Mining of Conceptual Cost Estimation Knowledge with a Neuro Fuzzy System
نویسنده
چکیده
Conceptual cost estimation during the early stage of a construction project plays important role for feasibility analysis and project planning. Traditional approaches rely heavily on experienced engineers, and may cause loss of conceptual estimation knowledge of the firm. This paper proposes a method integrates a previous developed conceptual cost estimation method (PIREM) with the ANFIS neuro-fuzzy system for mining of cost estimation data. A case study of residential building projects in Mainland China is conducted to test the proposed method. The testing results show that the proposed method does not only achieve high system accuracy, but also provide many features desirable for estimators such as explicit fuzzy decision rules and graphical sensitivity analysis presentation.
منابع مشابه
Multi-Output Adaptive Neuro-Fuzzy Inference System for Prediction of Dissolved Metal Levels in Acid Rock Drainage: a Case Study
Pyrite oxidation, Acid Rock Drainage (ARD) generation, and associated release and transport of toxic metals are a major environmental concern for the mining industry. Estimation of the metal loading in ARD is a major task in developing an appropriate remediation strategy. In this study, an expert system, the Multi-Output Adaptive Neuro-Fuzzy Inference System (MANFIS), was used for estimation of...
متن کاملEstimation of coal proximate analysis factors and calorific value by multivariable regression method and adaptive neuro-fuzzy inference system (ANFIS)
The proximate analysis is the most common form of coal evaluation and it reveals the quality of a coal sample. It examines four factors including the moisture, ash, volatile matter (VM), and fixed carbon (FC) within the coal sample. Every factor is determined through a distinct experimental procedure under ASTM specified conditions. These determinations are time consuming and require a signific...
متن کاملPrediction of slope stability using adaptive neuro-fuzzy inference system based on clustering methods
Slope stability analysis is an enduring research topic in the engineering and academic sectors. Accurate prediction of the factor of safety (FOS) of slopes, their stability, and their performance is not an easy task. In this work, the adaptive neuro-fuzzy inference system (ANFIS) was utilized to build an estimation model for the prediction of FOS. Three ANFIS models were implemented including g...
متن کاملNusselt Number Estimation along a Wavy Wall in an Inclined Lid-driven Cavity using Adaptive Neuro-Fuzzy Inference System (ANFIS)
In this study, an adaptive neuro-fuzzy inference system (ANFIS) was developed to determine the Nusselt number (Nu) along a wavy wall in a lid-driven cavity under mixed convection regime. Firstly, the main data set of input/output vectors for training, checking and testing of the ANFIS was prepared based on the numerical results of the lattice Boltzmann method (LBM). Then, the ANFIS was develope...
متن کاملAn indirect adaptive neuro-fuzzy speed control of induction motors
This paper presents an indirect adaptive system based on neuro-fuzzy approximators for the speed control of induction motors. The uncertainty including parametric variations, the external load disturbance and unmodeled dynamics is estimated and compensated by designing neuro-fuzzy systems. The contribution of this paper is presenting a stability analysis for neuro-fuzzy speed control of inducti...
متن کامل