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dc.contributor.authorCarlson, Noah Joseph
dc.description.abstractDigitization is influencing commodity trading and agricultural markets and as they transition towards extreme liquidity, agribusiness risk exposures increase, and traditional competitive advantages diminish. In commodity origination, logistics and destination basis comprise the most volatile and determinant influences of margin. To capture a consistently higher margin and represent narrowed interior basis, agribusiness firms must manage these risks by optimizing transformations. To accomplish this, ex-ante decision-making is often necessary as forward price clairvoyance is not always prevalent, is risky, or contains premium. Modeling this spatial equilibrium is difficult through traditional reductionist and essentialist application as the overdetermined and convoluted system presents bidirectional and simultaneous price discoveries. Developments in neurobiology, technology, and Artificial Intelligence expand capabilities to represent brain behavior and unconscious inference in computational modeling. The use of Recurrent Deep Machine Learning could improve ex-ante decision accuracy within commodity trading through its nonlinear, nonlocal, nonstationary, and sequential capabilities.en_US
dc.publisherNorth Dakota State Universityen_US
dc.rightsNDSU policy 190.6.2en_US
dc.titleEx-Ante Temporal Optimization in Soybean Origination: An Overdetermined Approach Through Deep Learningen_US
dc.typeThesisen_US
dc.date.accessioned2022-05-27T16:44:31Z
dc.date.available2022-05-27T16:44:31Z
dc.date.issued2021
dc.identifier.urihttps://hdl.handle.net/10365/32608
dc.subjectagricultural economicsen_US
dc.subjectcommodity originationen_US
dc.subjectmachine learningen_US
dc.subjectsoybean analysisen_US
dc.subjectspatial equilibriumen_US
dc.subjectstorage optimizationen_US
dc.identifier.orcid0000-0001-6583-4936
dc.rights.urihttps://www.ndsu.edu/fileadmin/policy/190.pdfen_US
ndsu.degreeMaster of Science (MS)en_US
ndsu.collegeAgriculture, Food Systems and Natural Resourcesen_US
ndsu.departmentAgribusiness and Applied Economicsen_US
ndsu.programAgribusiness and Applied Economicsen_US
ndsu.advisorWilson, William


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