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Libros sobre el tema "NATURE INSPIRED ALGORITHM"

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Autor: Grafiati
Publicado: 11 de septiembre de 2023

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1

Caraveo, Camilo, Fevrier Valdez y Oscar Castillo. A New Bio-inspired Optimization Algorithm Based on the Self-defense Mechanism of Plants in Nature. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-05551-6.

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2

Chiong, Raymond, ed. Nature-Inspired Algorithms for Optimisation. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-00267-0.

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3

Gavrilova, Marina L. Transactions on Computational Science XV: Special Issue on Advances in Autonomic Computing: Formal Engineering Methods for Nature-Inspired Computing Systems. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012.

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4

Jain, Shashank. Nature-Inspired Optimization Algorithms with Java. Berkeley, CA: Apress, 2022. http://dx.doi.org/10.1007/978-1-4842-7401-9.

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5

Yang, Xin-She, ed. Nature-Inspired Algorithms and Applied Optimization. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-67669-2.

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6

Yang, Xin-She y Xing-Shi He. Mathematical Foundations of Nature-Inspired Algorithms. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-16936-7.

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7

Bozorg-Haddad, Omid, ed. Advanced Optimization by Nature-Inspired Algorithms. Singapore: Springer Singapore, 2018. http://dx.doi.org/10.1007/978-981-10-5221-7.

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8

Clever algorithms: Nature-inspired programming recipes. [S.l.]: Lulu, 2011.

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9

Yadav, Neha, Anupam Yadav, Jagdish Chand Bansal, Kusum Deep y Joong Hoon Kim, eds. Harmony Search and Nature Inspired Optimization Algorithms. Singapore: Springer Singapore, 2019. http://dx.doi.org/10.1007/978-981-13-0761-4.

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10

Carbas, Serdar, Abdurrahim Toktas y Deniz Ustun, eds. Nature-Inspired Metaheuristic Algorithms for Engineering Optimization Applications. Singapore: Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-33-6773-9.

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11

Dey, Nilanjan, Amira S. Ashour y Siddhartha Bhattacharyya, eds. Applied Nature-Inspired Computing: Algorithms and Case Studies. Singapore: Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-13-9263-4.

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12

Mohamed, Ali, Diego Oliva y Ponnuthurai Nagaratnam Suganthan, eds. Handbook of Nature-Inspired Optimization Algorithms: The State of the Art. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-07512-4.

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13

Mohamed, Ali Wagdy, Diego Oliva y Ponnuthurai Nagaratnam Suganthan, eds. Handbook of Nature-Inspired Optimization Algorithms: The State of the Art. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-07516-2.

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14

Okwu, Modestus O. y Lagouge K. Tartibu. Metaheuristic Optimization: Nature-Inspired Algorithms Swarm and Computational Intelligence, Theory and Applications. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-61111-8.

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15

P, Spaink H., Rozenberg Grzegorz, Kok Joost N, Back Th, Eiben Agoston E y SpringerLink (Online service), eds. Bee-Inspired Protocol Engineering: From Nature to Networks. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009.

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16

Nair, Raveendranath U., Hema Singh, Vineetha Joy y Vishal G. Padwal. Optimization of Multilayered Radar Absorbing Structures Using Nature Inspired Algorithm. Taylor & Francis Group, 2021.

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17

Nair, Raveendranath U., Hema Singh, Vineetha Joy y Vishal G. Padwal. Optimization of Multilayered Radar Absorbing Structures (RAS) Using Nature Inspired Algorithm. Taylor & Francis Group, 2021.

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18

Optimization of Multilayered Radar Absorbing Structures (RAS) Using Nature Inspired Algorithm. Taylor & Francis Group, 2021.

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19

Nair, Raveendranath U., Hema Singh, Vineetha Joy y Vishal G. Padwal. Optimization of Multilayered Radar Absorbing Structures (RAS) Using Nature Inspired Algorithm. Taylor & Francis Group, 2021.

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20

Castillo, Oscar, Camilo Caraveo y Fevrier Valdez. A New Bio-inspired Optimization Algorithm Based on the Self-defense Mechanism of Plants in Nature. Springer, 2018.

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21

Vassiliadis, Vassilios y Georgios Dounias. Algorithmic Trading based on Biologically Inspired Algorithms. Editado por Shu-Heng Chen, Mak Kaboudan y Ye-Rong Du. Oxford University Press, 2018. http://dx.doi.org/10.1093/oxfordhb/9780199844371.013.11.

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Resumen
The chapter discusses algorithmic trading, which refers to any automated process, consisting of a number of interconnected components, whose main aim is to perform financial transactions of any kind. Its chief advantage lies in the fact that human intervention is minimized to an acceptable extent. This is quite desirable because nowadays numerous factors affect financial decisions. Financial managers are able to deal with a limited amount of information. There are many ways to implement algorithmic trading systems. This chapter aims to highlight the efficiency of biologically inspired methodologies when incorporated in such systems. Biologically inspired intelligence comprises a range of algorithms whose common philosophy is based on the behavior of real-world, natural systems and networks. What is more, the performance of the applied nature-inspired intelligence (NII) methodologies is compared to traditional benchmark approaches such as the random portfolio construction.
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22

Adeli, Hojjat y N. H. Siddique. Nature-Inspired Computing. Taylor & Francis Group, 2020.

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23

Balamurugan, S., Anupriya Jain, Sachin Sharma, Dinesh Goyal, Sonia Duggal y Seema Sharma, eds. Nature‐Inspired Algorithms Applications. Wiley, 2021. http://dx.doi.org/10.1002/9781119681984.

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24

Nature-Inspired Optimization Algorithms. Elsevier, 2014. http://dx.doi.org/10.1016/c2013-0-01368-0.

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25

Nature-Inspired Optimization Algorithms. Elsevier, 2021. http://dx.doi.org/10.1016/c2019-0-03762-4.

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26

Khamparia, Aditya, Ashish Khanna, Nhu Gia Nguyen y Bao Le Nguyen, eds. Nature-Inspired Optimization Algorithms. De Gruyter, 2021. http://dx.doi.org/10.1515/9783110676112.

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27

A, Vasuki. Nature-Inspired Optimization Algorithms. Taylor & Francis Group, 2020.

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28

Nature-Inspired Metaheuristic Algorithms. Luniver Press, 2008.

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29

Nature-Inspired Optimization Algorithms. Elsevier, 2016.

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30

A, Vasuki. Nature-Inspired Optimization Algorithms. Taylor & Francis Group, 2020.

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31

A, Vasuki. Nature-Inspired Optimization Algorithms. Taylor & Francis Group, 2022.

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32

A, Vasuki. Nature-Inspired Optimization Algorithms. Taylor & Francis Group, 2020.

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33

Nature-Inspired Optimization Algorithms. Taylor & Francis Group, 2020.

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34

Yang, Xin-She. Nature-Inspired Optimization Algorithms. Elsevier Science & Technology Books, 2020.

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35

Adeli, Hojjat y Nazmul H. Siddique. Nature-Inspired Computing: Bio-Inspired Algorithms. Taylor & Francis Group, 2023.

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36

Chiong, Raymond. Nature-Inspired Algorithms for Optimisation. Springer Berlin / Heidelberg, 2010.

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37

Goyal, Dinesh, S. Balamurugan, Anupriya Jain, Sonia Duggal y Sachin Sharma. Nature Inspired Algorithms and Applications. Wiley & Sons, Incorporated, John, 2021.

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38

Goyal, Dinesh, S. Balamurugan, Anupriya Jain, Sonia Duggal y Sachin Sharma. Nature Inspired Algorithms and Applications. Wiley & Sons, Incorporated, John, 2021.

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39

Goyal, Dinesh, S. Balamurugan, Anupriya Jain, Sonia Duggal y Sachin Sharma. Nature Inspired Algorithms and Applications. Wiley & Sons, Limited, John, 2022.

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40

Nature-Inspired Algorithms for Optimisation. Springer London, Limited, 2009.

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41

Goyal, Dinesh, S. Balamurugan, Anupriya Jain, Sonia Duggal y Sachin Sharma. Nature Inspired Algorithms and Applications. Wiley & Sons, Incorporated, John, 2021.

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42

Yang, Xin-She. Nature-Inspired Algorithms and Applied Optimization. Springer, 2018.

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43

Discrete Problems in Nature Inspired Algorithms. CRC Press, 2017. http://dx.doi.org/10.1201/9781351260886.

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44

Tiwari, Ritu y Anupam Prof Shukla. Discrete Problems in Nature Inspired Algorithms. Taylor & Francis Group, 2017.

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45

Tiwari, Ritu y Anupam Prof Shukla. Discrete Problems in Nature Inspired Algorithms. Taylor & Francis Group, 2017.

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46

Tiwari, Ritu y Anupam Prof Shukla. Discrete Problems in Nature Inspired Algorithms. Taylor & Francis Group, 2017.

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47

Yang, Xin-She. Nature-Inspired Algorithms and Applied Optimization. Springer, 2017.

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48

Yang, Xin-She y Xing-Shi He. Mathematical Foundations of Nature-Inspired Algorithms. Springer, 2019.

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49

Shukla, Anupam y Ritu Tiwari. Discrete Problems in Nature Inspired Algorithms. Taylor & Francis Group, 2020.

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50

Bozorg-Haddad, Omid. Advanced Optimization by Nature-Inspired Algorithms. Springer, 2017.

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