Prediction of Biological Oxygen Demand using Artificial Intelligence & Machine Learning-Reference-Cited by-同舟云学术

Prediction of Biological Oxygen Demand using Artificial Intelligence & Machine Learning

Published:2022-11-24 Issue: Volume: Page:
ISSN:
Container-title:2022 International Conference on Augmented Intelligence and Sustainable Systems (ICAISS)
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Author:

Sunori Sandeep Kumar¹,Negi Pushpa Bhakuni²,Rana Anita³,Mittal Amit⁴,Juneja Pradeep⁵

Affiliation:

1. Graphic Era Hill University,Department of ECE,Bhimtal,India

2. Graphic Era Hill University,Department of Chemistry,Bhimtal,India

3. Kumaun University,Department of Chemistry,Nainital,India

4. Graphic Era Hill University,Department of EVS,Bhimtal,India

5. Graphic Era University,Department of ECE,Dehradun

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10010702/10010572/10010948.pdf?arnumber=10010948

Reference16 articles.

1. Development of axurographically fabricated miniaturized low-cost, high-performance microbial fuel cell and its application for sensing biological oxygen demand;xiao;2019 IEEE Sensors,2019

2. Biological oxygen demand (BOD) soft measuring based on dynamic neural network (DNN): A simulation study;han;Asian Control Conference 2009,0

3. Validation of the Streeter-Phelps Model in Matlab to predict biochemical demand for oxygen DOB and dissolved oxygen OD;maza;2020 IX International Congress of Mechatronics Engineering and Automation (CIIMA),2020

4. Biochemical oxygen demand prediction for Chaophraya river using alpha-trimmed ARIMA model

5. Compensation and Simulation of Restrictive Memory Least Square Method for BOD Soft Measurement Mechanism Model

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