Presidential Young Investigator Award-Genetic Algorithms andMachine Learning in Dynamic Systems Control
{'Code': '07020000', 'Directorate': {'Abbreviation': 'ENG', 'LongName': 'Directorate For Engineering'}, 'Division': {'Abbreviation': 'CBET', 'LongName': 'Div Of Chem, Bioeng, Env, & Transp Sys'}}
{'SignBlockName': 'Stephen C. Traugott', 'PO_EMAI': None, 'PO_PHON': None}
A three-pronged research effort will be initiated.  Four projects in            three categories, genetic algorithms, classifier (rule-learning)                systems, and fluid pipeline simulation and control, will be undertaken.         The role of dominance operators in genetic algorithms will be studied           to demonstrate their importance in non-stationary environments;                 extensions to classifier systems will be studied to enhance their               rule-learning capability when applied to dynamic system control;                stochastic interpolations in time will be studied as a new numerical            solution technique for hyperbolic partial differential equations with           possible efficiency and accuracy advantages; and a pipeline operations          laboratory will be established at the University of Alabama with its            first project targeted at advanced pipeline simulation.
{'FirstName': 'David', 'LastName': 'Goldberg', 'PI_MID_INIT': 'E', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'David E Goldberg', 'EmailAddress': 'deg@uiuc.edu', 'NSF_ID': '000332366', 'StartDate': '07/01/1985', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
{'Name': 'University of Alabama Tuscaloosa', 'CityName': 'TUSCALOOSA', 'ZipCode': '354012029', 'PhoneNumber': '2053485152', 'StreetAddress': '801 UNIVERSITY BLVD', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Alabama', 'StateCode': 'AL', 'CONGRESSDISTRICT': '07', 'CONGRESS_DISTRICT_ORG': 'AL07', 'ORG_UEI_NUM': 'RCNJEHZ83EV6', 'ORG_LGL_BUS_NAME': 'UNIVERSITY OF ALABAMA', 'ORG_PRNT_UEI_NUM': 'TWJWHYEM8T63'}
{'Name': None, 'CityName': None, 'StateCode': None, 'ZipCode': None, 'StreetAddress': None, 'CountryCode': None, 'CountryName': None, 'StateName': None, 'CountryFlag': None, 'CONGRESSDISTRICT': None, 'CONGRESS_DISTRICT_PERF': '""'}
{'Code': '1443', 'Text': 'FD-Fluid Dynamics'}
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=1984&All=true', 'xml': '8451610.xml'}