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Electronics & ICT Academy, Telangana State, India

Metaheuristic Optimization Algorithms in Engineering @ CMR College of Engineering & Technology (Autonomous), Hyderabad

Participants Information

Participants: 71
Speakers:09
Female participants:28
Male participants:43
Participants from SC/ST category:20
Research Scholars:Nil

Lab Sessions

  • Implementation of Genetic, PSO, NN & DE Algorithm using MATLAB
  • Applications of Meta Heuristic Algorithms in Mechanical & Electrical Engineering

Topics Covered

  • Introduction to Engineering Optimization
  • Linear Programming using Simplex Method
  • Non Linear Optimization
  • Introduction to Genetic Algorithm
  • Non Linear System Identification using GA
  • Particle swarm optimization
  • Channel Equalization using PSO
  • Differential Evaluation
  • Antenna Array Synthesis Using DE
  • BAT Algorithm
  • Sine Cosine Algorithm
  • Teaching-Learning-Based Optimization (TLBO) Algorithm
  • Jaya Algorithm
  • Optimization tool box
  • Induction program, Universal Human Values
  • Convolution Neural Networks and applications to Image processing
  • Benchmarking and Evaluation of Evolutionary Algorithms: Foundations and Perspectives
  • Statistical Tests
  • Guidelines on how to publish research papers in reputed SCI Journals
  • Deep Neural Networks
  • Hybridization of Optimization Techniques with Neural Networks
  • Future trends in Optimization

Highlights

List of Speakers

Prof. Kasi Viswanadh, Associate Professor, NIT Warangal


Dr. J. Ravi Kumar, Associate Professor, NIT Warangal


Dr. Hari Kumar Voruganti, MED, NIT Warangal


Dr. Y. Chandrashekar, EED, NIT Warangal


Dr. Gopi Ram, Assistant Professor, Dept. of ECE, NIT Warangal


Dr. N. Hathi Ram, Associate Professor, VCE


Dr. Nagaraju Naik, CMRCET, Hyderabad


Dr. Farooq Husmi, Dept of ECE, NIT Warangal


Prof. Swagatham Das, Associate Professor, ISI, Kolkata




Feedback Summary

  • Effective lectures delivered by expertized resource persons.

  • Clear explosure of industrial related problems.

  • The program covered from basics to higher level of different domain problems and optimization solutions.

    • Suggestions from Participants

  • Require more hands on sessions.