Alternative Learning Curve Models: An Analysis of Forecast Error

Abstract

Numerous learning curve models have been offered in the literature and used in practice. This paper selects five learning curve models which differ with respect to the pattern of learning assumed to exist, and investigates the forecast accuracy of the varying models under varying circumstances. The broad objectives are to identify conditions which may affect model accuracy, documenting the manner in which forecast errors for each model depend on those conditions, and suggest which of the five models may be more or less accurate under a given set of conditions. Tests are conducted using annual cost and quantity data from a large sample of major aerospace weapon system programs. Learning curve, Cost progress model, Cost estimation, Forecasting accuracy.

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Document Details

Document Type
Technical Report
Publication Date
Jan 01, 1994
Accession Number
ADA278801

Entities

People

  • O. D. Moses

Organizations

  • Naval Postgraduate School

Tags

Communities of Interest

  • Air Platforms
  • Materials and Manufacturing Processes
  • Space
  • Weapons Technologies

DTIC Thesaurus Topics

  • Abstracts
  • Accuracy
  • Aircrafts
  • Cost Analysis
  • Cost Models
  • Cost Reductions
  • Costs
  • Errors
  • Learning
  • Military Aircraft
  • Production Rate
  • Random Walk
  • Standards
  • Statistics
  • System Software
  • Systems Management
  • Weapon Systems

Readers

  • Computational Modeling and Simulation
  • Neural Network Machine Learning.

Technology Areas

  • Space