R. Shukla

Electrical and Electronic Engineering · 2018

A researcher in the Science corpus: 1 paper; trusts 7 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom R. Shukla trusts

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

  1. Hirotaka Koizumi (in Artificial Intelligence)
  2. Ali Keyhani (in Renewable Energy, Sustainability and the Environment)
  3. Dhruv Kapoor (in Renewable Energy, Sustainability and the Environment)
  4. Abir Chatterjee (in Renewable Energy, Sustainability and the Environment)
  5. Lian Lian Jiang (in Renewable Energy, Sustainability and the Environment)
  6. Douglas Leslie Maskell (in Renewable Energy, Sustainability and the Environment)
  7. Jagdish Chandra Patra (in Renewable Energy, Sustainability and the Environment)

Papers from R. Shukla's perspective

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

  1. Identification of Photovoltaic Source Models (IEEE transactions on energy conversion)
  2. Simulated Annealing algorithm for photovoltaic parameters identification
  3. Parameter extraction of solar cells using particle swarm optimization
  4. Parameter Estimation Method to Improve the Accuracy of Photovoltaic Electrical Model (IEEE Journal of Photovoltaics)
  5. A Calculation Method of Photovoltaic Array's Operating Point for MPPT Evaluation Based on One-Dimensional Newton–Raphson Method (IEEE transactions on industry applications)
  6. A parameter extraction technique exploiting intrinsic properties of solar cells
  7. A three diode model for industrial solar cells and estimation of solar cell parameters using PSO algorithm
  8. Parameters extraction of solar cells – A comparative examination of three methods
  9. Identification of PV solar cells and modules parameters using the genetic algorithms: Application to maximum power extraction
  10. Parameter estimation of solar cells and modules using an improved adaptive differential evolution algorithm

Their papers