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Showing 4 results for Fuzzy Model

M.h. Sebt, H. Rajaei, M.m. Pakseresht,
Volume 5, Issue 3 (9-2007)
Abstract

Project participants are becoming more aware of the high costs and risks associated with delay claims and their litigation. Among delays, weather delay has an important role in projects performed in severe environmental conditions. This research is the extension of delay analysis techniques by approving analysis of weather delays using fuzzy logic. At the presented technique, first using a fuzzy logic model calculated the delay that occurred during the activity execution after weather event then by the selected delay analysis method (Time impact analysis) and using the risk of the contractor during the contract approval together with the effect of previous delay in changing the duration of activities, analyzed weather delays in construction project. A local general contractor and governmental firms involved in a highway construction project practiced by offering their experienced and knowledge in delay analysis procedures to provide data for development and testing of the model specified for rain events. The results indicated that the presented model is in accordance with practical experiences in weather delay duration except in some circumstances that can be divided into the separated parts. It also advances the use of fuzzy logic in delay analysis procedures and becomes it more systematic special for weather delays.
U. H Issa, A. Ahmed,
Volume 12, Issue 2 (4-2014)
Abstract

Driven Precast Reinforced Concrete Piles (DPRCP) is extensively used as a foundation for bridges constructed over canals in Egypt in order to avoid the diversion of water canals. The objectives of this research include identifying the main activities of DPRCP execution in the bridge-construction industry in Egypt and the risk factors affecting them. In addition, assessment of the effects of these risk factors on the quality of activities of DPRCP. Four activities are identified in order to execute the process of construction of DPRCP. These activities include: preparing and casting piles, positioning piles and steering the driving machine, handling piles, and driving piles. Thirty one risk factors affecting the DPRCP activities execution are identified. A survey was executed in Egypt concerning probabilities of occurrence of these factors and their impacts on the quality of activities of DPRCP. In addition, a new membership function is introduced to represent the quality of activities and used in a fuzzy model for factors assessment. Results showed that the proposed membership function can be used effectively to assess the quality of activities associated with the construction of DPRCP. A list of risk factors is highlighted to show the most critical risk factors that help in preparing the quality management plan for the upcoming similar projects. The gentile distribution of data obtained for the different activities proved that the investigated risk factors for the DPRCP in this study are significant.
Farzin Kalantary, Javad Sadoghi Yazdi, Hossein Bazazzadeh,
Volume 12, Issue 3 (7-2014)
Abstract

In comparison with other geomaterials, constitutive modeling of rockfill materials and its validation is more complicated. This is principally due to the existence of more intricate phenomena such as particle crushing, as well as laboratory test limitations. These issues have necessitated developing more complex constitutive models, with many parameters. Regardless of the type of model, the calibrations of the parameters in such models are considered as one of the most important and challenging steps in the application of the model. Therefore, the need for comprehensive and rapid methods for evaluation of optimum parameters of the models is deemed necessary. In this paper, a Neuro-Fuzzy model in conjunction with Particle Swarm Optimization (PSO) is used for calibration of the twelve parameters of Hierarchical Single Surface (HISS) constitutive model based on the Disturbed State Concept (DSC). The Neuro-fuzzy system is used to provide a high-degree nonlinear regression model between the deviatoric stress and volumetric strain versus axial strain that has been obtained from consolidated drained large scale tri-axial tests on rockfill materials. The model parameters are determined in an iterative optimized loop with PSO and ANFIS such that the equations of DSC/HISS are simultaneously satisfied. Material data used in this study are gathered from the results of large tri-axial tests for two rockfill dams in Iran. It is shown that the proposed method has higher accuracy and more importantly its robustness is exhibited through test predictions. The achieved improvement is substantiated in a comparison with the more widely used "Least-Square" method.
M. Effati, M. A. Rajabi, F. Samadzadegan, Sh. Shabani,
Volume 12, Issue 3 (9-2014)
Abstract

Road transportation by way of automobiles is a very convenient means of transportation. Today, the most detrimental consequence of developing transportation systems in a country is traffic accident that places a huge financial burden on society. This paper investigates the role of information systems in transportation safety that leads to improved planning and operation of the transportation system through the application of new technologies. Current methods for identification of segments of roads with high potential of accident are based on statistical approaches. Since there are not accident records for newly built roads, these methods cannot be used for regional roads that are recently built. This paper presents a GIS based Neuro-Fuzzy modeling for identification of road hazardous zones. The results of proposed approach are compared with statistical methods. It is shown that this method is a cheaper but at the same time robust means of analyzing the level of hazard associated with each road segment under consideration, specially when data are uncertain and incomplete.

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