1. Artificial neural networks aided conceptual stage design of water harvesting structures
- Author
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Vinay Agrawal, Naveen Gupta, Ravindra Nagar, Vinay Chandwani, and A.S. Jethoo
- Subjects
Artificial neural network ,Engineering ,Decision support system ,0211 other engineering and technologies ,02 engineering and technology ,Machine learning ,computer.software_genre ,Field (computer science) ,Water harvesting structure ,021105 building & construction ,0202 electrical engineering, electronic engineering, information engineering ,Sensitivity (control systems) ,Bearing capacity ,lcsh:Science ,lcsh:Science (General) ,Parametric statistics ,business.industry ,Lift (data mining) ,Conceptual stage of design ,lcsh:Q ,020201 artificial intelligence & image processing ,Artificial intelligence ,Stage (hydrology) ,business ,computer ,lcsh:Q1-390 - Abstract
Summary The paper presents artificial neural networks (ANNs) based methodology for ascertaining the structural parameters of water harvesting structures (WHS) at the conceptual stage of design. The ANN is trained using exemplar patterns generated using an in-house MSExcel based design program, to draw a functional relationship between the five inputs design parameters namely, peak flood discharge, safe bearing capacity of strata, length of structure, height of structure and silt factor and four outputs namely, top width, bottom width, foundation depth and flood lift representing the structural parameters of WHS. The results of the study show that, the structural parameters of the WHS predicted using ANN model are in close agreement with the actual field parameters. The versatility of ANN to map complex or complex unknown relationships has been proven in the study. A parametric sensitivity study is also performed to assess the most significant design parameter. The study holistically presents a neural network based decision support tool that can be used to accurately estimate the major design parameters of the WHS at the conceptual stage of design in quick time, aiding the engineer-in-charge to conveniently forecast the budget requirements and minimize the labor involved during the subsequent phases of analysis and design.
- Published
- 2016
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