Cuckoo Species Research Articles

Cuckoo Search Algorithm for Optimal Placement and Sizing of Static Var Compensator in Large-Scale Power Systems

Abstract This paper presents an application of Cuckoo search algorithm to determine optimal location and sizing of Static VAR Compensator. Cuckoo search algorithm is a modern heuristic technique basing Cuckoo species’ parasitic strategy. The Lévy flight has been employed to generate random Cuckoo eggs. Moreover, the objective function is a multiobjective problem, which minimizes loss power, voltage deviation and investment cost of Static VAR Compensator while satisfying other operating constraints in power system. Cuckoo search algorithm is evaluated on three case studies and compared with the Teaching-learning-based optimization, Particle Swarm optimization and Improved Harmony search algorithm. The results show that Cuckoo search algorithm is better than other optimization techniques and its performance is also better.

A novel method based on adaptive cuckoo search for optimal network reconfiguration and distributed generation allocation in distribution network

Abstract This paper proposes a new methodology to optimize network topology and placement of distributed generation (DG) in distribution network with an objective of reduction real power loss and voltage stability enhancement. A meta-heuristic cuckoo search algorithm (CSA) inspired from the obligate brood parasitism of some cuckoo species which lay their eggs in the nests of other birds of other species for solving optimization problems is adapted to simultaneously reconfigure and identify the optimal location and size of DG units in a distribution network. The graph theory is used to determine the search space which reduces infeasible network configurations of reconfiguration process and check the radial constraint of each configuration of distribution network. The effectiveness of the proposed method has been validated on three different distribution network systems at seven different scenarios. The obtained results show well the effectiveness and performance of the proposed method in distribution network reconfiguration with optimal location and size of DG problems.

Cuckoo Search Algorithm for Minimization of Power Loss and Voltage Deviation

This paper proposes a cuckoo search algorithm (CSA) to solve the optimal reactive power dispatch (ORPD) problem in power system operation considering the power loss and voltage deviation. The proposed CSA is a nature inspired algorithm from the cuckoo species laying their eggs in the nest of other species. There is a probability of the host bird to discover the alien eggs in its nest and the host bird either destroys the strange egg or simply ignores the host and builds a new one. The advantages of the CSA method are few control parameters and high optimal solution quality. The proposed method has been tested on the IEEE 30 bus system and the result comparison has indicated that the proposed method can obtain better solution quality than many other methods. Therefore, the proposed CSA method can be an alternative method for solving the ORPD problem.

Chemical defence in avian brood parasites: production and function of repulsive secretions in common cuckoo chicks

The use of active chemical defence against predators is relatively rare in birds. Among others, it has been reported for some members of family Cuculidae whose chicks, when threatened, expel dark foul‐smelling liquid from their cloaca. Apart from the brood parasitic great spotted cuckoo Clamator glandarius, however, this phenomenon has not yet been systematically studied in any other cuckoo species. Here we investigated the repellent behaviour in the evicting brood parasite, the common cuckoo Cuculus canorus, parasitizing the great reed warbler Acrocephalus arundinaceus. We explored whether production of secretions varies with chick age or size, and tested its presumed repellent function against various types of predators. We found that the production of secretions commenced at the age of approximately eight days, then gradually increased and decreased again shortly before fledging. Furthermore, we experimentally confirmed a more intensive repellent effect of the secretions on mammal predators than on avian predators, such as raptors and owls. The secretions have, however, no effect on corvid predators, probably because these scavengers often consume malodorous food. Further experimental studies together with phylogenetic comparative analyses are needed to elucidate the origin and function of this intriguing phenomenon both in parasitic and non‐parasitic cuckoos.

Complete mitochondrial genome and the phylogenetic position of the Lesser Cuckoo, Cuculus poliocephalus (Aves: Cuculiformes)

The complete mitochondrial genome of the Lesser Cuckoo Cuculus poliocephalus was determined using next-generation sequencing. Phylogenetic analyses with 20 cuckoo species and six genes (12S, ATP6, CYTb, ND2, ND3, and ND6) strongly verified the identity of our sample as grouping with C. poliocephalus, which was sister to a clade of other Cuculus spp., including C. canorus, C. micropterus, and C. saturatus. The mitogenomic length of C. poliocephalus was 17 508 bp, including 13 protein-coding genes, 22 transfer RNA genes, two ribosomal RNA genes, one control region with 48 bp unit tandem repeats close to 3′ end, and one short pseudo-control region with 33 tandem repeats of CAACAAA. An extra nucleotide (T) was identified at position 174 of ND3. The mitogenome of C. poliocephalus will contribute to studies of mitogenomic evolution, the phylogenetic relationship of cuckoos, and the co-evolutionary pattern between brood parasitic birds and their hosts.

Visual tracking method based on cuckoo search algorithm

Cuckoo search (CS) is a new meta-heuristic optimization algorithm that is based on the obligate brood parasitic behavior of some cuckoo species in combination with the Lévy flight behavior of some birds and fruit flies. It has been found to be efficient in solving global optimization problems. An application of CS is presented to solve the visual tracking problem. The relationship between optimization and visual tracking is comparatively studied and the parameters’ sensitivity and adjustment of CS in the tracking system are experimentally studied. To demonstrate the tracking ability of a CS-based tracker, a comparative study of tracking accuracy and speed of the CS-based tracker with six “state-of-art” trackers, namely, particle filter, meanshift, PSO, ensemble tracker, fragments tracker, and compressive tracker are presented. Comparative results show that the CS-based tracker outperforms the other trackers.

Cuckoo search with varied scaling factor

Cuckoo search (CS), inspired by the obligate brood parasitic behavior of some cuckoo species, iteratively uses Levy flights random walk (LFRW) and biased/selective random walk (BSRW) to search for new solutions. In this study, we seek a simple strategy to set the scaling factor in LFRW, which can vary the scaling factor to achieve better performance. However, choosing the best scaling factor for each problem is intractable. Thus, we propose a varied scaling factor (VSF) strategy that samples a value from the range [0,1] uniformly at random for each iteration. In addition, we integrate the VSF strategy into several advanced CS variants. Extensive experiments are conducted on three groups of benchmark functions including 18 common test functions, 25 functions proposed in CEC 2005, and 28 functions introduced in CEC 2013. Experimental results demonstrate the effectiveness of the VSF strategy.

Dual parasitism of Fork-tailed Drongos by African and Jacobin Cuckoos

Different species of brood parasitic birds, which lay their eggs in the nests of host foster-parents, rarely target the same host species population. We report brood parasitism of Fork-tailed Drongos Dicrurus adsimilis in the southern Kalahari Desert by both African Cuckoo Cuculus gularis and Jacobin Cuckoo Clamator jacobinus serratus. Drongos are the only known host for the African Cuckoo, and were more frequently parasitised by this species (21.8% nests). Nevertheless, parasitism rates suggest that in the Kalahari, drongos are also an important host for Jacobin Cuckoo (4.6% nests). Jacobin Cuckoos likely compete with African Cuckoos for drongo hosts, as exemplified by the occurrence of both African and Jacobin Cuckoo eggs in the same drongo clutch. The drongo's defensive adaptations to parasitism by African Cuckoos, including egg rejection, may also curtail parasitism by Jacobin Cuckoos. The extent of competition between these cuckoo species and whether they possess adaptations to prevent one another's access to drongo hosts remains to be explored.

Butterflies that trick ants with sound

Larvae of parasitic Maculinea butterflies use acoustic mimicry to induce host ants to adopt and care for them.

New feather mites of the genera Aniacarus and Aniibius (Acariformes:Pterolichidae) from two cuckoo species (Cuculiformes: Cuculidae) in Brazil.

Five new species of the family Pterolichidae are described from two common non-parasitic cuckoo species of the subfamily Crotophaginae (Cuculiformes: Cuculidae) in Brazil: Aniacarus ani sp. n. from the Smooth-billed Ani, Crotophaga ani Linnaeus, A. simplex sp. n., A. robustus sp. n., A. coronatus sp. n. and Aniibius guirae sp. n. from the Guira Cuckoo, Guira guira (Gmelin). A key to all known species of Aniacarus is provided. All four pterolichid species associated with the G. guira can occur simultaneously on one host individual. A brief review of studies of feather mites associated with Cuculidae is given.

Contrasting genetic structure in cuckoo and predatory Maculinea butterflies

In Europe, both Maculinea alcon and M. teleius frequently co-occur inhabiting humid meadows. Although their parasitic life cycle is similar, ecological differences have been demonstrated between them: (i) spatial distribution of their eggs is different, and (ii) M. alcon is a cuckoo species, while M. teleius is predatory. The aim of the present study is to identify the genetic consequences of the ecological differences between these two butterfly species. To do so, we studied the genetic structure in samples from 9 M. alcon and 16 M. teleius sites obtained from the Carpathian Basin using 16 polymorphic enzyme markers. Both species exhibited relatively low enzyme polymorphism compared to other lycaenid species. Nevertheless, all measures of variation were significantly higher in M. teleius than in M. alcon. Genetic differentiation, however, was generally higher among M. alcon populations as compared to M. teleius. Moreover, the results of Bayesian clustering indicated a clear regional pattern with three well-defined cluster regions in M. alcon. In contrast, the regional pattern was less evident in M. teleius where we found three comparatively less distinct cluster regions. Putatively adaptive genetic differences were detected among cluster regions exploiting different host ants in M. alcon, while they were less evident in M. teleius. These results conform to our predictions on the differences between the utilization of their host ants. Since the pattern of genetic differentiation is different in the two Maculinea species, conservation strategies need also to differ in their cases.

A Study from the Perspective of Nature-Inspired Metaheuristic Optimization Algorithms

are various metaheuristic algorithms which can be used to solve optimization problems efficiently. Among these algorithms, nature-inspired optimization algorithms are attractive because of their better results. In this paper, four types of metaheuristic algorithms such as ant colony optimization algorithm, firefly algorithm, bat algorithm and cuckoo search algorithms were used as the basis for comparison. Ant colony optimization algorithm is based on the interactions between social insect, ants. Firefly algorithm is influenced by the flashing behavior of swarming firefly. Cuckoo search uses brooding parasitism of cuckoo species and bat algorithm is inspired by the echolocation of foraging bats. Keywordsant colony optimization algorithm, firefly algorithm, bat algorithm, cuckoo search algorithm.

A Novel Order Reduction Method Using Cuckoo Search Algorithm

ABSTRACTIn this paper, a novel method is presented to obtain stable reduced-order model of higher order linear time invariant continuous systems using optimization technique. In order to perform optimization, a new meta-heuristic search algorithm, called Cuckoo Search (CS) is applied which is inspired by the natural behaviour of cuckoo species including the Lévy flight behaviour of some birds and fruit flies. The effectiveness of the proposed method is supported by some numerical examples of single input single output (SISO) systems and the results are compared with other well-known methods available in the literature in terms of most popular performance indices like integral square error, integral absolute error, and integral time absolute error. The method is extended for multi input multi output (MIMO) systems also.

Task Scheduling in the Cloud Computing Based on the Cuckoo Search Algorithm

Cloud computing is the latest emerging trend in distributed computing, where shared resources are provided to end-users in an on demand fashion that brings many advantjuages, including data ubiquity, flexibility of access, high availability of resources, and flexibility. The task scheduling problem in Cloud computing is an NP-hard problem. Therefore, many heuristics have been proposed, from low level execution of tasks in multiple processors to high level execution of tasks. In this paper, a new evolutionary algorithm is proposed which named CSA to schedule the tasks in Cloud computing. CSA algorithm is based on the obligate brood parasitic behavior of some cuckoo species in combination with the Levy flight behavior of some birds and fruit flies. The simulation results demonstrated that when the value of Pa is low, the speed and coverage of the algorithm become very high.

Distribution network reconfiguration for power loss minimization and voltage profile improvement using cuckoo search algorithm

Abstract This paper proposes a reconfiguration methodology based on a cuckoo search algorithm (CSA) for minimizing active power loss and the maximizing voltage magnitude. The CSA method is a new meta-heuristic algorithm inspired from the obligate brood parasitism of some cuckoo species which lay their eggs in the nests of other host birds of other species for solving optimization problems. Compared to other methods, CSA method has fewer control parameters and is more effective in optimization problems. The effectiveness of the proposed CSA has been tested on three different distribution network systems and the obtained test results have been compared to those from other methods in the literature. The simulation results show that the proposed CSA can be an efficient and promising method for distribution network reconfiguration problems.

Cuckoo Search Algorithm with Chaotic Maps

Cuckoo search algorithm is a novel nature-inspired optimization technique based on the obligate brood parasitic behavior of some cuckoo species. It iteratively employs Lévy flights random walk with a scaling factor and biased/selective random walk with a fraction probability. Unfortunately, these two parameters are used in constant value schema, resulting in a problem sensitive to solution quality and convergence speed. In this paper, we proposed a variable value schema cuckoo search algorithm with chaotic maps, called CCS. In CCS, chaotic maps are utilized to, respectively, define the scaling factor and the fraction probability to enhance the solution quality and convergence speed. Extensive experiments with different chaotic maps demonstrate the improvement in efficiency and effectiveness.

Optimal Tuning of Multimachine Power System Stabilizer using Cuckoo Search Algorithm

In this paper, optimal multiobjective design of robust multimachine Power System Stabilizers (PSS) using Cuckoo Search (CS) optimization algorithm is presented for small-signal stability enhancement. This algorithm is based on the obligate brood parasitic behaviour of some cuckoo species in combination with Lévy flight behaviour of some birds and fruit flies. A conventional speed-based lead-lag PSS is used in this work. The parameters of the Cuckoo Search based Power System Stabilizer (CSPSS) are optimized simultaneously to shift the unstable or poorly damped electromechanical mode eigenvalues of all operating conditions to a D-shape zone in the left half of the s-plane. A multiobjective eigenvalue based objective function is designed to optimize a problem involving the damping factor and damping ratio of the electromechanical modes. To show the effectiveness and the robustness of CSPSS, time domain simulations, eigenvalue analysis and performance indices are presented and compared with Genetic Algorithm based PSSs (GAPSS) and Particle Swarm Optimization based PSO (PSOPSS) under wide range of operating conditions and severe disturbances. It is observed that CSPSS exhibits improved damping performance compare to GAPSS and PSOPSS.

Optimal design of FIR fractional order differentiator using cuckoo search algorithm

In this paper, a new meta-heuristic optimization algorithm, called cuckoo search algorithm (CSA) is applied to determine the optimal coefficients of the finite impulse response-fractional order differentiator (FIR-FOD) problem. CSA is based on lifestyle and unique parasitic behavior in egg laying and breeding of some cuckoo species along with Lévy flight behavior of some birds and fruit flies. The CSA is capable of solving linear and nonlinear optimization problems. The proposed CSA method prevents the local minima problem encountered in conventional FIR-FOD design method. A novel weighted least square (WLS) fitness function is adopted to improve the response of the FOD to a great extent. The proposed CSA based method has alleviated from inherent drawbacks of premature convergence and stagnation unlike genetic algorithm (GA). To verify the effectiveness of the proposed FIR-FOD based on the cuckoo search algorithm, different set of initial population is tested by simulation. Simulation results affirm that the proposed fractional order differentiator design approach using CSA outperforms the genetic algorithm in terms design accuracy (magnitude and phase error), fast convergence rate and optimal solution. The simulation results confirmed that the proposed FOD using CSA outperforms the FOD designed using evolutionary algorithm like GA and conventional FOD design methods such as radial basis function (RBF) interpolation method and DCT interpolation method.

Hawk mimicry in cuckoos and anti‐parasitic aggressive behavior of barn swallows in Denmark and China

Hosts of brood parasites defend their nests against parasitism by aggression and subsequently, if parasitized, by rejection of the parasite egg or nestling. Cuckoos have evolved plumage mimicry with convergence towards the phenotype of Accipiter hawks that are common predators of cuckoo hosts. Here we tested two alternative hypotheses 1) whether barn swallows Hirundo rustica have evolved less aggressive behavior towards cuckoos in areas of sympatry with more abundant Accipiter hawks; and 2) whether barn swallows have evolved more aggressive anti‐parasite behavior in areas with a single species of cuckoo. We presented dummies of common cuckoo Cuculus canorus, sparrowhawk Accipiter nisus and Oriental turtledove Streptopelia orientalis (a benign control) at the nests of barn swallows during breeding, while recording intensity of response and proximity of barn swallows to the dummy. We demonstrated that cuckoos moved away when attacked aggressively and approached more closely by barn swallows showing that barn swallow behavior was efficient at driving away cuckoos. Barn swallows were significantly more aggressive and approached cuckoo and sparrowhawk dummies more closely in Denmark than in China, despite sparrowhawks being relatively more common in Denmark. Responses towards cuckoo dummies differed from responses towards sparrowhawk dummies, showing that barn swallows distinguished between the two different causes of danger. These findings are inconsistent with a less aggressive response towards cuckoo dummies in areas of sympatry with more abundant Accipiter hawks, but consistent with the alternative hypothesis that barn swallows have evolved more aggressive behavior towards cuckoos in areas with a single species of brood parasite, but not in areas with multiple species of parasites, where it is harder for hosts to tell the difference.

Economic Emission Load Dispatch with Multiple Fuel Options Using Cuckoo Search Algorithm with Gaussian and Cauchy Distributions

Cuckoo Search Algorithm (CSA), a new meta-heuristic algorithm based on natural phenomenon of Cuckoo species and Levy flights random walk, has been successfully applied to several optimization problems so far. In the paper two modified versions of CSA, where new solutions are generated using two distributions including Gaussian and Cauchy distributions are proposed for economic emission load dispatch (EELD) problem with multiple fuel options. The advantages of CSA with Gaussian distribution (CSA-Gauss) and CSA with Cauchy distribution (CSA-Cauchy) over CSA with Levy distribution are fewer parameters and fewer equations and shorter computational process. The proposed method is tested on one test system consisting of ten generating units with various load demands and compared to other methods. In addition, the best compromise from the set of obtained solutions is found and compared to this from lamda-iteration (LI) method and Hopfield Lagrange Network (HLN). The result comparisons have indicated that the proposed method is a highly effective method.