scholarly journals Cuckoo search optimization for linear antenna arrays synthesis

2013 ◽  
Vol 10 (3) ◽  
pp. 371-380 ◽  
Author(s):  
Haffane Ahmed ◽  
Hasni Abdelhafid
Keyword(s):  
Antenna Arrays ◽  
Search Algorithm ◽  
Cuckoo Search ◽  
Microstrip Antennas ◽  
Cuckoo Search Algorithm ◽  
Breeding Strategy ◽  
Pattern Synthesis ◽  
Flight Behaviour ◽  
Search Optimization ◽  
Cuckoo Search Optimization

A recently developed metaheuristic optimization algorithm, the Cuckoo search algorithm, is used in this paper for the synthesis of symmetric uniformly spaced linear microstrip antennas array. Cuckoo search is based on the breeding strategy of Cuckoos augmented by a Levy flight behaviour found in the foraging habits of other species. This metaheuristic is tested on amplitude only pattern synthesis and amplitude and phase pattern synthesis. In both case, the objective, is to determinate the optimal excitations element that produce a synthesized radiation pattern within given bounds specified by a pattern mask.

Optimized Model for Cervical Cancer Detection Using Binary Cuckoo Search

2019 ◽  
Vol 12 (4) ◽  
pp. 293-303 ◽  
Author(s):  
Rachna Jain ◽  
Saurabh Raj Sangwan ◽  
Shivam Bachhety ◽  
Surbhi Garg ◽  
Yash Upadhyay
Keyword(s):  
Cervical Cancer ◽  
Decision Tree ◽  
Search Algorithm ◽  
Cuckoo Search ◽  
Cuckoo Search Algorithm ◽  
Decision Tree Classifier ◽  
Search Optimization ◽  
Tree Classifier ◽  
Cuckoo Search Optimization ◽  
Causes Of Deaths

Background:Cervical Cancer is one of the leading causes of deaths among women in India. Accurate and early detection of cancer seems to be a fruitful approach in the diagnosis process. It will be a boon for the medical industry. Prediction of cervical cancer using all the features takes a lot of time and computational resources. Hence, reducing the features and taking only essential features into consideration is an effective solution.Objective:The aim of the research is to identify the relevant features in the classification of cancer and optimize the model. Feature selection increases the accuracy percentage of any classifier. The binary cuckoo search optimization algorithm was applied to explore the important features in the attribute list.Methods:In our research, the performance of the proposed framework has been verified via instigating it with base classifiers such as Random Forest, kernel SVM, Decision Tree and kNN and then evaluated the results with and without Binary Cuckoo Optimization (BCO). The proposed method involves cuckoo search algorithm for selection of optimal feature split points. Cuckoo Search Optimization is a nature stimulated and breeding process of the cuckoo bird’s algorithm to predict best global solution.Results:The results produced only selected features vital for prediction of cancer. In addition, its performance has been paralleled against other factors such as Accuracy, Precision, Recall and Specificity and F-measure.Conclusion:The experimental results show that Decision Tree classifier outperforms all other classifiers with an accuracy of 94.7% increased to 97% after Cuckoo Optimization.

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.

scholarly journals A MPPT strategy based on cuckoo search for wind energy conversion system

2018 ◽  
Vol 7 (4) ◽  
pp. 2298
Author(s):  
C Centhil Kumar ◽  
I Jacob Raglend
Keyword(s):  
Fuzzy Logic Controller ◽  
Search Algorithm ◽  
Control Strategies ◽  
Cuckoo Search ◽  
Voltage Regulation ◽  
Cuckoo Search Algorithm ◽  
Wind Energy Conversion ◽  
Search Optimization ◽  
Cuckoo Search Optimization ◽  
Doubly Fed

The WECS based Doubly Fed Induction Generator (DFIG) system is presented in this paper which includes different MPPT control strategies for a grid connected system. The GSC gives the flow of power from the rotor part of DFIG up to the grid and the modulation of DC voltage. Here the cuckoo search algorithm based on MPPT is designed, to obtain a higher power from the changing speed wind turbine. The algorithms such as Perturb and Observe (P&O), Proportional Integral (PI) control and Fuzzy Logic Controller (FLC) are compared and their performances are evaluated. To design and develop the cuckoo search optimization based on MPPT for WECS, and to obtain optimum voltage regulation and power, thus improving the working performance, reducing the domain time and minimizing the performance indices. To simulate the different MPPT control methods, MATLAB/Simulink environment is used here. 

scholarly journals Current Control Optimization for Grid-tied Inverters Using Cuckoo Search Algorithm

2020 ◽  
Author(s):  
João Faria ◽  
José Pombo ◽  
Maria Do Rosário Calado ◽  
Sílvio Mariano
Keyword(s):  
Search Algorithm ◽  
Cuckoo Search ◽  
Cuckoo Search Algorithm ◽  
Current Control ◽  
Stable Operation ◽  
Control Optimization ◽  
Search Optimization ◽  
Cuckoo Search Optimization ◽  
Optimal Gains ◽  
Ac Converters

One of the most decisive factors for a smooth and stable operation of an DC / AC converter connected to the power grid are the gains used in the current controllers. This paper proposes the use of the Cuckoo Search optimization algorithm via Lévy Flights to facilitate the determination of the optimal gains of the grid connected DC/ AC converters. With the proposed algorithm, it becomes possible to determine the optimal gains of the current controllers of the DC / AC converters connected with the grid thus improving their stability, accuracy and response time. Keywords: DC/AC converters, Cuckoo search, Optimization, Current controllers

Performances of Adaptive Cuckoo Search Algorithm in Engineering Optimization

2016 ◽  
pp. 676-699 ◽  
Author(s):  
Pauline Ong ◽  
S. Kohshelan
Keyword(s):  
Search Algorithm ◽  
Cuckoo Search ◽  
Cuckoo Search Algorithm ◽  
Breeding Strategy ◽  
Function Optimization ◽  
Engineering Optimization ◽  
Optimal Solutions ◽  
Step Size ◽  
Swarm Optimization ◽  
Searching Strategy

A new optimization algorithm, specifically, the cuckoo search algorithm (CSA), which inspired by the unique breeding strategy of cuckoos, has been developed recently. Preliminary studies demonstrated the comparative performances of the CSA as opposed to genetic algorithm and particle swarm optimization, however, with the competitive advantage of employing fewer control parameters. Given enough computation, the CSA is guaranteed to converge to the optimal solutions, albeit the search process associated to the random-walk behavior might be time-consuming. Moreover, the drawback from the fixed step size searching strategy in the inner computation of CSA still remain unsolved. The adaptive cuckoo search algorithm (ACSA), with the effort in the aspect of integrating an adaptive search strategy, was attached in this study. Its beneficial potential are analyzed in the benchmark test function optimization, as well as engineering optimization problem. Results showed that the proposed ACSA improved over the classical CSA.

A Survey of the Cuckoo Search and Its Applications in Real-World Optimization Problems

2017 ◽  
pp. 541-555 ◽  
Author(s):  
Christopher Expósito-Izquierdo ◽  
Airam Expósito-Márquez
Keyword(s):  
Optimization Problems ◽  
Search Algorithm ◽  
Cuckoo Search ◽  
Search Space ◽  
Population Based ◽  
Cuckoo Search Algorithm ◽  
Breeding Strategy ◽  
Egg Laying ◽  
Practical Applications ◽  
Wide Range

The chapter at hand seeks to provide a general survey of the Cuckoo Search Algorithm and its most highlighted variants. The Cuckoo Search Algorithm is a relatively recent nature-inspired population-based meta-heuristic algorithm that is based upon the lifestyle, egg laying, and breeding strategy of some species of cuckoos. In this case, the Lévy flight is used to move the cuckoos within the search space of the optimization problem to solve and obtain a suitable balance between diversification and intensification. As discussed in this chapter, the Cuckoo Search Algorithm has been successfully applied to a wide range of heterogeneous optimization problems found in practical applications over the last few years. Some of the reasons of its relevance are the reduced number of parameters to configure and its ease of implementation.

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