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Artigo de periodico
Technology readiness assessment of ultra-deep salt caverns for carbon capture and storage in Brazil (2020)
Goulart, Mariana Barbeiro Ribeiro; Costa, Pedro Vassalo Maia da ; Costa, Alvaro Maia da; Miranda, Antonio C O; Mendes, André Bergsten ; Ebecken, Nelson Francisco Favilla ; Meneghini, Julio Romano ; Nishimoto, Kazuo ; Assi, Gustavo Roque da Silva
Source: International Journal of Greenhouse Gas Control. Unidade: EP
Subjects: PRÉ-SAL, GÁS NATURAL, PETRÓLEO, CARBONO
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ABNT
GOULART, Mariana Barbeiro Ribeiro et al. Technology readiness assessment of ultra-deep salt caverns for carbon capture and storage in Brazil. International Journal of Greenhouse Gas Control, v. 99, p. 1-19, 2020Tradução . . Disponível em: https://doi.org/10.1016/j.ijggc.2020.103083. Acesso em: 09 jun. 2024.
APA
Goulart, M. B. R., Costa, P. V. M. da, Costa, A. M. da, Miranda, A. C. O., Mendes, A. B., Ebecken, N. F. F., et al. (2020). Technology readiness assessment of ultra-deep salt caverns for carbon capture and storage in Brazil. International Journal of Greenhouse Gas Control, 99, 1-19. doi:10.1016/j.ijggc.2020.103083
NLM
Goulart MBR, Costa PVM da, Costa AM da, Miranda ACO, Mendes AB, Ebecken NFF, Meneghini JR, Nishimoto K, Assi GR da S. Technology readiness assessment of ultra-deep salt caverns for carbon capture and storage in Brazil [Internet]. International Journal of Greenhouse Gas Control. 2020 ; 99 1-19.[citado 2024 jun. 09 ] Available from: https://doi.org/10.1016/j.ijggc.2020.103083
Vancouver
Goulart MBR, Costa PVM da, Costa AM da, Miranda ACO, Mendes AB, Ebecken NFF, Meneghini JR, Nishimoto K, Assi GR da S. Technology readiness assessment of ultra-deep salt caverns for carbon capture and storage in Brazil [Internet]. International Journal of Greenhouse Gas Control. 2020 ; 99 1-19.[citado 2024 jun. 09 ] Available from: https://doi.org/10.1016/j.ijggc.2020.103083
Artigo de periodico
Parametric study and geomechanical design of Ultra-deep-water offshore salt caverns for carbon capture and storage in Brazil (2020)
Costa, Pedro Vassalo Maia da ; Costa, Alvaro Maia da; Meneghini, Julio Romano ; Nishimoto, Kazuo ; Sampaio, Claudio Mueller Prado; Assi, Gustavo Roque da Silva ; Malta, Edgard Borges ; Goulart, Mariana Barbeiro Ribeiro; Mendes, André Bergsten ; Udebhulu, Okhiria Dickson ; Azevedo, Ricardo Cabral de ; Eston, Sérgio Médici de ; De Tomi, Giorgio Francesco Cesare ; Ebecken, Nelson Francisco Favilla ; Rosa, Luiz Pinguelli; Miranda, Antonio C O; Brandão, Camila; Breda, Alexandre
Source: International Journal of Rock Mechanics and Mining Sciences. Unidade: EP
Subjects: DIÓXIDO DE CARBONO, PRÉ-SAL, PETRÓLEO, GÁS NATURAL
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ABNT
COSTA, Pedro Vassalo Maia da et al. Parametric study and geomechanical design of Ultra-deep-water offshore salt caverns for carbon capture and storage in Brazil. International Journal of Rock Mechanics and Mining Sciences, v. 131, p. 1-14, 2020Tradução . . Disponível em: https://doi.org/10.1016/j.ijrmms.2020.104354. Acesso em: 09 jun. 2024.
APA
Costa, P. V. M. da, Costa, A. M. da, Meneghini, J. R., Nishimoto, K., Sampaio, C. M. P., Assi, G. R. da S., et al. (2020). Parametric study and geomechanical design of Ultra-deep-water offshore salt caverns for carbon capture and storage in Brazil. International Journal of Rock Mechanics and Mining Sciences, 131, 1-14. doi:10.1016/j.ijrmms.2020.104354
NLM
Costa PVM da, Costa AM da, Meneghini JR, Nishimoto K, Sampaio CMP, Assi GR da S, Malta EB, Goulart MBR, Mendes AB, Udebhulu OD, Azevedo RC de, Eston SM de, De Tomi GFC, Ebecken NFF, Rosa LP, Miranda ACO, Brandão C, Breda A. Parametric study and geomechanical design of Ultra-deep-water offshore salt caverns for carbon capture and storage in Brazil [Internet]. International Journal of Rock Mechanics and Mining Sciences. 2020 ;131 1-14.[citado 2024 jun. 09 ] Available from: https://doi.org/10.1016/j.ijrmms.2020.104354
Vancouver
Costa PVM da, Costa AM da, Meneghini JR, Nishimoto K, Sampaio CMP, Assi GR da S, Malta EB, Goulart MBR, Mendes AB, Udebhulu OD, Azevedo RC de, Eston SM de, De Tomi GFC, Ebecken NFF, Rosa LP, Miranda ACO, Brandão C, Breda A. Parametric study and geomechanical design of Ultra-deep-water offshore salt caverns for carbon capture and storage in Brazil [Internet]. International Journal of Rock Mechanics and Mining Sciences. 2020 ;131 1-14.[citado 2024 jun. 09 ] Available from: https://doi.org/10.1016/j.ijrmms.2020.104354
Artigo de periodico
Potential of storing gas with high CO2 content in salt caverns built in ultra-deep water in Brazil (2019)
Costa, Alvaro Maia da; Costa, Pedro V Maia da ; Udebhulu, Okhiria Dickson ; Azevedo, Ricardo Cabral de ; Ebecken, Nelson Francisco Favilla ; Miranda, Antonio C O; Eston, Sérgio Médici de ; De Tomi, Giorgio Francesco Cesare ; Meneghini, Julio Romano ; Nishimoto, Kazuo ; Ruggeri, Felipe; Malta, Edgard Borges ; Fernandes, Mauro Élis Rocha; Brandão, Camila; Breda, Alexandre
Source: Greenhouse Gases: Science and Technology. Unidade: EP
Subjects: SAL (DEPÓSITO MINERAL), GÁS NATURAL, RESERVATÓRIOS
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ABNT
COSTA, Alvaro Maia da et al. Potential of storing gas with high CO2 content in salt caverns built in ultra-deep water in Brazil. Greenhouse Gases: Science and Technology, v. 9, n. 1, p. 79-94, 2019Tradução . . Disponível em: https://doi.org/10.1002/ghg.1834. Acesso em: 09 jun. 2024.
APA
Costa, A. M. da, Costa, P. V. M. da, Udebhulu, O. D., Azevedo, R. C. de, Ebecken, N. F. F., Miranda, A. C. O., et al. (2019). Potential of storing gas with high CO2 content in salt caverns built in ultra-deep water in Brazil. Greenhouse Gases: Science and Technology, 9( 1), 79-94. doi:10.1002/ghg.1834
NLM
Costa AM da, Costa PVM da, Udebhulu OD, Azevedo RC de, Ebecken NFF, Miranda ACO, Eston SM de, De Tomi GFC, Meneghini JR, Nishimoto K, Ruggeri F, Malta EB, Fernandes MÉR, Brandão C, Breda A. Potential of storing gas with high CO2 content in salt caverns built in ultra-deep water in Brazil [Internet]. Greenhouse Gases: Science and Technology. 2019 ; 9( 1): 79-94.[citado 2024 jun. 09 ] Available from: https://doi.org/10.1002/ghg.1834
Vancouver
Costa AM da, Costa PVM da, Udebhulu OD, Azevedo RC de, Ebecken NFF, Miranda ACO, Eston SM de, De Tomi GFC, Meneghini JR, Nishimoto K, Ruggeri F, Malta EB, Fernandes MÉR, Brandão C, Breda A. Potential of storing gas with high CO2 content in salt caverns built in ultra-deep water in Brazil [Internet]. Greenhouse Gases: Science and Technology. 2019 ; 9( 1): 79-94.[citado 2024 jun. 09 ] Available from: https://doi.org/10.1002/ghg.1834
Artigo de periodico
Experimental salt cavern in offshore ultra-deep water and well design evaluation for CO2 abatement (2019)
Costa, Alvaro Maia da; Costa, Pedro V Maia da ; Miranda, Antonio C O; Goulart, Mariana Barbeiro Ribeiro; Udebhulu, Okhiria Dickson ; Ebecken, Nelson Francisco Favilla ; Azevedo, Ricardo Cabral de ; Eston, Sérgio Médici de ; De Tomi, Giorgio Francesco Cesare ; Meneghini, Julio Romano ; Nishimoto, Kazuo ; Sampaio, Claudio Mueller Prado; Brandão, Camila; Breda, Alexandre
Source: International Journal of Mining Science and Technology. Unidade: EP
Subjects: CARBONO, PRÉ-SAL, POTÁSSIO, GÁS NATURAL
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
COSTA, Alvaro Maia da et al. Experimental salt cavern in offshore ultra-deep water and well design evaluation for CO2 abatement. International Journal of Mining Science and Technology, v. 29, n. 2, p. 239-244, 2019Tradução . . Disponível em: https://doi.org/10.1016/j.ijmst.2019.05.002. Acesso em: 09 jun. 2024.
APA
Costa, A. M. da, Costa, P. V. M. da, Miranda, A. C. O., Goulart, M. B. R., Udebhulu, O. D., Ebecken, N. F. F., et al. (2019). Experimental salt cavern in offshore ultra-deep water and well design evaluation for CO2 abatement. International Journal of Mining Science and Technology, 29( 2), 239-244. doi:10.1016/j.ijmst.2019.05.002
NLM
Costa AM da, Costa PVM da, Miranda ACO, Goulart MBR, Udebhulu OD, Ebecken NFF, Azevedo RC de, Eston SM de, De Tomi GFC, Meneghini JR, Nishimoto K, Sampaio CMP, Brandão C, Breda A. Experimental salt cavern in offshore ultra-deep water and well design evaluation for CO2 abatement [Internet]. International Journal of Mining Science and Technology. 2019 ;29( 2): 239-244.[citado 2024 jun. 09 ] Available from: https://doi.org/10.1016/j.ijmst.2019.05.002
Vancouver
Costa AM da, Costa PVM da, Miranda ACO, Goulart MBR, Udebhulu OD, Ebecken NFF, Azevedo RC de, Eston SM de, De Tomi GFC, Meneghini JR, Nishimoto K, Sampaio CMP, Brandão C, Breda A. Experimental salt cavern in offshore ultra-deep water and well design evaluation for CO2 abatement [Internet]. International Journal of Mining Science and Technology. 2019 ;29( 2): 239-244.[citado 2024 jun. 09 ] Available from: https://doi.org/10.1016/j.ijmst.2019.05.002
Artigo de periodico
Bayesian network classifiers: beyond classification accuracy (2011)
Santos, Edimilson Batista dos; Hruschka Junior, Estevam Rafael ; Hruschka, Eduardo Raul ; Ebecken, Nelson Francisco Favilla
Source: Intelligent Data Analysis : an International Journal. Unidade: ICMC
Assunto: INTELIGÊNCIA ARTIFICIAL
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ABNT
SANTOS, Edimilson Batista dos et al. Bayesian network classifiers: beyond classification accuracy. Intelligent Data Analysis : an International Journal, v. 15, n. 3, p. 279-298, 2011Tradução . . Disponível em: https://doi.org/10.3233/IDA-2010-0468. Acesso em: 09 jun. 2024.
APA
Santos, E. B. dos, Hruschka Junior, E. R., Hruschka, E. R., & Ebecken, N. F. F. (2011). Bayesian network classifiers: beyond classification accuracy. Intelligent Data Analysis : an International Journal, 15( 3), 279-298. doi:10.3233/IDA-2010-0468
NLM
Santos EB dos, Hruschka Junior ER, Hruschka ER, Ebecken NFF. Bayesian network classifiers: beyond classification accuracy [Internet]. Intelligent Data Analysis : an International Journal. 2011 ;15( 3): 279-298.[citado 2024 jun. 09 ] Available from: https://doi.org/10.3233/IDA-2010-0468
Vancouver
Santos EB dos, Hruschka Junior ER, Hruschka ER, Ebecken NFF. Bayesian network classifiers: beyond classification accuracy [Internet]. Intelligent Data Analysis : an International Journal. 2011 ;15( 3): 279-298.[citado 2024 jun. 09 ] Available from: https://doi.org/10.3233/IDA-2010-0468
Artigo de periodico
A Bayesian imputation method for a clustering genetic algorithm (2011)
Hruschka Junior, Estevam Rafael ; Hruschka, Eduardo Raul ; Ebecken, Nelson Francisco Favilla
Source: Journal of Computational Methods in Sciences and Engineering. Unidade: ICMC
Assunto: INTELIGÊNCIA ARTIFICIAL
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
HRUSCHKA JUNIOR, Estevam Rafael e HRUSCHKA, Eduardo Raul e EBECKEN, Nelson Francisco Favilla. A Bayesian imputation method for a clustering genetic algorithm. Journal of Computational Methods in Sciences and Engineering, v. 11, n. 4, p. 173-183, 2011Tradução . . Disponível em: https://doi.org/10.3233/JCM-2011-0362. Acesso em: 09 jun. 2024.
APA
Hruschka Junior, E. R., Hruschka, E. R., & Ebecken, N. F. F. (2011). A Bayesian imputation method for a clustering genetic algorithm. Journal of Computational Methods in Sciences and Engineering, 11( 4), 173-183. doi:10.3233/JCM-2011-0362
NLM
Hruschka Junior ER, Hruschka ER, Ebecken NFF. A Bayesian imputation method for a clustering genetic algorithm [Internet]. Journal of Computational Methods in Sciences and Engineering. 2011 ; 11( 4): 173-183.[citado 2024 jun. 09 ] Available from: https://doi.org/10.3233/JCM-2011-0362
Vancouver
Hruschka Junior ER, Hruschka ER, Ebecken NFF. A Bayesian imputation method for a clustering genetic algorithm [Internet]. Journal of Computational Methods in Sciences and Engineering. 2011 ; 11( 4): 173-183.[citado 2024 jun. 09 ] Available from: https://doi.org/10.3233/JCM-2011-0362
Trabalho de evento
A distance-based mutation operator for learning bayesian network structures using evolutionary algorithms (2010)
Santos, Edimilson Batista dos; Hruschka Junior, Estevam Rafael ; Hruschka, Eduardo Raul ; Ebecken, Nelson Francisco Favilla
Source: Proceedings. Conference titles: IEEE World Congress on Computational Intelligence - WCCI. Unidade: ICMC
Assunto: INTELIGÊNCIA ARTIFICIAL
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ABNT
SANTOS, Edimilson Batista dos et al. A distance-based mutation operator for learning bayesian network structures using evolutionary algorithms. 2010, Anais.. Piscataway: Institute of Electrical and Electronics Engineers - IEEE, 2010. Disponível em: https://doi.org/10.1109/CEC.2010.5586049. Acesso em: 09 jun. 2024.
APA
Santos, E. B. dos, Hruschka Junior, E. R., Hruschka, E. R., & Ebecken, N. F. F. (2010). A distance-based mutation operator for learning bayesian network structures using evolutionary algorithms. In Proceedings. Piscataway: Institute of Electrical and Electronics Engineers - IEEE. doi:10.1109/CEC.2010.5586049
NLM
Santos EB dos, Hruschka Junior ER, Hruschka ER, Ebecken NFF. A distance-based mutation operator for learning bayesian network structures using evolutionary algorithms [Internet]. Proceedings. 2010 ;[citado 2024 jun. 09 ] Available from: https://doi.org/10.1109/CEC.2010.5586049
Vancouver
Santos EB dos, Hruschka Junior ER, Hruschka ER, Ebecken NFF. A distance-based mutation operator for learning bayesian network structures using evolutionary algorithms [Internet]. Proceedings. 2010 ;[citado 2024 jun. 09 ] Available from: https://doi.org/10.1109/CEC.2010.5586049
Artigo de periodico
On the influence of imputation in classification: practical issues (2009)
Hruschka, Eduardo Raul ; Garcia, Antonio J. T.; Hruschka Junior, Estevam Rafael ; Ebecken, Nelson Francisco Favilla
Source: Journal of Experimental & Theoretical Artificial Intelligence. Unidade: ICMC
Assunto: INTELIGÊNCIA ARTIFICIAL
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
HRUSCHKA, Eduardo Raul et al. On the influence of imputation in classification: practical issues. Journal of Experimental & Theoretical Artificial Intelligence, v. 21, n. 1, p. 43 - 58, 2009Tradução . . Disponível em: https://doi.org/10.1080/09528130802246602. Acesso em: 09 jun. 2024.
APA
Hruschka, E. R., Garcia, A. J. T., Hruschka Junior, E. R., & Ebecken, N. F. F. (2009). On the influence of imputation in classification: practical issues. Journal of Experimental & Theoretical Artificial Intelligence, 21( 1), 43 - 58. doi:10.1080/09528130802246602
NLM
Hruschka ER, Garcia AJT, Hruschka Junior ER, Ebecken NFF. On the influence of imputation in classification: practical issues [Internet]. Journal of Experimental & Theoretical Artificial Intelligence. 2009 ; 21( 1): 43 - 58.[citado 2024 jun. 09 ] Available from: https://doi.org/10.1080/09528130802246602
Vancouver
Hruschka ER, Garcia AJT, Hruschka Junior ER, Ebecken NFF. On the influence of imputation in classification: practical issues [Internet]. Journal of Experimental & Theoretical Artificial Intelligence. 2009 ; 21( 1): 43 - 58.[citado 2024 jun. 09 ] Available from: https://doi.org/10.1080/09528130802246602

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