Relevant bibliographies by topics / Bioinspired Computation

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers

Academic literature on the topic 'Bioinspired Computation'

Author: Grafiati
Published: 9 March 2023
Last updated: 19 July 2025

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Journal articles on the topic "Bioinspired Computation"

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Cui, Zhihua, Rajan Alex, Rajendra Akerkar, and Xin-She Yang. "Recent Advances on Bioinspired Computation." Scientific World Journal 2014 (2014): 1–3. http://dx.doi.org/10.1155/2014/934890.

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Gunji, Yukio-Pegio, and Daisuke Uragami. "Breaking of the Trade-Off Principle between Computational Universality and Efficiency by Asynchronous Updating." Entropy 22, no. 9 (2020): 1049. http://dx.doi.org/10.3390/e22091049.

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Although natural and bioinspired computing has developed significantly, the relationship between the computational universality and efficiency beyond the Turing machine has not been studied in detail. Here, we investigate how asynchronous updating can contribute to the universal and efficient computation in cellular automata (CA). First, we define the computational universality and efficiency in CA and show that there is a trade-off relation between the universality and efficiency in CA implemented in synchronous updating. Second, we introduce asynchronous updating in CA and show that asynchro
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Hanif, Muhammad Kashif, Ramzan Talib, Muhammad Awais, Muhammad Yahya Saeed, and Umer Sarwar. "Comparison of Bioinspired Computation and Optimization Techniques." Current Science 115, no. 3 (2018): 450. http://dx.doi.org/10.18520/cs/v115/i3/450-453.

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Botella, Guillermo, Antonio Garcia, Manuel Rodriguez-Alvarez, Eduardo Ros, Uwe Meyer-Baese, and María C. Molina. "Robust Bioinspired Architecture for Optical-Flow Computation." IEEE Transactions on Very Large Scale Integration (VLSI) Systems 18, no. 4 (2010): 616–29. http://dx.doi.org/10.1109/tvlsi.2009.2013957.

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Chen, Tinggui, Jianjun Yang, Kai Huang, and Qiang Cheng. "Bioinspired Computation and Its Applications in Operation Management." Scientific World Journal 2014 (2014): 1–5. http://dx.doi.org/10.1155/2014/356571.

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Demidova, L. A., and A. V. Gorchakov. "Application of bioinspired global optimization algorithms to the improvement of the prediction accuracy of compact extreme learning machines." Russian Technological Journal 10, no. 2 (2022): 59–74. http://dx.doi.org/10.32362/2500-316x-2022-10-2-59-74.

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Objectives. Recent research in machine learning and artificial intelligence aimed at improving prediction accuracy and reducing computational complexity resulted in a novel neural network architecture referred to as an extreme learning machine (ELM). An ELM comprises a single-hidden-layer feedforward neural network in which the weights of connections among input-layer neurons and hidden-layer neurons are initialized randomly, while the weights of connections among hidden-layer neurons and output-layer neurons are computed using a generalized Moore– Penrose pseudoinverse operation. The replacem
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Wang, Zhaocai, Xiaoguang Bao, and Tunhua Wu. "A Parallel Bioinspired Algorithm for Chinese Postman Problem Based on Molecular Computing." Computational Intelligence and Neuroscience 2021 (January 15, 2021): 1–13. http://dx.doi.org/10.1155/2021/8814947.

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The Chinese postman problem is a classic resource allocation and scheduling problem, which has been widely used in practice. As a classical nondeterministic polynomial problem, finding its efficient algorithm has always been the research direction of scholars. In this paper, a new bioinspired algorithm is proposed to solve the Chinese postman problem based on molecular computation, which has the advantages of high computational efficiency, large storage capacity, and strong parallel computing ability. In the calculation, DNA chain is used to properly represent the vertex, edge, and correspondi
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Wu, Zhihua, and Aike Guo. "Bioinspired figure-ground discrimination via visual motion smoothing." PLOS Computational Biology 19, no. 4 (2023): e1011077. http://dx.doi.org/10.1371/journal.pcbi.1011077.

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Flies detect and track moving targets among visual clutter, and this process mainly relies on visual motion. Visual motion is analyzed or computed with the pathway from the retina to T4/T5 cells. The computation of local directional motion was formulated as an elementary movement detector (EMD) model more than half a century ago. Solving target detection or figure-ground discrimination problems can be equivalent to extracting boundaries between a target and the background based on the motion discontinuities in the output of a retinotopic array of EMDs. Individual EMDs cannot measure true veloc
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Chen, Lei, Liyi Zhang, Yanju Guo, Yong Huang, and Jingyi Liang. "Blind Source Separation Based on Covariance Ratio and Artificial Bee Colony Algorithm." Mathematical Problems in Engineering 2014 (2014): 1–12. http://dx.doi.org/10.1155/2014/484327.

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The computation amount in blind source separation based on bioinspired intelligence optimization is high. In order to solve this problem, we propose an effective blind source separation algorithm based on the artificial bee colony algorithm. In the proposed algorithm, the covariance ratio of the signals is utilized as the objective function and the artificial bee colony algorithm is used to solve it. The source signal component which is separated out, is then wiped off from mixtures using the deflation method. All the source signals can be recovered successfully by repeating the separation pro
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Marin Machado de Souza, Rafael, Andrew Holm, Márcio Biczyk, and Leandro Nunes de Castro. "A Systematic Literature Review on the Use of Federated Learning and Bioinspired Computing." Electronics 13, no. 16 (2024): 3157. http://dx.doi.org/10.3390/electronics13163157.

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Federated learning (FL) and bioinspired computing (BIC), two distinct, yet complementary fields, have gained significant attention in the machine learning community due to their unique characteristics. FL enables decentralized machine learning by allowing models to be trained on data residing across multiple devices or servers without exchanging raw data, thus enhancing privacy and reducing communication overhead. Conversely, BIC draws inspiration from nature to develop robust and adaptive computational solutions for complex problems. This paper explores the state of the art in the integration
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Dissertations / Theses on the topic "Bioinspired Computation"

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MANZONI, LUCA. "Dynamics of bioinspired computation." Doctoral thesis, Università degli Studi di Milano-Bicocca, 2013. http://hdl.handle.net/10281/42373.

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Since its birth, Computer Science has been inspired by natural phenomena. Two main approaches where developed through the years. The first one is concerned with the study of the properties nature-inspired models that can also be used to model nature. Examples in this fields are Cellular Automata and Reaction Systems. The second one uses nature-inspired model to perform optimization tasks where exact algorithms are not applicable. Evolutionary algorithms, like Genetic Algorithms and Genetic Programming are some of the most prominent examples. The main aim of this thesis is the study of the d
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Benítez, César Manuel Vargas. "Contributions to the study of the protein folding problem using bioinspired computation and molecular dynamics." Universidade Tecnológica Federal do Paraná, 2015. http://repositorio.utfpr.edu.br/jspui/handle/1/1211.

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O Problema de Dobramento de Proteínas (PDP) é considerado um dos desafios abertos mais importantes da Biologia e Bioinformática. Nesta tese, uma nova abordagem para simular os pathways de dobramento de proteínas é proposta onde, ao invés de utilizar a estrutura tridimensional da proteína, os estados de dobramento são representados por Mapas de Contatos (MC). Autômatos Celulares bidimensionais (2D-CA) são utilizados para simular o processo de dobramento, onde cada configuração representa um estado de dobramento e é obtida em relação ao seu estado predecessor e uma regra de transição. Determinar
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Centi, Alessia. "Computational modelling and design of bioinspired silica materials." Thesis, University of Strathclyde, 2017. http://digitool.lib.strath.ac.uk:80/R/?func=dbin-jump-full&object_id=27951.

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The use of bio-inspired methods for production of mesoporous silicas could lead to significant improvements in the synthetic conditions at which these materials are traditionally produced, removing the need for strong pH as well as high temperatures and pressures, and opening the way for milder treatments for template removal. However, due to the complexity of these systems, with many processes occurring simultaneously and high dependence on the specific synthetic conditions,obtaining a detailed description of their mechanism of formation based only on experimental methods is often very diffic
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Warren, Kristin M. "Passive Mechanical Lysis of Bioinspired Systems: Computational Modeling and Microfluidic Experiments." Research Showcase @ CMU, 2016. http://repository.cmu.edu/dissertations/840.

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Many developed nations depend on oil for the production of gasoline, diesel, and natural gas. Meanwhile, oil shortages progress and bottlenecks in oil productions continue to materialize. These and other factors result in an energy crisis, which cause detrimental social and economic effects. Because of the impending energy crisis, various potential energy sources have developed including solar, wind, hydroelectric, nuclear, and biomass. Within the biomass sector for renewable energy sources, algae-based biofuels have become one of the most exciting, new feedstocks. Of the potential plant biofu
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David, Marcio Frayze. "Um algoritmo bioinspirado para agrupamento de dados." Universidade Presbiteriana Mackenzie, 2010. http://tede.mackenzie.br/jspui/handle/tede/1519.

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Made available in DSpace on 2016-03-15T19:38:16Z (GMT). No. of bitstreams: 1 Marcio Frayze David.pdf: 699315 bytes, checksum: 587538708d29252e3c3a8f5c46cbaa53 (MD5) Previous issue date: 2010-05-03<br>Fundo Mackenzie de Pesquisa<br>This dissertation discusses the use of bio-inspired algorithms for data clustering, with emphasis on a model of emergent collective behavior of agents and a new clustering algorithm called cBoids is presented. The cBoids algorithm is a variation of the classic Boids model. In this new algorithm, each Boid represents an object from the data base and the three origin
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Naldi, Murilo Coelho. "Agrupamento híbrido de dados utilizando algoritmos genéticos." Universidade de São Paulo, 2006. http://www.teses.usp.br/teses/disponiveis/55/55134/tde-07112006-080351/.

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Técnicas de Agrupamento vêm obtendo bons resultados quando utilizados em diversos problemas de análise de dados, como, por exemplo, a análise de dados de expressão gênica. Porém, uma mesma técnica de agrupamento utilizada em um mesmo conjunto de dados pode resultar em diferentes formas de agrupar esses dados, devido aos possíveis agrupamentos iniciais ou à utilização de diferentes valores para seus parâmetros livres. Assim, a obtenção de um bom agrupamento pode ser visto como um processo de otimização. Esse processo procura escolher bons agrupamentos iniciais e encontrar o melhor conjunto de v
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Vargas, Patricia Amancio. "Sistemas computacionais bio-inspirados : sintese e aplicação em inteligencia computacional e homeostase artificial." [s.n.], 2005. http://repositorio.unicamp.br/jspui/handle/REPOSIP/260780.

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Orientadores: Fernando Jose Von Zuben, Leandro Nunes de Castro Silva<br>Tese (doutorado) - Universidade Estadual de Campinas, Faculdade de Engenharia Eletrica e Computação<br>Made available in DSpace on 2018-08-06T14:08:06Z (GMT). No. of bitstreams: 1 Vargas_PatriciaAmancio_D.pdf: 4626705 bytes, checksum: b203a58e3f5f1c613db0787b3e396196 (MD5) Previous issue date: 2005<br>Resumo: Este trabalho propõe uma classificação circunstancial para sistemas complexos, incluindo uma estrutura unificada de descrição a ser empregada na análise e síntese de sistemas computacionais bio-inspirados. Como um r
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Grosberg, Anna. "A Bioinspired Computational Model of Cardiac Mechanics: Pathology and Development." Thesis, 2008. https://thesis.library.caltech.edu/2263/13/Ch2.pdf.

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<p>In this work we study the function and development of the myocardium by creating models that have been stripped down to essentials. The model for the adult myocardium is based on the double helical band formation of the heart muscle fibers, observed in both histological studies and advanced DTMRI images. The muscle fibers in the embryonic myocardium are modeled as a helical band wound around a tubular chamber. We model the myocardium as an elastic body, utilizing the finite element method for the computations. We show that when the spiral band architecture is combined with spatial wave exci
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Huang, Tzu-Hsuan, and 黃子軒. "Computational Phase-Field Modeling for Microstructural Evolution in Bioinspired Material from Freeze-Casting Process." Thesis, 2016. http://ndltd.ncl.edu.tw/handle/10558826010888428956.

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碩士<br>國立臺灣大學<br>土木工程學研究所<br>104<br>In this research, a numerical model for microstructure evolution in the freeze-casting process is established. The theoretical mechanism behind the ceramic colloidal suspension solidification process is revealed; also, the relationship between the critical factors and the porous structures is quantitatively described. The model is benchmarked with experimental results and found to be in good agreement. In recent decades, freeze-casting, with an excellent flexibility in microstructure control, has attracted great attention as a potential manufacture method
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Books on the topic "Bioinspired Computation"

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Neumann, Frank, and Carsten Witt. Bioinspired Computation in Combinatorial Optimization. Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-16544-3.

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Ferrández Vicente, José Manuel, José Ramón Álvarez-Sánchez, Félix de la Paz López, Fco Javier Toledo-Moreo, and Hojjat Adeli, eds. Bioinspired Computation in Artificial Systems. Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-18833-1.

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Neumann, Frank. Bioinspired Computation in Combinatorial Optimization: Algorithms and Their Computational Complexity. Springer-Verlag Berlin Heidelberg, 2010.

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Mira, José, José Manuel Ferrández, José R. Álvarez, Félix de la Paz, and F. Javier Toledo, eds. Bioinspired Applications in Artificial and Natural Computation. Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-02267-8.

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David, Hutchison. Bioinspired Applications in Artificial and Natural Computation: Third International Work-Conference on the Interplay Between Natural and Artificial Computation, IWINAC 2009, Santiago de Compostela, Spain, June 22-26, 2009, Proceedings, Part II. Springer Berlin Heidelberg, 2009.

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Cabestany, Joan, Alberto Prieto, and Francisco Sandoval, eds. Computational Intelligence and Bioinspired Systems. Springer Berlin Heidelberg, 2005. http://dx.doi.org/10.1007/b136983.

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Silhavy, Radek, ed. Artificial Intelligence and Bioinspired Computational Methods. Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-51971-1.

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Vega, Francisco Fernández de. Parallel Architectures and Bioinspired Algorithms. Springer Berlin Heidelberg, 2012.

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Ferrández, José Manuel. New Challenges on Bioinspired Applications: 4th International Work-conference on the Interplay Between Natural and Artificial Computation, IWINAC 2011, La Palma, Canary Islands, Spain, May 30 - June 3, 2011. Proceedings, Part II. Springer Berlin Heidelberg, 2011.

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Stephan, Olariu, and Zomaya Albert Y, eds. Handbook of bioinspired algorithms and applications. Chapman & Hall/CRC, 2006.

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Book chapters on the topic "Bioinspired Computation"

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Neumann, Frank, and Carsten Witt. "Combinatorial Optimization and Computational Complexity." In Bioinspired Computation in Combinatorial Optimization. Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-16544-3_2.

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Neumann, Frank, and Carsten Witt. "Shortest Paths." In Bioinspired Computation in Combinatorial Optimization. Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-16544-3_8.

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Neumann, Frank, and Carsten Witt. "Eulerian Cycles." In Bioinspired Computation in Combinatorial Optimization. Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-16544-3_9.

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Neumann, Frank, and Carsten Witt. "Introduction." In Bioinspired Computation in Combinatorial Optimization. Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-16544-3_1.

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Neumann, Frank, and Carsten Witt. "Multi-objective Minimum Spanning Trees." In Bioinspired Computation in Combinatorial Optimization. Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-16544-3_10.

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Neumann, Frank, and Carsten Witt. "Minimum Spanning Trees Made Easier." In Bioinspired Computation in Combinatorial Optimization. Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-16544-3_11.

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Neumann, Frank, and Carsten Witt. "Covering Problems." In Bioinspired Computation in Combinatorial Optimization. Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-16544-3_12.

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Neumann, Frank, and Carsten Witt. "Cutting Problems." In Bioinspired Computation in Combinatorial Optimization. Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-16544-3_13.

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Neumann, Frank, and Carsten Witt. "Stochastic Search Algorithms." In Bioinspired Computation in Combinatorial Optimization. Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-16544-3_3.

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Neumann, Frank, and Carsten Witt. "Analyzing Stochastic Search Algorithms." In Bioinspired Computation in Combinatorial Optimization. Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-16544-3_4.

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Conference papers on the topic "Bioinspired Computation"

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Arias-Rojas, Tatiana, Silvia Mau-Incháustegui, J. J. Saavedra-Arias, and Stefany Solano-González. "Computational Proteomic Profiling of Putative Magnetotactic Bacterial Proteins." In 2024 IEEE 6th International Conference on BioInspired Processing (BIP). IEEE, 2024. https://doi.org/10.1109/bip63158.2024.10885381.

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Luiz, Matheus de S., M. A. Pastrana, Lukas A. Da Silva, et al. "Comparison of Bioinspired MLP Controllers for Mobile Robots Obstacle Following/Avoidance." In 2024 IEEE Latin American Conference on Computational Intelligence (LA-CCI). IEEE, 2024. https://doi.org/10.1109/la-cci62337.2024.10814784.

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Pastrana, M. A., José Oniram de A. Limaverde Filho, Luiz Henrique Oliveira, Jaider Bautista, Eugênio Fortaleza, and Daniel M. Muñoz. "Comparative analysis of bioinspired algorithms for tuning a flatness-based controller: A ball and beam case study." In 2024 IEEE Latin American Conference on Computational Intelligence (LA-CCI). IEEE, 2024. https://doi.org/10.1109/la-cci62337.2024.10814736.

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Neumann, Frank, and Carsten Witt. "Bioinspired computation in combinatorial optimization." In Proceeding of the fifteenth annual conference companion. ACM Press, 2013. http://dx.doi.org/10.1145/2464576.2466738.

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Witt, Carsten. "Bioinspired computation in combinatorial optimization." In GECCO '14: Genetic and Evolutionary Computation Conference. ACM, 2014. http://dx.doi.org/10.1145/2598394.2605353.

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Neumann, Frank, and Carsten Witt. "Bioinspired computation in combinatorial optimization." In the fourteenth international conference. ACM Press, 2012. http://dx.doi.org/10.1145/2330784.2330928.

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da Silveira, Lucas A., Jose L. Soncco-Alvarez, Thaynara A. de Lima, and Mauricio Ayala-Rincon. "Behavior of Bioinspired Algorithms in Parallel Island Models." In 2020 IEEE Congress on Evolutionary Computation (CEC). IEEE, 2020. http://dx.doi.org/10.1109/cec48606.2020.9185732.

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Cotta, Carlos, Antonio J. Fernández-Leiva, Francisco Fernández de Vega, et al. "Ephemeral Computing and Bioinspired Optimization - Challenges and Opportunities." In 7th International Conference on Evolutionary Computation Theory and Applications. SCITEPRESS - Science and and Technology Publications, 2015. http://dx.doi.org/10.5220/0005628903190324.

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Fu, Qinbing, Jigen Peng, and Shigang Yue. "Bioinspired Contrast Vision Computation for Robust Motion Estimation Against Natural Signals." In 2021 International Joint Conference on Neural Networks (IJCNN). IEEE, 2021. http://dx.doi.org/10.1109/ijcnn52387.2021.9533680.

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Hauptvogel, Michael, Jordi Madrenas, and J. Manuel Moreno. "SpiNDeK: An Integrated design tool for the multiprocessor emulation of complex bioinspired spiking neural networks." In 2009 IEEE Congress on Evolutionary Computation (CEC). IEEE, 2009. http://dx.doi.org/10.1109/cec.2009.4982941.

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