Chandrasekar Ravi

Orcid: 0000-0003-0212-4173

According to our database1, Chandrasekar Ravi authored at least 13 papers between 2017 and 2026.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

Book  In proceedings  Article  PhD thesis  Dataset  Other 

Links

On csauthors.net:

Bibliography

2026
Optimization of Selective Disassembly Sequence Planning for Waste Electrical and Electronic Equipment Using a Hybrid Dual-Advantage Reinforcement Learning Approach.
Qual. Reliab. Eng. Int., 2026

2025
A Novel Deep Reinforcement Learning Approach for Stability-Based Parallel Disassembly Sequence Planning Problem.
SN Comput. Sci., March, 2025

2024
An Optimal Disassembly Sequence Planning for Complex Products using Enhanced Deep Reinforcement Learning Framework.
SN Comput. Sci., June, 2024

A study of object recognition and tracking techniques for augmented reality applications.
Int. J. Comput. Vis. Robotics, 2024

A novel reinforcement learning framework for disassembly sequence planning using Q-learning technique optimized using an enhanced simulated annealing algorithm.
Artif. Intell. Eng. Des. Anal. Manuf., 2024

2022
Driver Identification Using Optimized Deep Learning Model in Smart Transportation.
ACM Trans. Internet Techn., November, 2022

Bitcoin price prediction using optimized multiplicative long short term memory with attention mechanism using modified cuckoo search optimization.
Concurr. Comput. Pract. Exp., 2022

2021
Study of Swarm Intelligence Algorithms for Optimizing Deep Neural Network for Bitcoin Prediction.
Int. J. Swarm Intell. Res., 2021

Exponential Moving Average Modelled Particle Swarm Optimization Algorithm for Efficient Disassembly Sequence Planning towards Practical Feasibility.
Int. J. Perform. Eng., 2021

2020
Fuzzy Crow Search Algorithm-Based Deep LSTM for Bitcoin Prediction.
Int. J. Distributed Syst. Technol., 2020

2018
BGFS: Design and Development of Brain Genetic Fuzzy System for Data Classification.
J. Intell. Syst., 2018

Image Classification Using Deep Learning and Fuzzy Systems.
Proceedings of the Intelligent Systems Design and Applications, 2018

2017
BSFS: Design and Development of Exponential Brain Storm Fuzzy System for Data Classification.
Int. J. Uncertain. Fuzziness Knowl. Based Syst., 2017


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