Construction Conceptual Cost Estimates Using Evolutionary Fuzzy Neural Inference Model
نویسندگان
چکیده
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.
منابع مشابه
Evolutionary Fuzzy Hybrid Neural Network for Conceptual Cost Estimates in Construction Projects
Conceptual cost estimates are important to project feasibility studies, even the final project success. The estimates provide significant information for project evaluations, engineering designs, cost budgeting and cost management. This study proposes an artificial intelligence approach, the evolutionary fuzzy hybrid neural network (EFHNN), to improve precision of conceptual cost estimates. The...
متن کاملConceptual cost estimates using evolutionary fuzzy hybrid neural network for projects in construction industry
Conceptual cost estimates are important to project feasibility studies and impact upon final project success. Such estimates provide significant information that can be used in project evaluations, engineering designs, cost budgeting and cost management. This study proposes an artificial intelligence approach, the evolutionary fuzzy hybrid neural network (EFHNN), to improve conceptual cost esti...
متن کاملA Neural Network Model Based on Support Vector Machine for Conceptual Cost Estimation in Construction Projects
Estimation of the conceptual costs in construction projects can be regarded as an important issue in feasibility studies. This estimation has a major impact on the success of construction projects. Indeed, this estimation supports the required information that can be employed in cost management and budgeting of these projects. The purpose of this paper is to introduce an intelligent model to im...
متن کاملModeling environmental indicators for land leveling, using Artificial Neural Networks and Adaptive Neuron-Fuzzy Inference System
Land leveling is one of the most important steps in soil preparation and cultivation. Although land leveling with machines requires considerable amount of energy, it delivers a suitable surface slope with minimal soil deterioration as well as damage to plants and other organisms in the soil. Notwithstanding, in recent years researchers have tried to reduce fossil fuel consumption and its delete...
متن کاملModeling environmental indicators for land leveling, using Artificial Neural Networks and Adaptive Neuron-Fuzzy Inference System
Land leveling is one of the most important steps in soil preparation and cultivation. Although land leveling with machines requires considerable amount of energy, it delivers a suitable surface slope with minimal soil deterioration as well as damage to plants and other organisms in the soil. Notwithstanding, in recent years researchers have tried to reduce fossil fuel consumption and its delete...
متن کامل