Faculty Development Program

ANN and its utilization in modeling and Simulation


13 Jan 2020
10:00 AM

Organised by

At Conference Hall, UIT-RGPV, Bhopal

About Event,
ANN and its utilization in modeling and Simulation

To comprehend the concept of ANN and to provide a rigorous, advanced foundation in Artificial Neural Network to endow researcher working with real time data/ physical processes a tool for analyze, modeled and simulate complex data using ANN.

The Speakers

Lecture From Industries Experts

Events Details

ANN and its utilization in modeling and simulation

About Event

It is quite complex to develop a mathematical model which can map the behaviour and inter dependency of a process or system parameters. ANN is a computational technique that has the capability to model correlation between the process variables, input and output values. It enables to study complex systems without any knowledge of the exact relations governing their operation. FDP will provide the participants a rigorous, advanced foundation in Artificial Neural Network through hands on implementation of various algorithms in the field of science engineering.

The Speakers

1. Dr. Manoj Kumar, Professor and HOD Mathematics, MNNIT, Allahabad. U.P. 2. Mr. Gaurav Nema, Development Head, Puffins Software Bhopal 3. Dr. Hemant Parmar, Deptt. of Mechanical Engg. ,UEC Ujjain M.P.

Major Topic Covered

Introduction to Artificial Neural Network ANN, Problem Formulations Representations, Knowledge Representation, Understanding various models of ANN, Modeling engineering problem like Fluid flow, heat transfer, forecasting etc using ANN, Hands on Sessions Case Studies of Artificial Neural Network ANN.

Department of Petrochemical Engineering

With enormous potential for growth in the field of petrochemical sector has enkindled the idea to foster the need of specialized engineers in the field of petrochemical Engineering. In 2012, Department of Petrochemical Engineering was established in UIT, RGPV. The department run B.Tech course in the Petrochemical Engineering with an intake of 60 students. The department is equipped with laboratory facility of Mass Transfer, Reaction Engineering, Fluid Mechanics, process control etc.