Relevant bibliographies by topics / Evolutionary models

Academic literature on the topic 'Evolutionary models'

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Published: 4 June 2021
Last updated: 20 February 2023

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Journal articles on the topic "Evolutionary models"

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Han, Z., and Ph Podsiadlowski. "Binary Evolutionary Models." Proceedings of the International Astronomical Union 4, S252 (April 2008): 349–57. http://dx.doi.org/10.1017/s1743921308023193.

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AbstractIn this talk, we present the general principles of binary evolution and give two examples. The first example is the formation of subdwarf B stars (sdBs) and their application to the long-standing problem of ultraviolet excess (also known as UV-upturn) in elliptical galaxies. The second is for the progenitors of type Ia supernovae (SNe Ia). We discuss the main binary interactions, i.e., stable Roche lobe overflow (RLOF) and common envelope (CE) evolution, and show evolutionary channels leading to the formation of various binary-related objects. In the first example, we show that the binary model of sdB stars of Han et al. (2002, 2003) can reproduce field sdB stars and their counterparts, extreme horizontal branch (EHB) stars, in globular clusters. By applying the binary model to the study of evolutionary population synthesis, we have obtained an “a priori” model for the UV-upturn of elliptical galaxies and showed that the UV-upturn is most likely resulted from binary interactions. This has major implications for understanding the evolution of the UV excess and elliptical galaxies in general. In the second example, we introduce the single degenerate channel and the double degenerate channel for the progenitors of SNe Ia. We give the birth rates and delay time distributions for each channel and the distributions of companion stars at the moment of SN explosion for the single degenerate channel, which would help to search for the remnant companion stars observationally.
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Sullivan, Roger J., and Henry F. Lyle, III. "Economic models are not evolutionary models." Behavioral and Brain Sciences 28, no. 6 (December 2005): 836. http://dx.doi.org/10.1017/s0140525x05430149.

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Henrich et al. reject the “selfishness axiom” within a narrowly-defined economic model, and are premature in claiming that they have demonstrated cross-cultural variability in “selfishness” as defined in broader evolutionary theory. We also question whether a key experimental condition, anonymity, can be maintained in the small, cohesive, social groupings employed in the study.
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Moraes, Marcelo Botelho da Costa, and Marcelo Seido Nagano. "Cash Management Policies By Evolutionary Models: A Comparison Using The MILLER-ORR Model." Journal of Information Systems and Technology Management 10, no. 3 (December 30, 2013): 561–76. http://dx.doi.org/10.4301/s1807-17752013000300006.

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APALOO, JOSEPH. "FREQUENCY INDEPENDENT EVOLUTIONARY MODELS." Journal of Biological Systems 07, no. 01 (March 1999): 1–9. http://dx.doi.org/10.1142/s0218339099000024.

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Using general classes of evolutionary models in which fitnesses are frequency independent and density dependent, we show that a phenotype is an ESS if and only if it is a NIS. This result is seen to hold in single species and multi species evolutionary models with and without structure. Frequency independent and density dependent evolutionary models are thus more likely to attain an ESS.
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van Rensbergen, Walter, Nicki Mennekens, Jean-Pierre de Greve, Kim Jansen, and Bert de Loore. "Evolutionary models of binaries." Proceedings of the International Astronomical Union 6, S272 (July 2010): 486–91. http://dx.doi.org/10.1017/s1743921311011136.

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AbstractWe have put on CDS a catalog containing 561 evolutionary models of binaries: J/A+A/487/1129 (Van Rensbergen+, 2008). The catalog covers a grid of binaries with a B-type primary at birth, different values for the initial mass ratio and a wide range of initial orbital periods. The evolution was calculated with the Brussels code in which we introduced the spinning up and the creation of a hot spot on the gainer or its accretion disk, caused by impacting mass coming from the donor. When the kinetic energy of fast rotation added to the radiative energy of the hot spot exceeds the binding energy, a fraction of the transferred matter leaves the system: the evolution is liberal during a short lasting era of rapid mass transfer. The spin-up of the gainer was modulated using both strong and weak tides. The catalog shows the results for both types. For comparison, we included the evolutionary tracks calculated with the conservative assumption. Binaries with an initial primary below 6 M⊙ show hardly any mass loss from the system and thus evolve conservatively. Above this limit differences between liberal and conservative evolution grow with increasing initial mass of the primary star.
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Ponzi, A., and Y. Aizawa. "Evolutionary financial market models." Physica A: Statistical Mechanics and its Applications 287, no. 3-4 (December 2000): 507–23. http://dx.doi.org/10.1016/s0378-4371(00)00389-7.

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Burley, Peter. "Evolutionary von Neumann models." Journal of Evolutionary Economics 2, no. 4 (December 1992): 269–80. http://dx.doi.org/10.1007/bf01200126.

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Garfield, Zachary H., Robert L. Hubbard, and Edward H. Hagen. "Evolutionary Models of Leadership." Human Nature 30, no. 1 (February 19, 2019): 23–58. http://dx.doi.org/10.1007/s12110-019-09338-4.

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Nelson, Gareth. "CLADISTICS AND EVOLUTIONARY MODELS." Cladistics 5, no. 3 (September 1989): 275–89. http://dx.doi.org/10.1111/j.1096-0031.1989.tb00490.x.

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Stephenson, Daniel. "Coordination and evolutionary dynamics: When are evolutionary models reliable?" Games and Economic Behavior 113 (January 2019): 381–95. http://dx.doi.org/10.1016/j.geb.2018.10.002.

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Dissertations / Theses on the topic "Evolutionary models"

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Hall, Matt. "Models of evolutionary ecology." Thesis, Imperial College London, 2002. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.268796.

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Hartmann, Klaas. "Biodiversity conservation and evolutionary models." Thesis, University of Canterbury. Mathematics and Statistics, 2008. http://hdl.handle.net/10092/1776.

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Biodiversity conservation requires a framework for prioritising limited resources to the many endangered species. One such framework that has seen much attention and is considered extensively in this thesis, is the Noah's Ark Problem (NAP). The NAP combines a biodiversity measure (Phylogenetic Diversity; PD) with species survival probabilities and conservation costs. The aim of the NAP is to allocate the limited conservation resources such that the future expected PD is maximised. Obtaining optimal solutions to the NAP is a computationally complex problem to which several efficient algorithms are provided here. An extension to the NAP is also developed which allows uncertainty about the survival probability estimates to be included. Using this extension we show that the NAP is robust to uncertainty in these parameters and that even very poor estimates are beneficial. To justify using or promoting PD, it must produce a significant increase in the amount of biodiversity that is preserved. We show that the increase attainable from the NAP is typically around 20% but may be as high as 150%. An alternative approach to PD and the NAP is to prioritise species using simple species specific indices. The benefit of these indices is that they are easy to calculate, explain and integrate into existing management frameworks. Here we investigate the use of such indices and show that they provide between 60% and 80% of the gains obtainable using PD. To explore the expected behaviours of conservation methods (such as the NAP) a distribution of phylogenetics trees is required. Evolutionary models describe the diversification process by which a single species gives rise to multiple species. Such models induce a probability distribution on trees and can therefore be used to investigate the expected behaviour of conservation methods. Even simple and widely used models, such as the Yule model, remain poorly understood. In this thesis we present some new analytic results and methods for sampling trees from a broad range of evolutionary models. Lastly we introduce a new model that provides a simple biological explanation for a long standing discrepancy between models and trees derived from real data -- the tree balance distribution.
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Forrester, Deanna L., and University of Lethbridge Faculty of Arts and Science. "Evolutionary models for male androphilia." Thesis, Lethbridge, Alta. : University of Lethbridge, Dept. of Psychology, 2011, 2011. http://hdl.handle.net/10133/2631.

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Androphilia refers to sexual attraction and arousal to adult males, whereas gynephilia refers to sexual attraction and arousal to adult females. Prehistoric artifacts such as art and pottery indicate that male-male same sex behaviour has existed for millennia. Bearing this in mind, and considering that male androphilia has a genetic component yet androphilic males reproduce at a fraction of the rate than do gynephilic males, how the genes for male androphilia have been maintained in the population presents an evolutionary puzzle. This thesis tests two hypotheses that attempt to address this Darwinian paradox. Chapter one reviews the current literature on the kin selection hypothesis and the sexually antagonistic gene hypothesis. In addition, rationales for testing these hypotheses in Canada are provided. Chapter two tests the kin selection hypothesis for male androphilia within a Canadian population. Results and implications are discussed. Chapter three tests the sexually antagonistic gene hypothesis within a Canadian population. Results and implications are discussed. Chapter four summarizes the results of the two studies and discusses how these findings may be interpreted from an evolutionary perspective. The impacts of gene-environment interaction on the functional behavioral expression of traits are emphasized.
viii, 113 leaves ; 29 cm
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Hadjichrysanthou, C. "Evolutionary models in structured populations." Thesis, City University London, 2012. http://openaccess.city.ac.uk/1731/.

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Evolutionary dynamics have been traditionally studied in infinitely large homogeneous populations where each individual is equally likely to interact with every other individual. However, real populations are finite and characterised by complex interactions among individuals. In this work, the influence of the population structure on the outcome of the evolutionary process is explored. Through an analytic approach, this study first examines the stochastic evolutionary game dynamics following the update rules of the invasion process, an adaptation of the Moran process, on finite populations represented by three simple graphs; the complete graph, the circle and the star graph. The exact formulae for the fixation probability and the speed of the evolutionary process under different conditions are derived, and the effect of the population structure on each of these quantities is studied. The research then considers to what extent the change of the strategy update rules of the evolutionary dynamics can affect the evolutionary process in structured populations compared to the process in homogeneous well-mixed populations. As an example, the evolutionary game dynamics on the extreme heterogeneous structure of the star graph is studied analytically under different update rules. It is shown that in contrast to homogeneous populations, the choice of the update rules might be crucial for the evolution of a non-homogeneous population. Although an analytic investigation of the process is possible when the contact structure of the population has a simple form, this is usually infeasible on complex structures and the use of various assumptions and approximations is necessary. This work introduces an effective method for the approximation of the evolutionary process in populations with a complex structure. Another component of this research work involves the use of game theory for the modelling of a very common phenomenon in the natural world. The models developed examine the evolution of kleptoparasitic populations, foraging populations in which animals can steal the prey from other animals for their survival. A basic game-theoretical model of kleptoparasitism in an infinite homogeneous well-mixed population is extended to structured populations represented by different graphs. The features of the population structure that might favour the appearance of kleptoparasitic behaviour among animals are addressed. In addition, a game-theoretical model is proposed for the investigation of the ecological conditions that encourage foraging animals to share their prey, a very common behaviour occurring in a wide range of animal species.
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Clarke, Magnus. "Evolutionary models with ecological interactions." Thesis, University of Sheffield, 2017. http://etheses.whiterose.ac.uk/19890/.

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Models for the evolution of species' traits and speciation rates usually ignore ecology: most comparative analyses of evolution are ecologically neutral and ignore ecological mechanisms such as competition and limiting similarity. However, such processes can impact profoundly on the distribution of traits across a group of species if they are ecologically similar (e.g. as in adaptive radiations). Here, two new models are introduced to explicitly include the effects of lineage-lineage interactions, one generating trait evolution and the other addressing lineage diversification. The new model for trait evolution is fitted to a wide range of existing animal datasets, using a simulation approach. Evidence was found of clade-wide character displacement patterns in some adaptive radiations, including Darwin’s finches; however, these patterns are not prevalent across animal clades as a whole. Three types of diversification model are also compared here, including the novel interaction-based diversification model. This new model links trait space densities to diversification rates, suppressing diversification among closely packed species. Although these models have a similar conceptual basis, in terms of the accumulation of filled niches, they produce quite different evolutionary histories. The implications of ecological interactions between species are discussed, both for data interpretation and for future modelling approaches.
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Hoehn, Kenneth. "Evolutionary models of antibody lineages." Thesis, University of Oxford, 2017. https://ora.ox.ac.uk/objects/uuid:ae1fcd96-d858-4f6d-8d99-46b678b2625d.

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Antibodies are proteins released into the blood and mucosa to identify and neutralize invading pathogens by binding to structures on their surface (antigens). Before being exported as antibodies, these vital components of the adaptive immune system are expressed, and refined, as membrane-bound B cell receptors (BCRs). BCRs are initially formed through somatic recombination of germline DNA, creating a large repertoire of unique sequences. After encountering antigen for the first time, BCRs undergo an evolutionary process of somatic mutation and clonal selection leading to improved antigen binding. Recently, next-generation sequencing has provided an unprecedented ability to characterize the genetic diversity of BCRs within individuals. Chapter 1 of this thesis overviews the work done elsewhere in the field until now. Chapter 2 uses summary statistics applied to high-throughput sequence data from a clinical trial to explore the genetic changes that occur in the repertoire during HIV infection. The results of these analyses motivated a more rigorous, model-based approach to understanding BCR diversity. Chapter 3 introduces a new phylogenetic substitution model that relaxes common model assumptions that are violated by somatic hypermutation. Chapter 4 expands this model to incorporate previously defined empirical models of somatic hypermutation, providing a more complete model of B cell maturation. Chapter 5 uses the models developed in Chapters 4 and 5 to explore dynamics of clonal selection during the maturation of three HIV broadly neutralizing antibody lineages. Finally, Chapter 6 shows how this framework may be scaled up to characterize data from entire BCR repertoires from a phylogenetic perspective.
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梁慧敏 and Wai-man Wanthy Leung. "Evolutionary optimisation of industrial systems." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 1999. http://hub.hku.hk/bib/B30252994.

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Quickfall, Christopher G. "Models of the major evolutionary transitions." Thesis, University of Sheffield, 2016. http://etheses.whiterose.ac.uk/14383/.

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This thesis is concerned with the major transitions view of evolution; the idea that general principles operate in the evolution of each new level of the biological hierarchy (Bourke, 2011). We discuss the theoretical background of this field, focussing on inclusive fitness theory and multi-level selection theory, different approaches to analysing the selection of traits. Many of the commonalities between different transitions are dependent on whether they occur within or between species, and whether relatedness is absent (`egalitarian') or present (`fraternal') (Queller, 1997). Altruism underpins fraternal transitions, and mutually beneficial behaviour underpins egalitarian transitions (Bourke, 2011). We focus on several different models relating to this four-way decomposition. Firstly, we focus on arguments that between-species donation may amount to between-species altruism; this has been a point of contention within the literature (Fletcher and Doebeli, 2009; Gardner et al., 2011; Wyatt et al., 2013). We discuss both deterministic (resting on an assumption of quasi-linkage equilibrium) and stochastic approaches to a simple model of between-species donation, finding that stable donation behaviour can evolve in the presence of assortment across all loci, but is vulnerable to unassorted modifiers. We argue that this behaviour can be interpreted as within-species altruism, using the other species as a vector for altruism, and, further, consider our models in relation to the current literature on greenbeards. Our second model concerns maternally-transmitted sex-distorting endosymbionts. Many species, particularly insect populations, are infected by sex-distorting parasites such as the bacteria Wolbachia, which are maternally-transmitted; thus, distortion of sex ratios towards the production of females may be beneficial to the symbiont. We investigate the potential for a reproductive parasite to transition towards mutualism, laying the foundation for an egalitarian transition between species; in particular, we find that population structure is key to this transition. Finally, we discuss several potential avenues for future research; in particular, we note that the social group transformation phase of a major transition involves a number of open questions, or ideas open to further investigation.
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McKenzie, Andy. "Stochastic speciation models for evolutionary trees." Thesis, University of Canterbury. Mathematics and Statistics, 2000. http://hdl.handle.net/10092/5597.

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Phylogenetic trees are widely used in biology to represent evolutionary relationships between species. As the details of the evolutionary process are mostly unknown, modelling work on the shapes of these trees has had to incorporate a random component. Two null models introduced for this purpose are the uniform model and the Yule model. A third model, the comb model, is useful for giving bounds on theoretical results. We investigate some mathematical properties of these three models. Let the distance between two nodes be the number of edges separating them. We find exact formulae for the mean distance of a randomly chosen leaf from the root, and for the mean distance between two randomly chosen leaves of a rooted tree. In addition, for the Yule model we find the probability distribution for the distance of randomly chosen leaf from the root. A cherry is a pair of leaves which are adjacent to a common node. By realising the process of cherry formation by extended Polya urn models we show that the number of cherries is asymptotically normal. This allows us to develop simple statistical tests for the Yule and uniform null hypotheses for the growth of rooted trees. A triplet is a cherry and a pendant edge that are adjacent to a common node. We also show that the asymptotic distribution of triplets is normal for the Yule model, and put forward a conjecture for the distribution under the uniform model. The construction of an evolutionary tree is generally a two stage process: an unrooted tree is constructed, then it is rooted. We investigate a method for rooting a tree based on the shape of the tree and the Yule model for the growth of rooted trees. We show that even for trees with large number of leaves the approximate location of the root can be located with high probability. Let S be a set of two rooted binary trees for which the leaf sets L1, L2 form a partition of the set {l, 2, ... ,n}. We derive a recursion for the number of trees on n leaves that are compatible with the set S. We extend this recursion for a set S of three trees, but show that the numbers of terms required in the recursion grows at least exponentially with the number of trees in the set S. Let S be a set of rooted binary trees. A tree which is a sub-tree of each of the trees in the set is called an agreement sub-tree, and such a tree with the maximum number of possible leaves is called a maximum agreement sub-tree (MAST). We derive an upper bound for the probability that two randomly generated trees have a MAST with number of leaves greater than or equal to a given value s. We find the form the upper bound takes when the trees are generated according to the uniform and Yule models. The entropy of a probability distribution is equal to the mean information, where the information of an event E is - log P (E). We derive exact and asymptotic formulae for the entropy of the comb, uniform and Yule probability distributions. We show that the comb, uniform, and Yule models satisfy a property called group elimination. A special case of the property of group elimination is sampling consistency. We show that for any probability distribution on trees that satisfies sampling consistency there is an upper bound on the probability of the fully symmetric tree shapes. We introduce a modification of the Yule model in which the speciation rate is a function of the time since the last speciation event of a lineage. Using analytical methods we investigate the probability (conditional and unconditional) of the symmetric tree on four leaves under this modified model. If the speciation rate is constant then the probability of the symmetric tree is the same as in the Yule model. Making the speciation rate zero for a period after a speciation event, then constant afterwards, is found to make the symmetric tree more probable. If the speciation rate is constant for some period after a speciation event, then subsequently zero, the symmetric tree is found to be less probable.
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Poulsen, Anders Udo. "Essays on evolutionary models of bargaining." Thesis, University of Essex, 2000. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.343583.

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Books on the topic "Evolutionary models"

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Williams, Bryn Vaughan. Evolutionary neural networks: Models and applications. Birmingham: Aston University. Department of Computer Science and Mathematics, 1995.

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Evolutionary game theory. Cambridge, Mass: MIT Press, 1995.

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Bulmer, M. G. Theoretical evolutionary ecology. Sunderland, Mass: Sinauer Associates, Inc, 1994.

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Jonathan, Raper, ed. Spatial evolutionary modeling. New York: Oxford University Press, 2000.

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Theoretical evolutionary ecology. Sunderland, Mass: Sinauer Associates, 1994.

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Ehteram, Mohammad, Zohreh Sheikh Khozani, Saeed Soltani-Mohammadi, and Maliheh Abbaszadeh. Estimating Ore Grade Using Evolutionary Machine Learning Models. Singapore: Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-19-8106-7.

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W, Feldman Marcus, and Karlin Samuel 1923-, eds. Mathematical evolutionary theory. Princeton, N.J: Princeton University Press, 1989.

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Mayer, David G. Evolutionary algorithms and agricultural systems. Boston: Kluwer Academic Publishers, 2002.

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Tanskanen, Pasi. The evolutionary structural optimization (ESO) method: Theoretical aspects and the modified evolutionary structural optimization (MESO) method. Lappeenranta, Finland: Lappeenranta University of Technology, 2000.

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Codon evolution: Mechanisms and models. Oxford: Oxford University Press, 2012.

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Book chapters on the topic "Evolutionary models"

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Ewens, Warren J., and Gregory R. Grant. "Evolutionary Models." In Statistical Methods in Bioinformatics, 365–84. New York, NY: Springer New York, 2001. http://dx.doi.org/10.1007/978-1-4757-3247-4_13.

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Ryan, Michael. "Evolutionary Models." In The Genetics of Political Behavior, 6–20. 1 Edition. | New York : Routledge, 2020.: Routledge, 2020. http://dx.doi.org/10.4324/9781003099710-2.

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Budde, Reinhard, Karlheinz Kautz, Karin Kuhlenkamp, and Heinz Züllighoven. "Evolutionary Process Models." In Prototyping, 67–78. Berlin, Heidelberg: Springer Berlin Heidelberg, 1992. http://dx.doi.org/10.1007/978-3-642-76820-0_7.

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Baragona, Roberto, Francesco Battaglia, and Irene Poli. "Evolving Regression Models." In Evolutionary Statistical Procedures, 63–84. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-16218-3_3.

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Wheeler, Michael. "Evolutionary Models in Psychology." In The Routledge Companion to Philosophy of Psychology, 471–84. Second edition. | Abingdon, Oxon ; New York, NY : Routledge, Taylor & Francis Group, 2020.: Routledge, 2019. http://dx.doi.org/10.4324/9780429244629-29.

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Broom, Mark, and Jan Rychtář. "Evolutionary cancer modelling." In Game-Theoretical Models in Biology, 485–98. 2nd ed. Boca Raton: Chapman and Hall/CRC, 2022. http://dx.doi.org/10.1201/9781003024682-22.

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Pohlheim, Hartmut, and Peter Marenbach. "Generation of structured process models using Genetic Programming." In Evolutionary Computing, 102–9. Berlin, Heidelberg: Springer Berlin Heidelberg, 1996. http://dx.doi.org/10.1007/bfb0032776.

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Studer, Romain A., and Marc Robinson-Rechavi. "Large-Scale Analyses of Positive Selection Using Codon Models." In Evolutionary Biology, 217–35. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-00952-5_13.

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Baragona, Roberto, Francesco Battaglia, and Irene Poli. "Time Series Linear and Nonlinear Models." In Evolutionary Statistical Procedures, 85–124. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-16218-3_4.

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Mayer, David G. "Agricultural Systems Models." In Evolutionary Algorithms and Agricultural Systems, 9–17. Boston, MA: Springer US, 2002. http://dx.doi.org/10.1007/978-1-4615-1717-7_2.

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Conference papers on the topic "Evolutionary models"

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Kumar, Pardeep, Saroj, and Rajesh Siddavatam. "Classification Models: Non Evolutionary vs. Evolutionary Approach." In 2009 International Conference on Advances in Computing, Control, & Telecommunication Technologies (ACT 2009). IEEE, 2009. http://dx.doi.org/10.1109/act.2009.91.

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Cassisi, Santi, Giuliana Giobbi, Amedeo Tornambe, Gabriella Raimondo, Marco Limongi, L. A. Antonelli, Nicola Menci, and Enzo Brocato. "Stellar Evolutionary Models: current uncertainties." In PROBING STELLAR POPULATIONS OUT TO THE DISTANT UNIVERSE: CEFALU 2008, Proceedings of the International Conference. AIP, 2009. http://dx.doi.org/10.1063/1.3141610.

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"Evolutionary Systems Agents’ Mathematical Models." In International Conference on Agents and Artificial Intelligence. SciTePress - Science and and Technology Publications, 2013. http://dx.doi.org/10.5220/0004219904410444.

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Szabó, György. "Spreading mechanisms of cooperation for the evolutionary Prisoner's Dilemma games." In Stochastic Models in Biological Sciences. Warsaw: Institute of Mathematics Polish Academy of Sciences, 2008. http://dx.doi.org/10.4064/bc80-0-10.

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Oh, Sanghoun, Sangwook Lee, and Moongu Jeon. "Evolutionary optimization programming with probabilistic models." In 2009 Fourth International Conference on Bio-Inspired Computing (BIC-TA). IEEE, 2009. http://dx.doi.org/10.1109/bicta.2009.5338075.

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Mendes, Jerome, Samuel Pinto, Rui Araujo, and Francisco Souza. "Evolutionary fuzzy models for nonlinear identification." In 2012 IEEE 17th Conference on Emerging Technologies & Factory Automation (ETFA 2012). IEEE, 2012. http://dx.doi.org/10.1109/etfa.2012.6489621.

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Arcega, Lorena, Jaime Font, and Carlos Cetina. "Evolutionary Algorithm for Bug Localization in the Reconfigurations of Models at Runtime." In MODELS '18: ACM/IEEE 21th International Conference on Model Driven Engineering Languages and Systems. New York, NY, USA: ACM, 2018. http://dx.doi.org/10.1145/3239372.3239392.

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Ishibuchi, Hisao, and Yusuke Nojima. "Evolutionary Multiobjective Fuzzy System Design." In 3d International ICST Conference on Bio-Inspired Models of Network, Information, and Computing Systems. ICST, 2008. http://dx.doi.org/10.4108/icst.bionetics2008.4718.

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Golchin, Maryam, and Alan Wee-Chung Liew. "Bicluster Detection by Hyperplane Projection and Evolutionary Optimization." In 9th International Conference on Bioinformatics Models, Methods and Algorithms. SCITEPRESS - Science and Technology Publications, 2018. http://dx.doi.org/10.5220/0006710000610068.

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J. Burden, Conrad. "Can Evolutionary Rate Matrices be Estimated from Allele Frequencies?" In International Conference on Bioinformatics Models, Methods and Algorithms. SCITEPRESS - Science and and Technology Publications, 2015. http://dx.doi.org/10.5220/0005253701830188.

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Reports on the topic "Evolutionary models"

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Johnson, Dominic. Evolutionary Models of Irregular Warfare. Fort Belvoir, VA: Defense Technical Information Center, March 2013. http://dx.doi.org/10.21236/ada581874.

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2

Aitken, J. D. Chapter 13: Evolutionary Models and Tectonic Comparisons. Natural Resources Canada/ESS/Scientific and Technical Publishing Services, 1993. http://dx.doi.org/10.4095/192383.

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Royce, Walker. Pragmatic Quality Metrics for Evolutionary Software Development Models. Fort Belvoir, VA: Defense Technical Information Center, January 1991. http://dx.doi.org/10.21236/ada243022.

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Flierl, Glenn. Evolutionary Models: Movement and Mixing in Trait and Physical Space. Fort Belvoir, VA: Defense Technical Information Center, May 2011. http://dx.doi.org/10.21236/ada558763.

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5

Erdem, Erkan, and James Tybout. Trade Policy and Industrial Sector Responses: Using Evolutionary Models to Interpret the Evidence. Cambridge, MA: National Bureau of Economic Research, September 2003. http://dx.doi.org/10.3386/w9947.

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6

Qi, Fei, Zhaohui Xia, Gaoyang Tang, Hang Yang, Yu Song, Guangrui Qian, Xiong An, Chunhuan Lin, and Guangming Shi. A Graph-based Evolutionary Algorithm for Automated Machine Learning. Web of Open Science, December 2020. http://dx.doi.org/10.37686/ser.v1i2.77.

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As an emerging field, Automated Machine Learning (AutoML) aims to reduce or eliminate manual operations that require expertise in machine learning. In this paper, a graph-based architecture is employed to represent flexible combinations of ML models, which provides a large searching space compared to tree-based and stacking-based architectures. Based on this, an evolutionary algorithm is proposed to search for the best architecture, where the mutation and heredity operators are the key for architecture evolution. With Bayesian hyper-parameter optimization, the proposed approach can automate the workflow of machine learning. On the PMLB dataset, the proposed approach shows the state-of-the-art performance compared with TPOT, Autostacker, and auto-sklearn. Some of the optimized models are with complex structures which are difficult to obtain in manual design.
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Durán González, Ana María. Correspondencia de los Modelos de Relaciones Públicas a distintos contextos evolutivos de Responsabilidad Social Empresarial / Connection between Public Relations models and the evolutionary contexts of Corporate Social Responsibility. Revista Internacional de Relaciones Públicas, June 2016. http://dx.doi.org/10.5783/rirp-11-2016-06-91-112.

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8

Комарова, Олена Володимирівна, and Альберт Армаїсович Азарян. Computer Simulation of Biological Processes at the High School. CEUR Workshop Proceedings (CEUR-WS.org), 2018. http://dx.doi.org/10.31812/123456789/2695.

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Abstract. Research goals: the necessity of study in high school of the law of Hardy – Weinberg as one of the fundamental genetic laws was justified. The peculiarities of using the method of model experiment in the study of the genetic and evolutionary processes in populations with the use of computer technology. Object of research: computer simulation of population genetic structure. Subject of research: computer simulation of genetic and evolutionary processes in ideal and real populations. Research methods: pedagogical experiment (survey), analysis of scientific publications on the use of the high school method of modelling genetic and evolutionary processes in populations, computer simulation. Results of the research: a web page for processing by the pupils of the modelling results of genetic and evolutionary processes in populations was created.
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Комарова, Олена Володимирівна, and Альберт Арамаїсович Азарян. Computer Simulation of Biological Processes at the High School. CEUR-WS.org, 2018. http://dx.doi.org/10.31812/123456789/2656.

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Abstract:
Research goals: the necessity of study in high school of the law of Hardy – Weinberg as one of the fundamental genetic laws was justified. The peculiarities of using the method of model experiment in the study of the genetic and evolutionary processes in populations with the use of computer technology. Object of research: computer simulation of population genetic structure. Subject of research: computer simulation of genetic and evolutionary processes in ideal and real populations. Research methods: pedagogical experiment (survey), analysis of scientific publications on the use of the high school method of modelling genetic and evolutionary processes in populations, computer simulation. Results of the research: a web page for processing by the pupils of the modelling results of genetic and evolutionary processes in populations was created.
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10

Gaver, Donald P., Patricia A. Jacobs, and Ernest A. Seglie. Modern Military Evolutionary Acquisition and the Ramifications of RAMS"". Fort Belvoir, VA: Defense Technical Information Center, June 2005. http://dx.doi.org/10.21236/ada434790.

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