Hydrology Newsletter

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 : https://waterandenergynexus.blogspot.com/2013/04/how-to-predict-time-dependent-variables.html Thanking you, Mrinmoy  My ResearchGate Id : Mrinmoy_Majumder Home Page:  http://www.mrinmoymajumder.com   Author of: Lecture Notes on MCDM Indian Link  ;  Global Link :

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 :

The summer season can be utilized by the pursue of research on the following few ideas. The ideas are developed based on the type of audience that means whether  B.Tech. or M.Tech, Students or Teachers, etc. students will enjoy doing these topics to complete their PG or UG requirement. Title: Short Term Rainfall forecasting by ANN-MCDM Approach Pre-requisite : Various data of climatic parameters, land use pattern of the region, cloud type and density for 1 to 5 days before the day of forecast. Justification of the Study : Rainfall can impact the output of many industrial and agricultural processes. Even the energy output from the power sector is affected by the climatic parameter. Short term rainfall forecasting is an important concept as it can help the planners of this industry to adjust their input so that the required output will remain unaffected. Brief Methodology : A widescale expert and local survey followed by a literature review have to be conducted to identify the p...

New Research Idea : Comparing Neuro-genetic,Neuro-Fuzzy and ANFIS in prediction of Soil Erodibility All the above neural hybrid models are applied in various hydrologic and hydraulic studies but such models are rarely used to predict Soil Erodibility due to the scarcity of data. But with combinatorial data matrix one can take the advantage of such models in prediction of  Soil Erosion in a watershed.