previous exam results and other factors, such as the location of the student's high school and the student's gender as input variables, and predicted the student academic performance. The standard CS and standard COA were separately utilized to train the feed-forward network for prediction. The algorithms optimized the weights between layers and biases of the neuron network. The simulation results were then discussed and analyzed to investigate the prediction ability of the neural network trained by these two algorithms. The findings demonstrated that both CS and COA have potential in training ANN and ANN-COA obtained slightly better results for predicting student academic performance in this case. It is expected that this work may be used to support student admission procedures and strengthen the service system in educational institutions. OPEN ACCESSAlgorithms 2014, 7 539

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Section: Number Of Current Cuckoo S Eggs Total Number Of Eggsmentioning

confidence: 99%

Predicting Student Academic Performance: A Comparison of Two Meta-Heuristic Algorithms Inspired by Cuckoo Birds for Training Neural Networks

2014

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“…This applied to two constrained continuous optimization problems. The results indicate that the MCOA is a powerful optimization technique that may yield better solutions to engineering problems [7].…”

Section: Related Workmentioning

confidence: 99%

Genetic Cuckoo Optimization Algorithm (GCOA)

Rashad¹,

Keshk²,

El-Dosuky³

et al. 2014

IJCA

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In this paper, Optimization is considered as the main impact of insight problem and heuristic methods. A proposed method is represented by using two optimization algorithms; cuckoo optimization; is heuristic method and Genetic algorithm; is meta-heuristic method in order to increase the optimization level and speed of calculation as possible. The proposed methodology and technique still a subject for improvements and enhancements for increasing its speeding up more and more. The proposed method is applicable for many industrial fields, agricultural fields and other provided that having optimization problem; just reconfigure problem parameters and have good opportunity to optimize well the problem. General Terms

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“…After some immigration events, all cuckoo populations gather in the same habitat, that is, the area's best position [44]. However, the performance of the CSA is affected by algorithm-dependent control parameters, such as egg laying radius [45].…”

Section: Cuckoo Search Algorithm (Csa)mentioning

confidence: 99%