Construction Conceptual Cost Estimates Using Evolutionary Fuzzy Neural Inference Model

The conceptual estimate plays an essential role in project feasibility study. In practice, it is performed based on estimators’ experiences. However, due to the inaccuracy of cost estimate, budgeting and cost control are planned inefficiently. In order to increase the estimate accuracy, this study employed the Evolutionary Fuzzy Neural Inference Model (EFNIM) to develop an Evolutionary Construction Conceptual Cost Estimate Model (ECCCEM). The ECCCEM is designed for owners and planners to perform order of magnitude estimates and conceptual estimates. The impact factors of cost estimate are identified through literature review and interview with experts. Applying the EFNIM, the evolutional construction conceptual cost estimate model is established. Furthermore, for automating the developed model, this study integrates the Evolutionary Fuzzy Neural Inference System (EFNIS) with the developed model to construct a web-based cost estimate system. This system can assist managers to estimate the project costs accurately for different purposes.