Desenvolvimento e aplicação do software MGA (Molecular Genetic Algorithm)
Autor(a) principal: | |
---|---|
Data de Publicação: | 2013 |
Tipo de documento: | Dissertação |
Idioma: | por |
Título da fonte: | Repositório Institucional da UFG |
dARK ID: | ark:/38995/001300000chz8 |
Texto Completo: | http://repositorio.bc.ufg.br/tede/handle/tede/7512 |
Resumo: | This work focuses on the development of the software MGA, which aims to determine the lowest energy structures of a given molecular system, using Genetic Algorithm (GA). The GA is a method of artificial intelligence that was developed to work with finding the best solutions of the specified conditions, ie, an algorithm that seeks the best answer desired, an optimal result. The MGA uses three techniques: Random Search (RS), Noninclusive Genetic Algorithm (NGA), Inclusive Genetic Algorithm (IGA). The last one is characterized by a new type of evolutionary strategy that allows in a single calculation and a single cycle, obtain several minimum of the potential energy surface. For optimum operation of the algorithm, was made an optimization of the parameters used in MGA, through response surface methodology. Using the techniques RS, IGA and NGA, were determined 141 distinct molecular structures of the amino acid asparagine. In the electronic structure calculations were considered the semi-empirical methods PM3, AM1 and RM1; and DFT potentials, with basis sets 6-311G ** and PC1. The RS determined the Global Minimum (GM) with ease, for the different potentials used, and proved that it’s quite useful in determining molecular geometries where there is no accuracy in the determination of local minima in order of energy. The NGA is efficient in determining the GM, performing in a shorter time, if compared to RS and IGA. The IGA proved to be a more robust method than the others, because in addition to determining the GM, it can find the local minima in order of energy. Performing calculations on an intermediate time of RS and NGA, the IGA determined the GM as the NGA, and found structures that were not founded using RS. The GM’s of asparagine determined using the potentials PC1, PM3, AM1 and RM1 have a large structural difference. This demonstrates that different potencials used in the electronic structure calculations may lead to different results. By analyzing the structures obtained for potentials PC1, PM3, AM1 and RM1, using the IGA, it appears that there is a difference in the topology of the potential energy surface of these potentials. |
id |
UFG-2_82868411f1e84e9548e03b4768fdeca6 |
---|---|
oai_identifier_str |
oai:repositorio.bc.ufg.br:tede/7512 |
network_acronym_str |
UFG-2 |
network_name_str |
Repositório Institucional da UFG |
repository_id_str |
|
spelling |
Guimarães, Freddy Fernandeshttp://lattes.cnpq.br/6780812627526129Guimarães, Freddy Fernandeshttp://lattes.cnpq.br/6780812627526129Neves, Jorge LuizMartins, Felipe Terrahttp://lattes.cnpq.br/6196634849515906Couto, Rafael Carvalho2017-07-07T20:26:10Z2013-04-15COUTO, R. C. Desenvolvimento e aplicação do software MGA (Molecular Genetic Algorithm). 2013. 98 f. Dissertação (Mestrado em Química) - Universidade Federal de Goiás, Goiânia, 2013.http://repositorio.bc.ufg.br/tede/handle/tede/7512ark:/38995/001300000chz8This work focuses on the development of the software MGA, which aims to determine the lowest energy structures of a given molecular system, using Genetic Algorithm (GA). The GA is a method of artificial intelligence that was developed to work with finding the best solutions of the specified conditions, ie, an algorithm that seeks the best answer desired, an optimal result. The MGA uses three techniques: Random Search (RS), Noninclusive Genetic Algorithm (NGA), Inclusive Genetic Algorithm (IGA). The last one is characterized by a new type of evolutionary strategy that allows in a single calculation and a single cycle, obtain several minimum of the potential energy surface. For optimum operation of the algorithm, was made an optimization of the parameters used in MGA, through response surface methodology. Using the techniques RS, IGA and NGA, were determined 141 distinct molecular structures of the amino acid asparagine. In the electronic structure calculations were considered the semi-empirical methods PM3, AM1 and RM1; and DFT potentials, with basis sets 6-311G ** and PC1. The RS determined the Global Minimum (GM) with ease, for the different potentials used, and proved that it’s quite useful in determining molecular geometries where there is no accuracy in the determination of local minima in order of energy. The NGA is efficient in determining the GM, performing in a shorter time, if compared to RS and IGA. The IGA proved to be a more robust method than the others, because in addition to determining the GM, it can find the local minima in order of energy. Performing calculations on an intermediate time of RS and NGA, the IGA determined the GM as the NGA, and found structures that were not founded using RS. The GM’s of asparagine determined using the potentials PC1, PM3, AM1 and RM1 have a large structural difference. This demonstrates that different potencials used in the electronic structure calculations may lead to different results. By analyzing the structures obtained for potentials PC1, PM3, AM1 and RM1, using the IGA, it appears that there is a difference in the topology of the potential energy surface of these potentials.O presente trabalho é focado no desenvolvimento do software MGA, que tem como objetivo a determinação das estruturas de menor energia de um dado sistema molecular, utilizando o Algoritmo Genético (AG). O AG é um método de inteligência artificial que foi desenvolvido para trabalhar com a procura de soluções que melhor atendam as condições especificadas, isto é, um algoritmo que procura a melhor resposta desejada, um resultado ótimo. O MGA utiliza três técnicas: Busca Aleatória (RS), Algoritmo Genético Não-inclusivo (NGA), Algoritmo Genético Inclusivo (IGA). Este último é caracterizado por um novo tipo de estratégia evolutiva que permite em um único cálculo e um único ciclo evolucionário obter diversos mínimos da superfície de energia potencial. Para o melhor funcionamento do algoritmo, foi feita uma otimização dos parâmetros utilizados do MGA, através da metodologia de superfície de resposta. Utilizando as técnicas RS, NGA e IGA, foram determinadas 141 estruturas moleculares distintas do aminoácido asparagina. Nos cálculos de estrutura eletrônica foram considerados os métodos semi-empíricos PM3, AM1 e RM1; e potenciais DFT, com os conjuntos de base 6-311G** e PC1. O RS determinou o Mínimo Global (GM) com facilidade, para os diferentes potenciais utilizados, e se mostrou bastante útil na determinação de geometrias moleculares onde não há um rigor na determinação de mínimos locais em ordem de energia. O NGA é eficiente na determinaçãoao do GM, realizando em um menor tempo, se comparado ao RS e IGA. O IGA mostrou-se um método mais robusto que os outros, pois além de determinar o GM é possível encontrar os mínimos locais em ordem de energia. Realizando cálculos em um tempo intermediário ao RS e NGA, o IGA determinou o GM assim como o NGA, e encontrou estruturas que não foram possíveis utilizando o RS. Os GM’s da asparagina determinados utilizando os potenciais PC1, PM3, AM1 e RM1 possuem uma grande diferença estrutural. Isto demonstra que diferentes potencias utilizados nos cálculos de estrutura eletrônica podem levar a diferentes resultados. Ao analisarmos as estruturas obtidas para os potenciais PC1, PM3, AM1 e RM1, utilizando o IGA, constata-se que há uma diferença na topologia de suas superfícies de energia potencial.Submitted by JÚLIO HEBER SILVA (julioheber@yahoo.com.br) on 2017-06-26T18:28:31Z No. of bitstreams: 2 Dissertação - Rafael Carvalho Couto - 2013.pdf: 41193945 bytes, checksum: 74a020dad23640afb84a085b841b91aa (MD5) license_rdf: 0 bytes, checksum: d41d8cd98f00b204e9800998ecf8427e (MD5)Approved for entry into archive by Cláudia Bueno (claudiamoura18@gmail.com) on 2017-07-07T20:26:09Z (GMT) No. of bitstreams: 2 Dissertação - Rafael Carvalho Couto - 2013.pdf: 41193945 bytes, checksum: 74a020dad23640afb84a085b841b91aa (MD5) license_rdf: 0 bytes, checksum: d41d8cd98f00b204e9800998ecf8427e (MD5)Made available in DSpace on 2017-07-07T20:26:10Z (GMT). No. of bitstreams: 2 Dissertação - Rafael Carvalho Couto - 2013.pdf: 41193945 bytes, checksum: 74a020dad23640afb84a085b841b91aa (MD5) license_rdf: 0 bytes, checksum: d41d8cd98f00b204e9800998ecf8427e (MD5) Previous issue date: 2013-04-15application/pdfporUniversidade Federal de GoiásPrograma de Pós-graduação em Química (IQ)UFGBrasilInstituto de Química - IQ (RG)Embargada pelo autor/orientador em 22/07/2013. Autorizado o povoamento pelo autor/orientador em 22/06/2017.66369392132541515860060060078260667437411972781571700325303117195http://creativecommons.org/licenses/by-nc-nd/4.0/info:eu-repo/semantics/openAccessAlgoritmo genéticoConfôrmerosMínimo globalMínimos locaisAsparaginaGenetic algorithmConformersGlobal minimumLocal minimaAsparagineCIENCIAS EXATAS E DA TERRA::QUIMICADesenvolvimento e aplicação do software MGA (Molecular Genetic Algorithm)Development and aplication of MGA software (Molecular Genetic Algorithm)info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesisreponame:Repositório Institucional da UFGinstname:Universidade Federal de Goiás (UFG)instacron:UFGLICENSElicense.txtlicense.txttext/plain; charset=utf-82165http://repositorio.bc.ufg.br/tede/bitstreams/5c0bda5c-3155-48c0-9aa9-5d9d1ba0b006/downloadbd3efa91386c1718a7f26a329fdcb468MD51CC-LICENSElicense_urllicense_urltext/plain; charset=utf-849http://repositorio.bc.ufg.br/tede/bitstreams/74b2a5cd-004e-4404-89d6-e056b4b649f1/download4afdbb8c545fd630ea7db775da747b2fMD52license_textlicense_texttext/html; charset=utf-80http://repositorio.bc.ufg.br/tede/bitstreams/7ee452c3-df70-4d7a-b81c-b4ba8fe5ef2d/downloadd41d8cd98f00b204e9800998ecf8427eMD53license_rdflicense_rdfapplication/rdf+xml; charset=utf-80http://repositorio.bc.ufg.br/tede/bitstreams/d0d34bc9-51e9-4f1b-925b-fa9d70aacb62/downloadd41d8cd98f00b204e9800998ecf8427eMD54ORIGINALDissertação - Rafael Carvalho Couto - 2013.pdfDissertação - Rafael Carvalho Couto - 2013.pdfapplication/pdf41193945http://repositorio.bc.ufg.br/tede/bitstreams/b8245cde-8e47-4025-87b4-2db928bb7ebe/download74a020dad23640afb84a085b841b91aaMD55tede/75122017-07-07 17:26:10.039http://creativecommons.org/licenses/by-nc-nd/4.0/Acesso Abertoopen.accessoai:repositorio.bc.ufg.br:tede/7512http://repositorio.bc.ufg.br/tedeRepositório InstitucionalPUBhttp://repositorio.bc.ufg.br/oai/requesttasesdissertacoes.bc@ufg.bropendoar:2017-07-07T20:26:10Repositório Institucional da UFG - Universidade Federal de Goiás (UFG)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 |
dc.title.eng.fl_str_mv |
Desenvolvimento e aplicação do software MGA (Molecular Genetic Algorithm) |
dc.title.alternative.eng.fl_str_mv |
Development and aplication of MGA software (Molecular Genetic Algorithm) |
title |
Desenvolvimento e aplicação do software MGA (Molecular Genetic Algorithm) |
spellingShingle |
Desenvolvimento e aplicação do software MGA (Molecular Genetic Algorithm) Couto, Rafael Carvalho Algoritmo genético Confôrmeros Mínimo global Mínimos locais Asparagina Genetic algorithm Conformers Global minimum Local minima Asparagine CIENCIAS EXATAS E DA TERRA::QUIMICA |
title_short |
Desenvolvimento e aplicação do software MGA (Molecular Genetic Algorithm) |
title_full |
Desenvolvimento e aplicação do software MGA (Molecular Genetic Algorithm) |
title_fullStr |
Desenvolvimento e aplicação do software MGA (Molecular Genetic Algorithm) |
title_full_unstemmed |
Desenvolvimento e aplicação do software MGA (Molecular Genetic Algorithm) |
title_sort |
Desenvolvimento e aplicação do software MGA (Molecular Genetic Algorithm) |
author |
Couto, Rafael Carvalho |
author_facet |
Couto, Rafael Carvalho |
author_role |
author |
dc.contributor.advisor1.fl_str_mv |
Guimarães, Freddy Fernandes |
dc.contributor.advisor1Lattes.fl_str_mv |
http://lattes.cnpq.br/6780812627526129 |
dc.contributor.referee1.fl_str_mv |
Guimarães, Freddy Fernandes |
dc.contributor.referee1Lattes.fl_str_mv |
http://lattes.cnpq.br/6780812627526129 |
dc.contributor.referee2.fl_str_mv |
Neves, Jorge Luiz |
dc.contributor.referee3.fl_str_mv |
Martins, Felipe Terra |
dc.contributor.authorLattes.fl_str_mv |
http://lattes.cnpq.br/6196634849515906 |
dc.contributor.author.fl_str_mv |
Couto, Rafael Carvalho |
contributor_str_mv |
Guimarães, Freddy Fernandes Guimarães, Freddy Fernandes Neves, Jorge Luiz Martins, Felipe Terra |
dc.subject.por.fl_str_mv |
Algoritmo genético Confôrmeros Mínimo global Mínimos locais Asparagina |
topic |
Algoritmo genético Confôrmeros Mínimo global Mínimos locais Asparagina Genetic algorithm Conformers Global minimum Local minima Asparagine CIENCIAS EXATAS E DA TERRA::QUIMICA |
dc.subject.eng.fl_str_mv |
Genetic algorithm Conformers Global minimum Local minima Asparagine |
dc.subject.cnpq.fl_str_mv |
CIENCIAS EXATAS E DA TERRA::QUIMICA |
description |
This work focuses on the development of the software MGA, which aims to determine the lowest energy structures of a given molecular system, using Genetic Algorithm (GA). The GA is a method of artificial intelligence that was developed to work with finding the best solutions of the specified conditions, ie, an algorithm that seeks the best answer desired, an optimal result. The MGA uses three techniques: Random Search (RS), Noninclusive Genetic Algorithm (NGA), Inclusive Genetic Algorithm (IGA). The last one is characterized by a new type of evolutionary strategy that allows in a single calculation and a single cycle, obtain several minimum of the potential energy surface. For optimum operation of the algorithm, was made an optimization of the parameters used in MGA, through response surface methodology. Using the techniques RS, IGA and NGA, were determined 141 distinct molecular structures of the amino acid asparagine. In the electronic structure calculations were considered the semi-empirical methods PM3, AM1 and RM1; and DFT potentials, with basis sets 6-311G ** and PC1. The RS determined the Global Minimum (GM) with ease, for the different potentials used, and proved that it’s quite useful in determining molecular geometries where there is no accuracy in the determination of local minima in order of energy. The NGA is efficient in determining the GM, performing in a shorter time, if compared to RS and IGA. The IGA proved to be a more robust method than the others, because in addition to determining the GM, it can find the local minima in order of energy. Performing calculations on an intermediate time of RS and NGA, the IGA determined the GM as the NGA, and found structures that were not founded using RS. The GM’s of asparagine determined using the potentials PC1, PM3, AM1 and RM1 have a large structural difference. This demonstrates that different potencials used in the electronic structure calculations may lead to different results. By analyzing the structures obtained for potentials PC1, PM3, AM1 and RM1, using the IGA, it appears that there is a difference in the topology of the potential energy surface of these potentials. |
publishDate |
2013 |
dc.date.issued.fl_str_mv |
2013-04-15 |
dc.date.accessioned.fl_str_mv |
2017-07-07T20:26:10Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/masterThesis |
format |
masterThesis |
status_str |
publishedVersion |
dc.identifier.citation.fl_str_mv |
COUTO, R. C. Desenvolvimento e aplicação do software MGA (Molecular Genetic Algorithm). 2013. 98 f. Dissertação (Mestrado em Química) - Universidade Federal de Goiás, Goiânia, 2013. |
dc.identifier.uri.fl_str_mv |
http://repositorio.bc.ufg.br/tede/handle/tede/7512 |
dc.identifier.dark.fl_str_mv |
ark:/38995/001300000chz8 |
identifier_str_mv |
COUTO, R. C. Desenvolvimento e aplicação do software MGA (Molecular Genetic Algorithm). 2013. 98 f. Dissertação (Mestrado em Química) - Universidade Federal de Goiás, Goiânia, 2013. ark:/38995/001300000chz8 |
url |
http://repositorio.bc.ufg.br/tede/handle/tede/7512 |
dc.language.iso.fl_str_mv |
por |
language |
por |
dc.relation.eng.fl_str_mv |
Embargada pelo autor/orientador em 22/07/2013. Autorizado o povoamento pelo autor/orientador em 22/06/2017. |
dc.relation.program.fl_str_mv |
663693921325415158 |
dc.relation.confidence.fl_str_mv |
600 600 600 |
dc.relation.department.fl_str_mv |
7826066743741197278 |
dc.relation.cnpq.fl_str_mv |
1571700325303117195 |
dc.rights.driver.fl_str_mv |
http://creativecommons.org/licenses/by-nc-nd/4.0/ info:eu-repo/semantics/openAccess |
rights_invalid_str_mv |
http://creativecommons.org/licenses/by-nc-nd/4.0/ |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.publisher.none.fl_str_mv |
Universidade Federal de Goiás |
dc.publisher.program.fl_str_mv |
Programa de Pós-graduação em Química (IQ) |
dc.publisher.initials.fl_str_mv |
UFG |
dc.publisher.country.fl_str_mv |
Brasil |
dc.publisher.department.fl_str_mv |
Instituto de Química - IQ (RG) |
publisher.none.fl_str_mv |
Universidade Federal de Goiás |
dc.source.none.fl_str_mv |
reponame:Repositório Institucional da UFG instname:Universidade Federal de Goiás (UFG) instacron:UFG |
instname_str |
Universidade Federal de Goiás (UFG) |
instacron_str |
UFG |
institution |
UFG |
reponame_str |
Repositório Institucional da UFG |
collection |
Repositório Institucional da UFG |
bitstream.url.fl_str_mv |
http://repositorio.bc.ufg.br/tede/bitstreams/5c0bda5c-3155-48c0-9aa9-5d9d1ba0b006/download http://repositorio.bc.ufg.br/tede/bitstreams/74b2a5cd-004e-4404-89d6-e056b4b649f1/download http://repositorio.bc.ufg.br/tede/bitstreams/7ee452c3-df70-4d7a-b81c-b4ba8fe5ef2d/download http://repositorio.bc.ufg.br/tede/bitstreams/d0d34bc9-51e9-4f1b-925b-fa9d70aacb62/download http://repositorio.bc.ufg.br/tede/bitstreams/b8245cde-8e47-4025-87b4-2db928bb7ebe/download |
bitstream.checksum.fl_str_mv |
bd3efa91386c1718a7f26a329fdcb468 4afdbb8c545fd630ea7db775da747b2f d41d8cd98f00b204e9800998ecf8427e d41d8cd98f00b204e9800998ecf8427e 74a020dad23640afb84a085b841b91aa |
bitstream.checksumAlgorithm.fl_str_mv |
MD5 MD5 MD5 MD5 MD5 |
repository.name.fl_str_mv |
Repositório Institucional da UFG - Universidade Federal de Goiás (UFG) |
repository.mail.fl_str_mv |
tasesdissertacoes.bc@ufg.br |
_version_ |
1813816964635688960 |