Effective Classification of Lung Cancer Using Hybrid Neuro Fuzzy Binary Cuckoo Search Algorithm

2020 ◽  
Vol 12 (SP4) ◽  
pp. 73-84
Author(s):  
Vasanthi K.
Keyword(s):  
Lung Cancer ◽  
Search Algorithm ◽  
Cuckoo Search ◽  
Cuckoo Search Algorithm ◽  
Neuro Fuzzy

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.

Optimal broadcast scheduling method for VANETs: An adaptive discrete firefly approach

2020 ◽  
Vol 39 (6) ◽  
pp. 8125-8137
Author(s):  
Jackson J Christy ◽  
D Rekha ◽  
V Vijayakumar ◽  
Glaucio H.S. Carvalho
Keyword(s):  
Intelligent Transportation System ◽  
Search Algorithm ◽  
Mac Protocol ◽  
High Mobility ◽  
Optimal Solution ◽  
Cuckoo Search ◽  
Cuckoo Search Algorithm ◽  
Traffic Density ◽  
Scheduling Problem ◽  
Broadcast Scheduling

Vehicular Adhoc Networks (VANET) are thought-about as a mainstay in Intelligent Transportation System (ITS). For an efficient vehicular Adhoc network, broadcasting i.e. sharing a safety related message across all vehicles and infrastructure throughout the network is pivotal. Hence an efficient TDMA based MAC protocol for VANETs would serve the purpose of broadcast scheduling. At the same time, high mobility, influential traffic density, and an altering network topology makes it strenuous to form an efficient broadcast schedule. In this paper an evolutionary approach has been chosen to solve the broadcast scheduling problem in VANETs. The paper focusses on identifying an optimal solution with minimal TDMA frames and increased transmissions. These two parameters are the converging factor for the evolutionary algorithms employed. The proposed approach uses an Adaptive Discrete Firefly Algorithm (ADFA) for solving the Broadcast Scheduling Problem (BSP). The results are compared with traditional evolutionary approaches such as Genetic Algorithm and Cuckoo search algorithm. A mathematical analysis to find the probability of achieving a time slot is done using Markov Chain analysis.

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