A GA based lambda error assessment for yearly stock forecast: A manufacturing case study.

Forecasting is a method used to determine the path of future trends. Historical data is significant for any forecasting technique. Organizations utilize forecasting to determine how to allocate their resources or plan for projected payments for an upcoming period of time. This is normally based on the projected demand for the goods and services they offer. This paper will used forecasting technique by integrating genetic algorithm for lambda assessment. This paper resulted that the GA lambda assessment approach will give better predictability. [ABSTRACT FROM AUTHOR]