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• W2558809944 abstract "The deterministic approach to estimating the production rate of a construction operation assumes constant midpoint physical attributes without addressing the effect of randomness of job conditions. On the other hand, most simulation models bypass physical factors and rely on second-order inputs of probability distributions of task times, the judgements of which have been cited as difficult for users to make. This paper presents an alternative approach to production estimation, based on simulating directly the effects of changing job factors on task times, while addressing the probabilistic nature of construction. The neural network model is used as the computing mechanism for determining the cycle times of the equipment in given conditions and provides the basis for estimation. The obtained times are then fed directly into a discrete-event simulation model to simulate the process and establish the production capacity of the system as constrained by first-order factors. The approach is illustrated using a hypothetical excavating and hauling operation while the object-oriented programming technique is used to implement the computing procedure." @default.
• W2558809944 created "2016-12-08" @default.
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• W2558809944 date "1999-01-01" @default.
• W2558809944 modified "2023-09-26" @default.
• W2558809944 title "SIMULATION OF CONSTRUCTION OPERATION WITH DIRECT INPUTS OF PHYSICAL FACTORS Simulation with first-order factors" @default.
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