A model for early construction cost prediction is useful for all construction project participants. This paper presents a combination of process-based and data-driven model for construction cost prediction in early project phases. Bromilow’s “time-cost” model is used as process-based model and general regression neural network (GRNN) as data-driven model. GRNN gave the most accurate prediction among three prediction models using neural networks which were applied, with the mean absolute percentage error (MAPE) of about 0.73% and the coefficient of determination R2 of 99.55%. The correlation coefficient between the predicted and the actual values is 0.998. The model is designed as an integral part of the cost predicting system (CPS), whose role is to estimate project costs in the early stages. The obtained results are used as Cost Model (CM) input being both part of the Decision Support System (DSS) and part of the wider Building Management Information System (BMIS). The model can be useful for all project participants to predict construction cost in early project stage, especially in the phases of bidding and contracting when many factors, which can determine the construction project implementation, are yet unknown.
This article proposes one approach for extrapolation of necessary parameters for numerical analyses in tunnelling. The approach is named as an empirical - statical - dynamical method for extrapolation. The proposed methodology is based on combination of empirical classification rock mass methods, geophysical measurements and direct dilatometer deformability testing on a field. The analyses are prepared for purposes of investigation and design for several tunnels in Republic of Macedonia. One example for dividing of tunnel length in quasi-homogenous zones, as a basis for forming of geotechnical and numerical model that can be a basis for interaction analyses of rock - structures system and stress-strain behaviour of rock massif, is also given. The several original regressive models between rock mass quality, deformability and velocity of longitudinal seismic waves are shown
The concept of risk analysis and management has a big impact and application in various branches of society. Today in civil engineering, especially in infrastructure projects this concept represents a serious matter that should not be avoided or delayed. There are different approaches and definitions for a risk, but it is important every problem to be reviewed separately. In tunneling the uncertainties and risks are always present, so appropriate measures and management should be considered and implemented.
The investigation in rock masses in interaction with engineering structures is extremely important in a process of design of tunnels. The main problem is how to extrapolate the parameter from the zone of testing to the whole volume that is of interes for interaction analyses of the system rock mass-structure. In this article Empirical-Statical-Dynamical (ESD) methodology of extrapolation is presented. The basis of the methodology lies in combination of the results from geotechnical and geophysical testings and rock mass classification, connected with definition of adequate regressive models.
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