Report of Investigations 9339: Genetic Algorithm Applied to Least Squares Curve Fitting

Details

• Journal Article:
  Tuscaloosa, AL: U.S. Department of the Interior, Bureau of Mines, RI 9339
• Personal Author:
  Karr, Charles L. ; Scheiner, Bernard J. ; Stanley, Donald A.
• Description:
  The U.S. Bureau of Mines is investigating the use of genetic algorithms (ga's) for solving optimization problems. This computer search technique, based on the mechanics of natural genetics, was used to perform simple least-squares curve fitting. Three examples are presented in which a ga manipulates binary coded strings to produce near-optimal solutions to least-squares curve-fitting problems after having viewed only a small portion of the search space. The examples include fitting data to the equation of a line, the equation of a parabola, and the ree-eyring equation. [Description provided by NIOSH]
• Subjects:
  Mining Occupational Health Safety
• Keywords:
  Optimization; Data-smoothing; Parabolas; Lines-geometry; Data-processing; Curve-fitting; Least-squares-method; Ree-Eyring-equation; Genetic-algorithms
• Source:
  Tuscaloosa, AL: U.S. Department of the Interior, Bureau of Mines, RI 9339, 1991 Jan; :1-8
• Series:
  NIOSH Numbered Publications   ; Mining Publications  
• Subseries:
  Report of Investigations
• Document Type:
  Text
• Genre:
  Report
• Place as Subject:
  Alabama ; OSHA Region 4
• CIO:
  National Institute for Occupational Safety and Health (NIOSH)
• Division:
  TURC - Tuscaloosa Research Center
• Topic:
  Workplace Safety & Health
• Location:
  North America
• Pages in Document:
  14 pdf pages
• NIOSHTIC Number:
  nn:10008480
• NTIS Accession Number:
  PB91-200527
• Federal Fiscal Year:
  1991
• Peer Reviewed:
  False
• Collection(s):
  National Institute for Occupational Safety and Health
• Main Document Checksum:
  urn:sha-512:57adfcd7e3db8a3d158fdc94f926438a228871e5282f2b08984158ef48dc459828a931829c105b1228bb20461ab482ab12e4c91cd2dda1cb03627d8fe13632ba
• Download URL:
  https://stacks.cdc.gov/view/cdc/10511/cdc_10511_DS1.pdf
• File Type:
  [PDF - 691.47 KB ]