Optimizing Water Distribution Pump Scheduling with SVM-Based Machine Learning Using IoT Sensor Data-Reference-Cited by-同舟云学术

Optimizing Water Distribution Pump Scheduling with SVM-Based Machine Learning Using IoT Sensor Data

Published:2023-08-18 Issue: Volume: Page:
ISSN:
Container-title:2023 Second International Conference On Smart Technologies For Smart Nation (SmartTechCon)
language:
Short-container-title:

Author:

Chandra S Basavaraddi Chethan¹,Roy Choudri Dr. Subramani²,Amarnath J Jegan³,Malathi N.⁴,Muthukannan K.⁵

Affiliation:

1. Kalpataru Institute of Technology,Department of Computer Science and Engineering,Tiptur, Tumkur,Karnataka,India

2. Vsardhaman College of Engineering,Department of Computer Science and Engineering,Hyderabad,Telangana,India

3. Sri Sairam Engineering College,Department of Computer Science and Engineering,Chennai,Tamil Nadu,India

4. Saveetha University,Saveetha School of Engineering, Saveetha Institute of Medical and Technical Sciences,Department of Computer Science and Engineering,Chennai,Tamil Nadu,India

5. Sri Shanmugha College of Engineering and Technology,Department of Information Technology,Salem,Tamil Nadu,India

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10391093/10391094/10391295.pdf?arnumber=10391295

Reference15 articles.

1. Optimal Water Supply Scheduling Mechanisms using Bio-Inspired Algorithms for IoT-based Smart Water Distribution Network

2. Improving energy efficiency in water supply systems with pump scheduling optimization

3. Optimal Pump Control for Water Distribution Networks via Data-Based Distributional Robustness

4. Data-Driven Solution for Optimal Pumping Units Scheduling of Smart Water Conservancy

5. Secure Communication in IoT-enabled Embedded Systems for Military Applications using Encryption

Cited by 2 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Research on efficiency simulation model of pumping stations based on data-driven methods;Energy Reports;2024-12

2. ML Based Valve Regulation for Optimal Water Relies Based on Root Zone Soil Moisture;2024 International Conference on Advances in Data Engineering and Intelligent Computing Systems (ADICS);2024-04-18