Developing a Model to Estimate the Actual Productivity of Loader in Construction Projects
Keywords:
ANN, Loader, ProductivityAbstract
The estimation of productivities for earthmoving equipment in construction project is an important operation to estimate the overall cost of it, whereit helps in making an accurate schedule so it prevents the total cost from overrunning. This study aimed to develop a rigorous methodology to estimate the actual productivity for one of the most important earthmoving equipment, Loader, using artificial neural networks technique, a theoretical study was conducted to realize the concept of the actual productivity for Loader and to know how it had been predicted in an inaccurate way, in addition to that a range of influential factors which affectson it was adopted, then data about that factors has been collected for 123 construction projects inthe Syrian Coast, then it has been analyzed to know the importance of the influential factors and sorted them using SPSS software.
At the end of this research, an artificial neural network design for predicting the actual productivity forLoader has been done, after it had been trained and tested, the income layer consists of 11 variables, the network includes one hidden layer with 10 neurons, while the output layer consists of a single neuron which represents the value of the actual productivity.
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