The Role of the SECoS Algorithm in Forecasting Budgeting Costs for Official Trips Orders

An official travel order is a formal letter used for work-related purposes, typically within government agencies, services, and office responsibilities. It is issued when an employee is directed to undertake assignments in a different region, outside the city, or even abroad. Planning the budget for an Official Travel Order requires financial readiness throughout the year. Therefore, it is essential to anticipate the budgeting of Official Travel Order costs, enabling effective implementation and improvement through the applications of an evolution-based artificial neural network (ANN) method. In this paper, a method is test by SECoS using parameter values: learning rate 1 is 0.31, learning rate 2 is 0.23, sensitivity
$\text{threshold}=0.03$
, and Threshold
$\text{error}=0.06$
. The obtained MAPE value is 0.00181066%.