Skip to main content

Reposted : How to predict time dependent hydrological variables with the help of neural network ?




We all know that most of the hydrological variables are time-dependent. It changes with time.

Artificial Neural Network on the other hand has been found to perform best for time-dependent problems.

Whether there is any relationship between time-dependent variables and neural network is unknown but it can be assured that neural networks can be used to develop models for the prediction of hydrological variables with better accuracy compared to other hydrological models.

The post below depicts the methodology for the application of neural networks in the development of hydrological models.

This is reposted from my Water and Energy Nexus Blog :

Thanking you,
Mrinmoy 
My ResearchGate Id : Mrinmoy_Majumder
Author of: Lecture Notes on MCDM

Labels

Labels:

Popular posts from this blog

Seven Most Tenable Application of Artificial Intelligence on Water Resource Management Problems

AI or Artificial Intelligence is a pioneering technique that has enabled the creation of intelligent machines. or smart machines which have the power to self adapt based on the situation presented to them. It requires situations whose response is known and based on this training data set it learns the problems which it has to solve when it is ready. Due to the alarming success with AI in robotics, electronics, etc fields the same technique is now used to solve the problems of water resource management. This ppt shows the seven most notable use of AI in water resources-based problems where satisfactory improvement has encouraged the further application of the technique. View the Presentation Dr.Mrinmoy Majumder, My ResearchGate Id : Mrinmoy_Majumder Home Page: http://www.mrinmoymajumder.com   Author of: Lecture Notes on MCDM Indian Link  ; Global Link :
Read more

Introduction to Glowworm Optimization Algorithm

Overview of the Glow Worm Algorithm Explanation of the original Glow Worm Algorithm  The Hybrid Glow Worm Algorithm is an important algorithm to study and understand because of its ability to effectively solve complex optimization problems. By combining the strengths of different algorithms, it offers a flexible and adaptable solution approach that can be applied to various domains. Understanding this algorithm can help researchers and practitioners in developing efficient and effective optimization strategies for their specific problem instances.  The original Glow Worm Algorithm is a swarm intelligence-based optimization algorithm inspired by the behavior of glow worms in nature. It involves a population of virtual glow worms that interact with each other and their environment to find optimal solutions.  The algorithm uses a combination of local and global search strategies, allowing the glow worms to explore and exploit the search space effectively. Additionally, the a...
Read more