Bird Mating Research Articles

Bird mating optimizer for structural damage detection using a hybrid objective function

Abstract A structural damage detection approach based on bird mating optimizer (BMO) in time-frequency domain is proposed in this paper. A hybrid objective function is introduced by minimizing the discrepancies between the measured and calculated natural frequencies and correlation function vector of acceleration of damaged and intact structures. Then the BMO algorithm with a disturbance procedure is developed to solve the objective function. Benefited from the hybrid objective function, only a few number of natural frequencies are needed in the detection process. And the disturbance procedure designed in this paper can enhance the precision of identification. The efficiency and robustness of the proposed method are verified by a planar truss and a frame, a three connected shear buildings and an experimental work. The studies in numerical simulations validate that the proposed objective function and disturbance procedure are helpful to improve the precision of identification. The experimental work shows that the proposed method has the potential of practical application. In addition, comparison among the proposed method and other optimization algorithms, i.e. GA, ABC, L-SHADE and HCLPSO, reveals the superiority of the proposed method in structural damage detection.

Parameters extraction of solar cell models using a modified simplified swarm optimization algorithm

The parameters of solar cells models have an effect on the simulation of solar cells and can be applied to monitor the working condition and diagnose potential faults for photovoltaic (PV) modules in a PV system. To accurately and efficiently extract the optimal parameters of solar cells in a limited CPU run time, a modified simplified swarm optimization (MSSO) algorithm is presented for the single diode and double diode models by minimizing the least square error between the calculated and experimental data. In MSSO, a new one-variable-update mechanism and survival-of-the-fittest policy are applied to enhance the ability of traditional SSO. To investigate the performance of MSSO, comparative studies with other well-known optimization algorithms, i.e., SSO, artificial bee colony (ABC) and simplified bird mating optimizer (SBMO), are presented, and extensive computational results are shown. The statistical data indicate that the MSSO method has the best performance among these methods in terms of efficiency, robustness and accuracy. Moreover, the current vs. voltage characteristics of the parameters extracted by MSSO coincide well with those of experimental data.

Multi-objective optimization of electrochemical discharge machining processes: a posteriori approach based on bird mating optimizer

In the modern manufacturing scenario, efforts are continuously being made to improve the performance of advanced machining processes. Electrochemical discharge machining (ECDM) is a hybrid non-traditional machining (NTM) process, which makes use of the combined advantages of two single-action NTM processes, i.e. electrical discharge machining and electrochemical machining. As a result, the performance characteristics of ECDM process are considerably different from those of the two single-phase processes with respect to productivity, accuracy and surface quality. Selection of the optimal process parameters is always crucial towards fully utilizing the benefits of ECDM process. In this paper, an a posteriori approach based on the novel bird mating optimizer (BMO) is applied for multi-objective optimization of ECDM responses. In this approach, the complete spectrum of non-dominated Pareto optimal solutions, from which the process engineers can easily choose the desired parametric setting depending on the application domain, is developed. It is much more useful from a practical standpoint than a priori approaches reported in the literature. The BMO is also used to predict the overall trends of the multi-parameter dependent responses, without the need of holding any of the process parameters constant during analysis.

Experimental evidence that brighter males sire more extra-pair young in tree swallows.

Across taxa, extra-pair mating is widespread among socially monogamous species, but few studies have identified male ornamental traits associated with extra-pair mating success, and even fewer studies have experimentally manipulated male traits to determine whether they are related directly to paternity. As a consequence, there is little experimental evidence to support the widespread hypothesis that females choose more ornamented males as extra-pair mates. Here, we conducted an experimental study of the relationship between male plumage colour and fertilization success in tree swallows (Tachycineta bicolor), which have one of the highest levels of extra-pair mating in birds. In this study, we experimentally dulled the bright blue plumage on the back of males (with nontoxic ink markers) early in the breeding season prior to most mating. Compared with control males, dulled males sired fewer extra-pair young, and, as a result, fewer young overall. Among untreated males, brighter blue males also sired more extra-pair young, and in paired comparisons, extra-pair sires had brighter blue plumage than the within-pair male they cuckolded. These results, together with previous work on tree swallows, suggest that extra-pair mating behaviour is driven by benefits to both males and females.

Genetics of bird mating systems

Evolution Elaborate courtship behaviors are no rarity in birds, but some species even have differently colored types of males and females—or morphs—with different reproductive strategies. In a Perspective, Taylor and Campagna discuss recent studies that shed light on how these morphs evolved.

EVOLUTION. Avian supergenes.

Genetic data reveal how two complex bird mating systems evolved

A Population Classification Evolution Algorithm for the Parameter Extraction of Solar Cell Models

To quickly and precisely extract the parameters for solar cell models, inspired by simplified bird mating optimizer (SBMO), a new optimization technology referred to as population classification evolution (PCE) is proposed. PCE divides the population into two groups, elite and ordinary, to reach a better compromise between exploitation and exploration. For the evolution of elite individuals, we adopt the idea of parthenogenesis in nature to afford a fast exploitation. For the evolution of ordinary individuals, we adopt an effective differential evolution strategy and a random movement of small probability is added to strengthen the ability to jump out of a local optimum, which affords a fast exploration. The proposed PCE is first estimated on 13 classic benchmark functions. The experimental results demonstrate that PCE yields the best results on 11 functions by comparing it with six evolutional algorithms. Then, PCE is applied to extract the parameters for solar cell models, that is, the single diode and the double diode. The experimental analyses demonstrate that the proposed PCE is superior when comparing it with other optimization algorithms for parameter identification. Moreover, PCE is tested using three different sources of data with good accuracy.

Spatial Isolation and Temporal Variation in Fitness and Condition Facilitate Divergence in a Migratory Divide.

A novel migratory polymorphism evolved within the last 60 years in blackcaps (Sylvia atricapilla) breeding sympatrically in southwestern Germany. While most individuals winter in the traditional areas in the Mediterranean, a growing number of blackcaps started migrating to Britain instead. The rapid microevolution of this new strategy has been attributed to assortative mating and better physical condition of birds wintering in Britain. However, the isolating barriers as well as the physical condition of birds are not well known. In our study, we examined whether spatial isolation occurred among individuals with distinct migratory behaviour and birds with different arrival dates also differed in physical and genetic condition. We caught blackcaps in six consecutive years upon arrival on the breeding grounds and assigned them via stable isotope analysis to their wintering areas. Analysis of the vegetation structure within blackcap territories revealed different microhabitat preferences of birds migrating to distinct wintering areas. Blackcaps arriving early on the breeding grounds had higher survival rates, better body condition and higher multilocus heterozygosities than later arriving birds. We did however not find an effect of parasite infection status on arrival time. Our results suggest that early arriving birds have disproportionate effects on population dynamics. Allochrony and habitat isolation may thus act together to facilitate ongoing divergence in hybrid zones, and migratory divides in particular.

Increased extra-pair paternity in broods of aging males and enhanced recruitment of extra-pair young in a migratory bird.

Despite keen interest in extra-pair mating in birds, its adaptive significance remains unresolved. Here, we use a multi-year dataset to test whether traits of a female's social mate influence her propensity to produce extra-pair offspring in a population of house wrens, and whether producing extra-pair young has consequences for a female's fitness through effects on offspring survival. Females were most likely to produce extra-pair offspring when paired with old males and when paired with males on poor-quality territories, although this latter effect was marginally nonsignificant. Among offspring, the cutaneous immunity of within-pair young decreased as the age of their sires increased, but cutaneous immunity of extra-pair young was not affected by the age of their extra-pair sires or by the age of the males rearing them. Extra-pair offspring were more likely than within-pair offspring to return as breeding adults to the local population, with extra-pair sons being more likely to return as a breeder for multiple years. Our findings support the hypothesis that females produce extra-pair offspring to enhance their inclusive fitness beyond what they are capable of given the male with which they are socially paired.

A hybrid bird mating optimizer algorithm with teaching-learning-based optimization for global numerical optimization

Bird Mating Optimizer (BMO) is a novel meta-heuristic optimization algorithm inspired by intelligent mating behavior of birds. However, it is still insufficient in convergence of speed and quality of solution. To overcome these drawbacks, this paper proposes a hybrid algorithm (TLBMO), which is established by combining the advantages of Teaching-learning-based optimization (TLBO) and Bird Mating Optimizer (BMO). The performance of TLBMO is evaluated on 23 benchmark functions, and compared with seven state-of-the-art approaches, namely BMO, TLBO, Artificial Bee Bolony (ABC), Particle Swarm Optimization (PSO), Fast Evolution Programming (FEP), Differential Evolution (DE), Group Search Optimization (GSO). Experimental results indicate that the proposed method performs better than other existing algorithms for global numerical optimization.

A hybrid bird mating optimizer algorithm with teaching-learning-based optimization for global numerical optimization

A hybrid bird mating optimizer algorithm with teaching-learning-based optimization for global numerical optimization

Stanje estetike danas

In this paper I argue for the possibility of expanding the field of aesthetics not only beyond art and beauty but also beyond everyday aesthetics (or prosaics) centered in human sensibility. This implies considering sensibility or aesthesis in all live beings to understand the vastness of bio-aesthetics. Part of this query is zoo-aesthetics. We have such growing evidence, enriched day by day, that animals are capable of creating, recreating, imitating, enjoying, exhibiting and expressing sensibility or aesthetic taste in various forms that it is harder to deny the more we record and witness their behavior. Moreover, as there are various artistic genres, we can equally speak of similar genres in zoo-poetics, namely: a) musical b) visual (both architectonic and decorative), c) drama, and d) dance. Are females enamored by the male bat or bird mating song? Do peahens feel pleasure at the sight of a male peacock's tail? As Nagel asked 'what is it like to be a bat?' I would really like to know what it is like to be a peahen. This full inquiry is being published in The indispensable excess of the aesthetics: evolution of sensibility in nature. (Lexington 2015).

Determination of photovoltaic modules parameters at different operating conditions using a novel bird mating optimizer approach

The main goal of this paper is to provide a framework to accurately estimate the electrical equivalent circuit parameters of photovoltaic arrays by use of an efficient heuristic technique. Owing to the non-linearity of the current vs. voltage (I–V) characteristics of PV modules, using a superior optimization technique helps to effectively find the real electrical parameters. Inspired by the mating process of different bird species, bird mating optimizer (BMO) is a new invented search technique which has shown superior performance for solving complex optimization problems. In this paper, the original BMO algorithm is simplified and used to estimate the electrical parameters of the module model for an amorphous silicon PV system at different operating conditions. The simplified BMO (SBMO) eliminates tedious efforts of parameter setting in original BMO and also modifies some rules. The usefulness of the proposed algorithm is investigated by comparing the obtained results with those found by two particle swarm optimization (PSO) variants, two harmony search (HS) variants as well as seeker optimization algorithm (SOA). Based on the investigated situations of this paper, SBMO yields more accurate results than the other studied methods.

Parameter estimation of fuel cell polarization curve using BMO algorithm

Polarization curves of proton exchange membrane fuel cells (PEMFCs) are affected by various parameters. The relative importance and effect of each parameter on the polarization curve is different. This paper studies estimation of parameters with the most influence on the electrochemical model. In order to evaluate the obtained results, the model accuracy is compared with that model in which all the parameters are estimated. Because PEMFCs parameter estimation is a complex optimization problem, a recently invented nature-inspired algorithm, bird mating optimizer (BMO), is proposed. For this aim, two real systems, the SR-12 Modular PEM Generator and the Ballard Mark V FC, are considered. The obtained results show that when the whole parameters are estimated, the accuracy of the model increases. Also, BMO algorithm yields better results than the other studied methods in terms of precision and robustness.

Bird mating optimizer: An optimization algorithm inspired by bird mating strategies

Thanks to their simplicity and flexibility, evolutionary algorithms (EAs) have attracted significant attention to tackle complex optimization problems. The underlying idea behind all EAs is the same and they differ only in technical details. In this paper, we propose a novel version of EAs, bird mating optimizer (BMO), for continuous optimization problems which is inspired by mating strategies of bird species during mating season. BMO imitates the behavior of bird species metaphorically to breed broods with superior genes for designing optimum searching techniques. On a large set of unimodal and multimodal benchmark functions, BMO represents a competitive performance to other EAs.

Alternation of clear-cut colour patterns inCorvuscrow evolution accords with learning-dependent social selection against unusual-looking conspecifics

Alternation of clear-cut colour patterns in<i>Corvus</i>crow evolution accords with learning-dependent social selection against unusual-looking conspecifics

Extraction of maximum power point in solar cells using bird mating optimizer-based parameters identification approach

Maximum power point of solar cells can be extracted by knowing the values of the electrical parameters. The validity of the obtained result depends on the accuracy of the model parameters. Hence, it is important to use a superior optimization technique to identify the optimal values of the parameters. Recently, a metaheuristic optimization algorithm, bird mating optimizer (BMO), has been devised which tries to metaphorically imitate the mating strategies of bird species. BMO employs several searching patterns to explore the region under consideration. This ability helps the algorithm to maintain the diversity and avoid premature convergence, and therefore, get close to the global solution. In this paper, the electrical parameters of a 57mm diameter commercial (RTC France) silicon solar cell are identified using BMO. The optimal parameters are then used to extract the maximum power point of the system. The accuracy of the proposed parameter identification approach is compared with the results found by the other optimization techniques. Simulation results accentuate the superior potential of BMO algorithm.

Artificial neural network training using a new efficient optimization algorithm

Because search space in artificial neural networks (ANNs) is high dimensional and multimodal which is usually polluted by noises and missing data, the process of weight training is a complex continuous optimization problem. This paper deals with the application of a recently invented metaheuristic optimization algorithm, bird mating optimizer (BMO), for training feed-forward ANNs. BMO is a population-based search method which tries to imitate the mating ways of bird species for designing optimum searching techniques. In order to study the usefulness of the proposed algorithm, BMO is applied to weight training of ANNs for solving three real-world classification problems, namely, Iris flower, Wisconsin breast cancer, and Pima Indian diabetes. The performance of BMO is compared with those of the other classifiers. Simulation results indicate the superior capability of BMO to tackle the problem of ANN weight training. BMO is also applied to model fuel cell system which has been addressed as an open and demanding problem in electrical engineering. The promising results verify the potential of BMO algorithm.

A new heuristic optimization algorithm for modeling of proton exchange membrane fuel cell: bird mating optimizer

SUMMARY As an open and demanding problem, accurate modeling of polarization curve in proton exchange membrane fuel cell has become the main issue of various researches. In recent years, because of their great potentials, metaheuristic optimization algorithms have represented good performances in identification of the unknown parameters of the proton exchange membrane fuel cell model, but there is the possibility to obtain more accurate results with more capable algorithms. In the literature, many heuristic optimization algorithms have been developed on the basis of natural phenomena. However, there are still some possibilities to devise new ones. In this paper, evolution of bird species has been regarded, and the intelligent behavior of birds during mating season has become an inspiration to devise a new heuristic optimization algorithm, named bird mating optimizer. Moreover, in this paper, the whole unknown parameters of the model, even dimensional parameters, are included in the identification process. The proposed algorithm is used to model the Ballard Mark V FC, and its performance is compared with those of the recently published paper by the authors. Simulation results reveal the superior performance of bird mating optimizer algorithm. Copyright © 2012 John Wiley & Sons, Ltd.

Inclusive fitness of ‘kissing cousins’: new evidence of a role for kin selection in the evolution of extra-pair mating in birds

Social monogamy is nearly ubiquitous across avian taxa,but evidence from a proliferation of studies utilizing molecular paternity analysis suggests that sexual monogamy is the rare exception rather than the rule (Griffith et al. 2002). Efforts to explain the prevalence of extra-pair paternity (EPP) have largely focused on the potential fitness benefits for offspring genetic quality, as females are less likely to benefit directly from seeking extra-pair mates. In particular, there has been considerable interest in the degree to which EPP may represent an adaptive female strategy to avoid inbreeding (or outbreeding)depression when paired with a highly related (or unrelated)social mate (Kempenaers 2007). Others have argued that, because relatives share many genes identical by descent,females might increase their own inclusive fitness by providing additional breeding opportunities to genetically related males (Waser et al. 1986; Kokko & Ots 2006). Thus, in the absence of significant inbreeding depression, pursuing EPP with relatives should be favoured by kin selection, although there exist few unambiguous empirical examples of such preferences in the literature. In this issue of Molecular Ecology, Wang &Lu (2011) present an analysis of mating patterns with respect to genetic relatedness of social and extra-pair partners in the ground tit (Parus humilis), a facultative cooperative breeder in which socially monogamous pairs occasionally form cooperative groups with unpaired helper males (Fig. 1). Consistent with the predictions of the kin-selection hypothesis, females in both bi-parental and cooperative groups preferentially engaged in extra-pair matings with relatives, irrespective of relatedness to their social mates, and while suffering no apparent costs of inbreeding depression in their progeny. These finding shave several exciting implications for our understanding of avian mating system diversity and the evolution of cooperative breeding.