- author = "Chandrasekaran Sivapragasam and Poomalai Saravanan and Kaliappan Ganeshmoorthy and Atchutha Muhil and Sundharamoorthy Dilip and Sundarasrinivasan Saivishnu",
- title = "Mathematical Modeling of Gradually Varied Flow with Genetic Programming: A Lab-Scale Application",
- booktitle = "Information and Communication Technology for Intelligent Systems, ICTIS 2018",
- year = "2018",
- editor = "Suresh Chandra Satapathy and Amit Joshi",
- volume = "1",
- series = "SIST, volume 106",
- pages = "409--416",
- address = "Ahmedabad, India",
- month = apr # " 6-7",
- publisher = "Springer",
- keywords = "genetic algorithms, genetic programming",
- isbn13 = "978-981-13-1741-5",
-
URL = "
http://link.springer.com/chapter/10.1007/978-981-13-1742-2_40",
-
DOI = "
doi:10.1007/978-981-13-1742-2_40",
- abstract = "This study suggests how research interest can be inculcated in the undergraduate students, and advanced knowledge can be mined by extending the scope of the conventional experiments that students study in their curriculum through the use of ICT-based modeling tools. The experiment on flow over rectangular notch experiment of the Civil Engineering curriculum is taken. Conventionally, the objective of the experiment is to find the coefficient of discharge for the notch. However, here an attempt is made to redefine the objectives beyond the scope of the curriculum by modeling the flow profile past the notch. In the presence of the notch, the flow behavior gets modulated. The application of genetic programming results in a new research finding and is found to be highly useful to draw an insightful understanding of the process being studied. This study is also important in dissemination of importance of use of such data mining methods and promoting interdisciplinary research from the early stage of engineering education.",
-
notes = "Published 2019
Center for Water Technology, Department of Civil Engineering, Kalasalingam Academy of Research and Education, Krishnankoil, 626126, Tamil Nadu, India",
