Mukesh Tiwari

Environmental Engineering · 2014–2019

A researcher in the Science corpus: 3 papers; trusts 25 researchers and is trusted by 3 researchers here, as inferred from the citation graph.

Subfields

• Environmental Engineering — 44 citations into it; #3,681 of 5,479 by trust here, #2,867 by citations
• Electrical and Electronic Engineering — 26 citations into it; #10,662 of 16,539 by trust here, #10,438 by citations
• Global and Planetary Change — 24 citations into it; #6,573 of 10,225 by trust here, #6,762 by citations
• Water Science and Technology — 24 citations into it
• Artificial Intelligence — 23 citations into it
• Ocean Engineering — 9 citations into it
• Statistics and Probability — 6 citations into it

Whom Mukesh Tiwari trusts overall

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

1. Jan Adamowski
2. Stéphane Mallat
3. Ozgur Kisi
4. Ingrid Daubechies
5. Holger R. Maier
6. Charles M. Bishop
7. D. Nalley
8. Vladimir Naumovich Vapni
9. C. Wu
10. Wensheng Wang

Who trusts Mukesh Tiwari overall

1. Anurag Malik
2. Ravinesh C. Deo
3. Mohammad Ali Ghorbani

Papers from Mukesh Tiwari's perspective

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

1. The Nature of Statistical Learning Theory
2. Neural Networks for Pattern Recognition
3. Statistical Learning Theory
4. Neural networks for the prediction and forecasting of water resource variables: a review of modelling issues and applications (Environmental Modelling & Software)
5. ImageNet classification with deep convolutional neural networks
6. A Theory for Multiresolution Signal Decomposition: The Wavelet Representation
7. A wavelet tour of signal processing
8. An Algorithm for Least-Squares Estimation of Nonlinear Parameters
9. Gradient-based learning applied to document recognition
10. Development of a coupled wavelet transform and neural network method for flow forecasting of non-perennial rivers in semi-arid watersheds.

Their papers

• Forecasting effective drought index using a wavelet extreme learning machine (W-ELM) model (2017) — 220 citations
• Coupling the maximum overlap discrete wavelet transform and long short-term memory networks for irrigation flow forecasting (2019) — 97 citations
• Wavelet Bootstrap Multiple Linear Regression Based Hybrid Modeling for Daily River Discharge Forecasting (2014) — 72 citations