A novel hybrid deep learning method with cuckoo search algorithm for classification of arrhythmia disease using ECG signals

2021 ◽  
Author(s):  
Pooja Sharma ◽  
Shail Kumar Dinkar ◽  
D. V. Gupta
Keyword(s):  
Deep Learning ◽  
Search Algorithm ◽  
Cuckoo Search ◽  
Cuckoo Search Algorithm ◽  
Learning Method ◽  
Ecg Signals

Reliability Optimization of Complex Systems Using Cuckoo Search Algorithm

2017 ◽  
pp. 94-110 ◽  
Author(s):  
Anuj Kumar ◽  
Sangeeta Pant ◽  
S. B. Singh
Keyword(s):  
Complex Systems ◽  
Life Support ◽  
Optimization Problems ◽  
Search Algorithm ◽  
Cuckoo Search ◽  
Cuckoo Search Algorithm ◽  
Reliability Optimization ◽  
Space Capsule ◽  
Metaheuristic Techniques

In this chapter, authors briefly discussed about the classification of reliability optimization problems and their nature. Background of reliability and optimization has also been provided separately so that one can clearly understand the basic terminology used in the field of reliability optimization. Classification of various optimization techniques have also been discussed by the authors. Few metaheuristic techniques related to reliability optimization problems like Genetic Algorithm (GA), Ant Colony Optimization (ACO) and Particle Swarm Optimization (PSO) have been discussed in brief. Thereafter, authors have discussed about Cuckoo Search Algorithm (CSA) which is the main focus of this chapter. Finally, Cuckoo Search Algorithm has been applied for solving reliability optimization problems of two complex systems namely complex bridge system and life support system in space capsule. Simulation results and conclusion have been presented in the last followed by the references.

Cuckoo Search Based Forest Cover Classification

2019 ◽  
Vol 16 (8) ◽  
pp. 3550-3553
Author(s):  
A. Shanthasheela ◽  
P. Shanmugavadivu
Keyword(s):  
Forest Cover ◽  
Search Algorithm ◽  
Research Work ◽  
Cuckoo Search ◽  
Cuckoo Search Algorithm ◽  
Search Optimization ◽  
Cuckoo Search Optimization ◽  
Nature Inspired Algorithms ◽  
Feasible Solutions

Cuckoo Search optimization is one of the nature-inspired algorithms being widely experimented and explored to offer optimal and feasible solutions for science and engineering problems. It is inspired by the brood parasitism of cuckoo species laying their eggs in the other host birds’ nests. This research work is designed on the principle of the Cuckoo Search algorithm for the classification of forest cover in the satellite images. The proposed method titled, Cuckoo Search Based Classification (CSBC) is confirmed to have efficiently classified the forest cover with accuracy of 95 percent and above. The results of this classification method are used to measure the land cover change, deforest cover change and to prepare forest maps.

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