Study on the RBF neural network approach to quick cost estimate of construction projectsÃ¯Â¿Â½
2Part I Literature Review Ã¯Â¿Â½
21. Executive Summary Ã¯Â¿Â½
42. Neural Network Ã¯Â¿Â½
42.1 What is Neural Network Ã¯Â¿Â½
62.2 Why Use Neural Networks Ã¯Â¿Â½
72.3 Artificial Neural Network Architecture Ã¯Â¿Â½
82.4 How Can Artificial Neural Networks Help Us Ã¯Â¿Â½
103. Introducing Radial Basis Function Networks Ã¯Â¿Â½
124. Radial Basis Functions Ã¯Â¿Â½
135. RBF Neural Network to Cost Estimate of Construction Projects Ã¯Â¿Â½
156. Knowledge Gaps Ã¯Â¿Â½
20Part II Research Reflection Ã¯Â¿Â½Ã¯Â¿Â½
Part I Literature Review
After several weeks' carefully analysing various academic sources, these literature review has compiled a list of the most valuable to the particular study. We have considered academic literature to be that of text books and well-credited journals.
Cost estimating is essential for cost planning and budgeting and takes place in all stages of project development.
Accurately forecasting the cost of projects is vital to the survival of any business or organization (Horngren, et al., 2005). It is widely accepted that approximately 70% of the life cycle cost of a product is fixed during the early design phases (Y. Liu and A.H. Basson, 2001). Cost estimate of awaiting projects is one of the main components in the project feasibility study stage. The accuracy of cost estimate has a direct influence on the a lot of key factors, including investment decision, project design scheme, investment economic effect, the continuity of project construction and so on. Distinctly, getting an accurate cost estimate using an easy-use and quick approach is of great significance to the successful investment management and control of engineering projects (Ostwald, 2001).
In many cases cost estimating also determines whether the client will go forth and agree on the construction contract. When the project...