Water Quality Prediction using AI and ML Algorithms
Downloads
Published
DOI:
https://doi.org/10.58414/SCIENTIFICTEMPER.2023.14.2.46Keywords:
Water pollution, Quality parameters, Water Quality Index, AI & ML AlgorithmsDimensions Badge
Issue
Section
License
Copyright (c) 2023 The Scientific Temper
This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.
Expeditious growth in industrial amelioration to support the country’s expanding population and economy has contaminated our water resources like never before. Water pollution is one of the most alarming concerns for us today. Prediction of water quality has grown in popularity in the field of water environmental science. Data-driven strategies are becoming increasingly fascinating and beneficial as we extend our understanding of water means. Data mining, which can manage the complexity within the provided data, is a direct method for exploration.Abstract
How to Cite
Downloads
Similar Articles
- Manu Narendra Dev Purohit, Deepika Yadav, Naresh Vyas, Population Studies on Snails , The Scientific Temper: Vol. 13 No. 02 (2022): The Scientific Temper
- B. Kalpana, P. Krishnamoorthy, S. Kanageswari, Anitha J. Albert, Machine learning approaches for predicting species interactions in dynamic ecosystems , The Scientific Temper: Vol. 15 No. 03 (2024): The Scientific Temper
- Moyliev Gayrat, Yunuskhodjaev Akhmadkhodja, Saidov Saidamir, Babakhanov Otabek, Mirsultanov Jakhongir, To study references and analysis of an experimental model for skin burns in rats , The Scientific Temper: Vol. 15 No. 01 (2024): The Scientific Temper
- Maya Kumari, Vikas Y Patade, Z Ahmad, TRANSGENIC APPROACH TOWARDS DEVELOPMENT OF COLD STRESS TOLERANT VEGETABLES FOR HIGH ALTITUDE AREAS , The Scientific Temper: Vol. 1 No. 01 (2010): The Scientific Temper
- Thilagavathi K, Thankamani K., P. Shunmugapriya, D. Prema, Navigating fake reviews in online marketing: Innovative strategies for authenticity and trust in the digital age , The Scientific Temper: Vol. 15 No. 03 (2024): The Scientific Temper
- Krutuja S. Gadgil, Prabodh Khampariya, Shashikant M. Bakre, Investigation of power quality problems and harmonic exclusion in the power system using frequency estimation techniques , The Scientific Temper: Vol. 14 No. 01 (2023): The Scientific Temper
- Manisha Pallvi, Carlson’s Trophic State Index of Shatiya Wetland in Gopalganj District of Bihar , The Scientific Temper: Vol. 12 No. 1&2 (2021): The Scientific Temper
- Vikas Jangra, Dr. Vikas Jangra, Vandana, Comparative study of color difference on coated and uncoated paper in digital printing , The Scientific Temper: Vol. 15 No. 01 (2024): The Scientific Temper
- Kanthalakshmi S, Nikitha M. S, Pradeepa G, Classification of weld defects using machine vision using convolutional neural network , The Scientific Temper: Vol. 14 No. 01 (2023): The Scientific Temper
- R. Gomathi, Balaji V, Sanjay R. Pawar, Ayesha Siddiqua, M. Dhanalakshmi, Ravi Rastogi, Ensuring ethical integrity and bias reduction in machine learning models , The Scientific Temper: Vol. 15 No. 01 (2024): The Scientific Temper
<< < 9 10 11 12 13 14 15 16 17 18 > >>
You may also start an advanced similarity search for this article.
