{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,5,13]],"date-time":"2025-05-13T16:24:14Z","timestamp":1747153454921,"version":"3.40.5"},"publisher-location":"Singapore","reference-count":11,"publisher":"Springer Nature Singapore","isbn-type":[{"type":"print","value":"9789811666155"},{"type":"electronic","value":"9789811666162"}],"license":[{"start":{"date-parts":[[2022,1,1]],"date-time":"2022-01-01T00:00:00Z","timestamp":1640995200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2022,1,1]],"date-time":"2022-01-01T00:00:00Z","timestamp":1640995200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2022]]},"DOI":"10.1007\/978-981-16-6616-2_12","type":"book-chapter","created":{"date-parts":[[2022,4,23]],"date-time":"2022-04-23T12:03:01Z","timestamp":1650715381000},"page":"131-139","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Investigation and Validation of Flow Characteristics Through Emergent Vegetation Patch Using Machine Learning Technique"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-6359-9116","authenticated-orcid":false,"given":"Soumen","family":"Maji","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9124-2563","authenticated-orcid":false,"given":"Apurbalal","family":"Senapati","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8219-339X","authenticated-orcid":false,"given":"Arunendu","family":"Mondal","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2022,4,24]]},"reference":[{"key":"12_CR1","doi-asserted-by":"crossref","unstructured":"Tracey, B.D., Duraisamy, K., Alonso, J.J.: A machine learning strategy to assist turbulence model development. In: 53rd AIAA Aerospace Sciences Meeting, p. 1287 (2015)","DOI":"10.2514\/6.2015-1287"},{"key":"12_CR2","doi-asserted-by":"crossref","unstructured":"Zhang, Z.J., Duraisamy, K.: Machine learning methods for data-driven turbulence modeling. In: 22nd AIAA Computational Fluid Dynamics Conference, p. 2460 (2015)","DOI":"10.2514\/6.2015-2460"},{"key":"12_CR3","doi-asserted-by":"crossref","unstructured":"Zhu, L., Zhang, W., Kou, J., Liu, Y.: Machine learning methods for turbulence modeling in subsonic flows around airfoils. Phys. Fluids 31(1), 015105 (2019)","DOI":"10.1063\/1.5061693"},{"key":"12_CR4","doi-asserted-by":"publisher","first-page":"106","DOI":"10.1017\/jfm.2019.238","volume":"870","author":"K Fukami","year":"2019","unstructured":"Fukami, K., Fukagata, K., Taira, K.: Super-resolution reconstruction of turbulent flows with machine learning. J. Fluid Mech. 870, 106\u2013120 (2019)","journal-title":"J. Fluid Mech."},{"issue":"9\u201310","key":"12_CR5","doi-asserted-by":"publisher","first-page":"567","DOI":"10.1080\/14685248.2020.1757685","volume":"21","author":"S Pandey","year":"2020","unstructured":"Pandey, S., Schumacher, J., Sreenivasan, K.R.: A perspective on machine learning in turbulent flows. J. Turbul. 21(9\u201310), 567\u2013584 (2020)","journal-title":"J. Turbul."},{"key":"12_CR6","unstructured":"Chollet, F.: Deep Learning with Python, Manning Publications, ISBN: 9781617294433, pp. 4\u20136 (2017)"},{"key":"12_CR7","doi-asserted-by":"publisher","DOI":"10.4018\/978-1-7998-7371-6","author":"A Senapati","year":"2021","unstructured":"Senapati, A., Maji, S., Mondal, A.: Limitations and implications of doubling time approach in COVID-19 infection spreading study: a gradient smoothing technique, data preprocessing, active learning, and cost perceptive approaches for resolving data imbalance. IGI Glob. (2021). https:\/\/doi.org\/10.4018\/978-1-7998-7371-6","journal-title":"IGI Glob."},{"key":"12_CR8","doi-asserted-by":"crossref","unstructured":"Senapati, A., Maji, S., Mondal, A.: Piece-wise linear regression: a new approach to predict COVID-19 spreading. In: IOP Conference Series: Materials Science and Engineering, Vol. 1020, No. 1, p. 012017. IOP Publishing (2021)","DOI":"10.1088\/1757-899X\/1020\/1\/012017"},{"key":"12_CR9","doi-asserted-by":"publisher","first-page":"41","DOI":"10.1007\/s41870-020-00552-3","volume":"13","author":"A Senapati","year":"2021","unstructured":"Senapati, A., Nag, A., Mondal, A., Maji, S.: A novel framework for COVID-19 case prediction through piecewise regression in India. Int. J. Inf. Technol. 13, 41\u201348 (2021). https:\/\/doi.org\/10.1007\/s41870-020-00552-3","journal-title":"Int. J. Inf. Technol."},{"key":"12_CR10","doi-asserted-by":"crossref","unstructured":"Deisenroth, M.P., Faisal, A.A., Ong, C.S.: Mathematics for Machine Learning, pp. 295\u2013305. Cambridge University Press (2020)","DOI":"10.1017\/9781108679930"},{"key":"12_CR11","unstructured":"L\u00e9on, B.: Online Algorithms and Stochastic Approximations. Online Learning and Neural Networks. Cambridge University Press. ISBN 978-0-52-1-65263-6"}],"container-title":["Smart Innovation, Systems and Technologies","Evolution in Computational Intelligence"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-981-16-6616-2_12","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,4,23]],"date-time":"2022-04-23T12:11:34Z","timestamp":1650715894000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-981-16-6616-2_12"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022]]},"ISBN":["9789811666155","9789811666162"],"references-count":11,"URL":"https:\/\/doi.org\/10.1007\/978-981-16-6616-2_12","relation":{},"ISSN":["2190-3018","2190-3026"],"issn-type":[{"type":"print","value":"2190-3018"},{"type":"electronic","value":"2190-3026"}],"subject":[],"published":{"date-parts":[[2022]]},"assertion":[{"value":"24 April 2022","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"We have taken permission from competent authorities to use the images\/data as given in the paper. In case of any dispute in the future, we shall be wholly responsible.","order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declaration"}}]}}