Five Most Used Machine Learning Techniques in Hydroinformatics
Hydroinformatics is the engineering of how AI,ML and data science can be utilized in water resources.
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1) ELECTRE : ELIMINATION AND CHOICE TRANSLATING REALITY 2)FMAE : FAILURE MODE EFFECTS ANALYSIS 3)MAUT : MULTI ATTRIBUTE UTILITY THEORY 4&5)PROMETHEE : PREFERENCE RANKING ORGANIZATION METHOD FOR ENRICHMENT EVALUATION (One and Two) 6)RA : RELIABILITY ANALYSIS 7)WSM : WEIGHTED SUM METHOD 8)WPM : WEIGHTED PRODUCT METHOD 9)DELPHI Method All these are free video tutorials. For case studies and project ideas please upgrade to Paid Member. Click here to procure in INR: Other than INR : Click here You may also like : HydroGeek: The newsletter for researchers of water resources https://hydrogeek.substack.com/ Baipatra VSC: Enroll for online courses for Free http://baipatra.ws Energy in Style: Participate in Online Internships for Free http://energyinstyle.website Innovate S: Online Shop for Water Researchers https://baipatra.stores.instamojo.com/ Call for Paper: International Journal of HydroClimatic Engineering http://energyinstyle.website/journals/ Hydro Geek Newsletter Edition...
AI & ML modeling application is now widespread in water resource development studies. But due to the uncertainty in water parameters, much more innovation is required for their practical applications In recent years like all the other fields of studies, the application of Artificial Intelligence and Machine Learning (AI&ML) on water resource development projects has increased manifold. For example : Sukanya, S., and Sabu Joseph. " Climate change impacts on water resources: An overview ." Visualization Techniques for Climate Change with Machine Learning and Artificial Intelligence (2023): 55-76. Kommadi, Bhagvan. " AI and ML Applications: 5G and 6G ." (2023). Joseph, Kiran, Ashok K. Sharma, Rudi van Staden, P. L. P. Wasantha, Jason Cotton, and Sharna Small. " Application of Software and Hardware-Based Technologies in Leaks and Burst Detection in Water Pipe Networks: A Literature Review ." Water 15, no. 11 (2023): 2046. Yurtsever, Mustafa, and E. M...
A drought prediction model is a computational system designed to forecast the likelihood and severity of future drought events by analyzing historical climate data, including precipitation, temperature, soil moisture, and other relevant environmental factors, using statistical and machine learning techniques to identify patterns and trends that can indicate potential drought conditions. These models aim to provide early warning systems, allowing water management authorities and communities to prepare for potential water shortages and take proactive measures to mitigate the impacts of drought. Click here to learn more. You may also like : HydroGeek: The newsletter for researchers of water resources https://hydrogeek.substack.com/ Baipatra VSC: Enroll for online courses for Free http://baipatra.ws Energy in Style: Participate in Online Internships for Free http://energyinstyle.website Innovate S: Online Shop for Water Researchers https://baipatra.stores.instamojo.com/ Call for Pape...