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DC Field | Value | Language |
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dc.contributor.author | Mahalakshmi G. | |
dc.contributor.author | Rajasekaran C. | |
dc.date.accessioned | 2020-03-31T14:15:22Z | - |
dc.date.available | 2020-03-31T14:15:22Z | - |
dc.date.issued | 2019 | |
dc.identifier.citation | Lecture Notes in Civil Engineering, 2019, Vol.25, pp.659-672 | en_US |
dc.identifier.uri | 10.1007/978-981-13-3317-0_59 | |
dc.identifier.uri | http://idr.nitk.ac.in/jspui/handle/123456789/13784 | - |
dc.description.abstract | The objective of this paper is to develop a model to estimate the construction cost of a highway at early stage (conceptual phase) of a project. Cost estimation at conceptual phase is a challenge as only limited information is known. As a result, wide cost variance is eminent at the completion of project. A neural network which can aid in cost estimation is developed. Parameters that can be obtained with least effort and highly influencing on cost are chosen. Developed neural network relates overall highway construction cost described in terms of materials, duration, topography, and prevailing soil conditions. Data of 52 projects were obtained from National Highway Authority of India (NHAI). The obtained results demonstrated that a multi perceptron network with backpropagation algorithm is capable of predicting construction cost of highway with reasonable accuracy. © Springer Nature Singapore Pte Ltd. 2019. | en_US |
dc.title | Early cost estimation of highway projects in India using artificial neural network | en_US |
dc.type | Book Chapter | en_US |
Appears in Collections: | 3. Book Chapters |
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