Narasimhan Sundararajan

Artificial Intelligence · 2004–2015

A researcher in the Science corpus: 6 papers; trusts 33 researchers and is trusted by 22 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 38 citations into it; #7,185 of 35,345 by trust here, #9,092 by citations
• Computational Theory and Mathematics — 11 citations into it
• Control and Systems Engineering — 11 citations into it; #7,698 of 8,257 by trust here, #6,083 by citations
• Electrical and Electronic Engineering — 7 citations into it

Whom Narasimhan Sundararajan trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

1. G. Huang
2. James Kennedy
3. Nikola K. Kasabov
4. Plamen Parvanov Angelov
5. Michael C. Mozer
6. Jing J. Liang
7. Paramasivan Saratchandran
8. Jaka Demsar
9. Ponnuthurai Nagaratnam Suganthan
10. Rui Mendes

Who trusts Narasimhan Sundararajan overall

1. G. Huang
2. Hai-Jun Rong
3. Shuang Feng
4. Edwin David Lughofer
5. J. J. Rubio
6. Nan-Ying Liang
7. Gao Huang
8. Han Zou
9. Paramasivan Saratchandran
10. C. Chen

Papers from Narasimhan Sundararajan's perspective

Ordered by how strongly the researchers Narasimhan Sundararajan trusts endorse each paper. Same corpus, a different order for every researcher.

1. Learning internal representations by error propagation
2. Population structure and particle swarm performance (Proceedings of the 2002 Congress on Evolutionary Computation. CEC'02 (Cat. No.02TH8600))
3. A Cooperative approach to particle swarm optimization (IEEE Transactions on Evolutionary Computation)
4. DENFIS: dynamic evolving neural-fuzzy inference system and its application for time-series prediction (IEEE transactions on fuzzy systems)
5. The fully informed particle swarm: simpler, maybe better (IEEE Transactions on Evolutionary Computation)
6. Extreme learning machine: a new learning scheme of feedforward neural networks (2004 IEEE International Joint Conference on Neural Networks (IEEE Cat. No.04CH37541))
7. UCI Repository of machine learning databases
8. Learning capability and storage capacity of two-hidden-layer feedforward networks (IEEE Trans. Neural Networks)
9. Skeletonization: A Technique for Trimming the Fat from a Network via Relevance Assessment
10. Support Vector Regression Machines

Their papers

• Online Sequential Fuzzy Extreme Learning Machine for Function Approximation and Classification Problems (2009) — 339 citations
• Self regulating particle swarm optimization algorithm (2015) — 300 citations
• Sequential Adaptive Fuzzy Inference System (SAFIS) for nonlinear system identification and prediction (2006) — 364 citations
• A Fast and Accurate Online Sequential Learning Algorithm for Feedforward Networks (2006) — 1,906 citations
• A generalized growing and pruning RBF (GGAP-RBF) neural network for function approximation (2005) — 703 citations
• An efficient sequential learning algorithm for growing and pruning RBF (GAP-RBF) networks (2004) — 400 citations