A well developed conceptual estimate is based on the study of historical project cost factors and result in forecasting rapid estimates accurate cost for project feasibility studies, budgeting and financing the finished products, financial valuation of a number of alternative projects etc.
The system is very useful for construction industries, chemical industries, refinery industries, industrial plants, engineering firms and operating companies as there is a strong requirement to generate precise cost estimates for new plants, major equipment acquisitions or upgrades, large maintenance projects, new buildings, etc.
Conceptual estimating also provides great assistance to the structural engineering sectors as it looks at the performance specifications and footprint of a structure and creates a budget for all of the activities regarding steel in the structure including detailing, fabricating, painting, transporting and erecting.
There are various techniques available for conceptual cost estimation. Regression analysis, simulation, and neural networks are mostly recognized techniques that are used all through the initial project stages.
In regression analysis one can estimate the project cost with a regression model as well as a number of independent variables. Here, cost-conscious models were considered for both regression and neural network modeling. A cost conscious model seems to a model that fits the data adequately without using any unnecessary parameters.