{"id":{"repo_id":"uiuc","oai_identifier":"oai:www.ideals.illinois.edu:2142/81683"},"canonical_url":"https://search.dev.ndltd.org/etd/uiuc/oai:www.ideals.illinois.edu:2142/81683","repository":{"repo_id":"uiuc","name":"University of Illinois - Urbana-Champaign","base_url":"https://www.ideals.illinois.edu/oai-pmh"},"display":{"title":"The Diffusion Equation Method for Global Optimization and Its Application to Magnetotelluric Geoprospecting","abstract":"In geoprospecting, the conductivity of rock is determined from its effect on electromagnetic waves. From the conductivity, we can deduce the type of rock (or oil or water) and the nature of the geological formation. Unfortunately, electromagnetic inverse problems of this kind are ill-posed. We investigate the use of the Diffusion Equation Method (DEM) for global optimization in implementing an approximate quasisolution method for determining the size, shape, and orientation of an underground deposit. We examine the theoretical underpinnings of the DEM, first discussing the concepts of smoothing and continuation and then establishing the effects of diffusion upon sinusoids and polynomials. From these foundations, we explain the effect of diffusion upon coercive functions and its implications for solving global optimization problems. We examine the robustness of the DEM and its limitations in finding the global optimizer, introduce a discrete DEM using finite differencing, and compare its cost to other global optimization methods. The main computational expense for this application is in repeatedly evaluating the objective function, which fortunately can be done in a highly parallel manner. We discuss our parallel implementation of the magnetotelluric geoprospecting objective function and discrete DEM, and analyze the performance and scalability of our approach.","abstract_html":"In geoprospecting, the conductivity of rock is determined from its effect on electromagnetic waves. From the conductivity, we can deduce the type of rock (or oil or water) and the nature of the geological formation. Unfortunately, electromagnetic inverse problems of this kind are ill-posed. We investigate the use of the Diffusion Equation Method (DEM) for global optimization in implementing an approximate quasisolution method for determining the size, shape, and orientation of an underground deposit. We examine the theoretical underpinnings of the DEM, first discussing the concepts of smoothing and continuation and then establishing the effects of diffusion upon sinusoids and polynomials. From these foundations, we explain the effect of diffusion upon coercive functions and its implications for solving global optimization problems. We examine the robustness of the DEM and its limitations in finding the global optimizer, introduce a discrete DEM using finite differencing, and compare its cost to other global optimization methods. The main computational expense for this application is in repeatedly evaluating the objective function, which fortunately can be done in a highly parallel manner. We discuss our parallel implementation of the magnetotelluric geoprospecting objective function and discrete DEM, and analyze the performance and scalability of our approach.","abstract_has_math":false,"creators":["Hartman-Baker, Rebecca Jean"],"institution":"University of Illinois at Urbana-Champaign","degree_name":"Ph.D.","degree_level":"Dissertation","degree_discipline":"Computer Science","degree_department":null,"school":null,"contributors":["Heath, Michael T."],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2015,"date_issued":"2015-09-25T20:20:00Z","date_published":"2015-09-25T20:20:00Z","updated_at":"2026-07-22T22:26:16Z","subjects":["Computer Science"],"languages":["eng"],"rights":[],"rights_urls":[],"identifier_entries":[{"key":"dc:identifier","label":"Identifier","values":["(MiAaPQ)AAI3199014"],"render_values":[{"text":"(MiAaPQ)AAI3199014","href":null,"code":true}]}]},"links":{"outbound_url":"http://hdl.handle.net/2142/81683","outbound_label":"Handle","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Heath, Michael T."]},{"key":"dc:creator","label":"Author","values":["Hartman-Baker, Rebecca Jean"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date","label":"Dc Date","values":["2015-09-25T20:20:00Z","10000-01-01","2005"]},{"key":"dc:type","label":"Dc Type","values":["text"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Computer Science"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Dissertation"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Ph.D."]},{"key":"thesis:institution_name","label":"Thesis Institution Name","values":["University of Illinois at Urbana-Champaign"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Computer Science"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language","label":"Dc Language","values":["eng"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["http://hdl.handle.net/2142/81683","(MiAaPQ)AAI3199014"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["In geoprospecting, the conductivity of rock is determined from its effect on electromagnetic waves. From the conductivity, we can deduce the type of rock (or oil or water) and the nature of the geological formation. Unfortunately, electromagnetic inverse problems of this kind are ill-posed. We investigate the use of the Diffusion Equation Method (DEM) for global optimization in implementing an approximate quasisolution method for determining the size, shape, and orientation of an underground deposit. We examine the theoretical underpinnings of the DEM, first discussing the concepts of smoothing and continuation and then establishing the effects of diffusion upon sinusoids and polynomials. From these foundations, we explain the effect of diffusion upon coercive functions and its implications for solving global optimization problems. We examine the robustness of the DEM and its limitations in finding the global optimizer, introduce a discrete DEM using finite differencing, and compare its cost to other global optimization methods. The main computational expense for this application is in repeatedly evaluating the objective function, which fortunately can be done in a highly parallel manner. We discuss our parallel implementation of the magnetotelluric geoprospecting objective function and discrete DEM, and analyze the performance and scalability of our approach.","Made available in DSpace on 2015-09-25T20:20:00Z (GMT). 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From the conductivity, we can deduce the type of rock (or oil or water) and the nature of the geological formation. Unfortunately, electromagnetic inverse problems of this kind are ill-posed. We investigate the use of the Diffusion Equation Method (DEM) for global optimization in implementing an approximate quasisolution method for determining the size, shape, and orientation of an underground deposit. We examine the theoretical underpinnings of the DEM, first discussing the concepts of smoothing and continuation and then establishing the effects of diffusion upon sinusoids and polynomials. From these foundations, we explain the effect of diffusion upon coercive functions and its implications for solving global optimization problems. We examine the robustness of the DEM and its limitations in finding the global optimizer, introduce a discrete DEM using finite differencing, and compare its cost to other global optimization methods. The main computational expense for this application is in repeatedly evaluating the objective function, which fortunately can be done in a highly parallel manner. We discuss our parallel implementation of the magnetotelluric geoprospecting objective function and discrete DEM, and analyze the performance and scalability of our approach.","Made available in DSpace on 2015-09-25T20:20:00Z (GMT). No. of bitstreams: 2 license.txt: 4848 bytes, checksum: 96035ab3f5e1c23cc7138a224ce498bd (MD5) 3199014.pdf: 2133196 bytes, checksum: fa22acdf027d1dc2c6e6174f8073c170 (MD5) Previous issue date: 2005","Embargo set by: Seth Robbins for item 82964 Lift date: Forever Reason: Restricted to the U of I community idenfinitely during batch ingest of legacy ETDs","Restricted to the U of I community idenfinitely during batch ingest of legacy ETDs","U of I Only","85 p.","Thesis (Ph.D.)--University of Illinois at Urbana-Champaign, 2005."],"dc:identifier":["http://hdl.handle.net/2142/81683","(MiAaPQ)AAI3199014"],"dc:language":["eng"],"dc:subject":["Computer Science"],"dc:title":["The Diffusion Equation Method for Global Optimization and Its Application to Magnetotelluric Geoprospecting"],"dc:type":["text"],"thesis:degree_discipline":["Computer Science"],"thesis:degree_level":["Dissertation"],"thesis:degree_name":["Ph.D."],"thesis:institution_name":["University of Illinois at Urbana-Champaign"]},"updated_at":"2026-07-22T22:26:16Z"}