Evaluating pump performance using laboratory observations and machine learning-Reference-Cited by-同舟云学术

Evaluating pump performance using laboratory observations and machine learning

Published:2019-04-28 Issue:sup1 Volume:27 Page:174-181
ISSN:0971-5010
Container-title:ISH Journal of Hydraulic Engineering
language:en
Short-container-title:ISH Journal of Hydraulic Engineering

Author:

Achieng Kevin O.¹^ORCID

Affiliation:

1. Department of Civil and Architectural Engineering, University of Wyoming, Laramie, WY, USA

Publisher

Informa UK Limited

Subject

Fluid Flow and Transfer Processes,Water Science and Technology,Civil and Structural Engineering,Environmental Engineering

Link

https://www.tandfonline.com/doi/pdf/10.1080/09715010.2019.1608596

Reference28 articles.

1. Prediction of side weir discharge coefficient by support vector machine technique

2. Systematic Artifacts in Support Vector Regression-Based Compound Potency Prediction Revealed by Statistical and Activity Landscape Analysis

3. ASSESSMENT OF PUMP’S PERFORMANCE IN WATER SUPPLY SYSTEMS – DATA COLLECTED FROM MULTIPLE CASE STUDIES

4. Carter, N.T. (2017). “Energy-water nexus: The water sector’s energy use claudia copeland specialist in resources and environmental policy.” www.crs.gov

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