Shunmuga Velayutham
Shunmuga Velayutham
Associate Professor of Computer Science, Amrita Vishwa Vidyapeetham
Verified email at cb.amrita.edu
Title
Cited by
Cited by
Year
Asymmetric subsethood-product fuzzy neural inference system (ASuPFuNIS)
CS Velayutham, S Kumar
IEEE Transactions on Neural Networks 16 (1), 160-174, 2005
422005
A comparative performance analysis of differential evolution and dynamic differential evolution variants
G Jeyakumar, CS Velayutham
2009 World Congress on Nature & Biologically Inspired Computing (NaBIC), 463-468, 2009
222009
Distributed mixed variant differential evolution algorithms for unconstrained global optimization
G Jeyakumar, CS Velayutham
Memetic Computing 5 (4), 275-293, 2013
162013
Distributed heterogeneous mixing of differential and dynamic differential evolution variants for unconstrained global optimization
G Jeyakumar, CS Velayutham
Soft Computing 18 (10), 1949-1965, 2014
142014
An empirical performance analysis of differential evolution variants on unconstrained global optimization problems
G Jeyakumar, C Shunmuga Velayutham
International Journal of Computer Information Systems and Industrial …, 2010
142010
Empirical study on migration topologies and migration policies for island based distributed differential evolution variants
G Jeyakumar, CS Velayutham
International Conference on Swarm, Evolutionary, and Memetic Computing, 29-37, 2010
112010
An empirical comparison of differential evolution variants on different classes of unconstrained global optimization problems
G Jeyakumar, CS Velayutham
2009 World Congress on Nature & Biologically Inspired Computing (NaBIC), 866-871, 2009
112009
Differential evolution based on-line feature analysis in an asymmetric subsethood product fuzzy neural network
CS Velayutham, S Kumar
International Conference on Neural Information Processing, 959-964, 2004
102004
Some applications of an asymmetric subsethood product fuzzy neural inference system
CS Velayutham, S Kumar
The 12th IEEE International Conference on Fuzzy Systems, 2003. FUZZ'03. 1 …, 2003
92003
A crowdsourcing-based platform for better governance
V Chandrasekaran, SV Rajan, RK Vasani, A Menon, PB Sivakumar, ...
Proceedings of the International Conference on Soft Computing Systems, 519-527, 2016
82016
A comparative study on theoretical and empirical evolution of population variance of differential evolution variants
G Jeyakumar, CS Velayutham
Asia-Pacific Conference on Simulated Evolution and Learning, 75-79, 2010
82010
Evolutionary subsethood product fuzzy neural network
CS Velayutham, S Paul, S Kumar
AFSS International Conference on Fuzzy Systems, 274-280, 2002
72002
An investigation on mixing heterogeneous differential evolution variants in a distributed framework
S Thangavelu, CS Velayutham
International Journal of Bio-Inspired Computation 7 (5), 307-320, 2015
62015
A study on genetic algorithm based video abstraction system
DKA Raju, CS Velayutham
2009 World Congress on Nature & Biologically Inspired Computing (NaBIC), 878-883, 2009
62009
Towards effective design of neuro-fuzzy systems
CS Velayutham
Ph. D. dissertation, 2005
62005
Teaching computational thinking to entry-level undergraduate engineering students at amrita university
CK Shyamala, CS Velayutham, L Parameswaran
2017 IEEE Global Engineering Education Conference (EDUCON), 1731-1734, 2017
52017
T {h} inker: A Physical Computing Tool Kit for Computational Thinking
VA Narayanan, CK Shyamala, CS Velayutham
2018 IEEE 18th International Conference on Advanced Learning Technologies …, 2018
42018
Is differential evolution sensitive to pseudo random number generator quality?–an investigation
L Rajashekharan, CS Velayutham
Intelligent Systems Technologies and Applications, 305-313, 2016
42016
Hybridizing differential evolution variants through heterogeneous mixing in a distributed framework
G Jeyakumar, CS Velayutham
Hybrid Soft Computing Approaches, 107-151, 2016
42016
Theoretical Analysis of Expected Population Variance Evolution for a Differential Evolution Variant
S Thangavelu, G Jeyakumar, RM Balakrishnan, CS Velayutham
Computational Intelligence in Data Mining-Volume 2, 403-416, 2015
42015
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