Muhammad Qamar Raza

2.3k citations
28 papers · 1.7k indexed · 2 hit papers · h-index 14

Muhammad Qamar Raza

28 papers receiving 1.7k citations

Hit Papers

On recent advances in PV output power forecast4022015202620182022200400600

Peers

Muhammad Qamar Raza
Comparison fields: 5 of 90
  • Renewable Energy, Sustainability and the Environment 496
  • Artificial Intelligence 789
  • Electrical and Electronic Engineering 1.4k
  • Energy Engineering and Power Technology 68
  • Management Science and Operations Research 237
Replace Zengqiang Mi with:
Zengqiang Mi China
Akın Taşçıkaraoğlu Türkiye
Jie Shi China
Ioannis P. Panapakidis Greece
Jesus Lago Netherlands
Saifur Rahman United States
Naran M. Pindoriya India
M. Ghofrani United States
H.M.I. Pousinho Portugal
Muhammad Qamar Raza relative to Zengqiang Mi China Zengqiang Mi's profile →
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Citations per year

Countries citing papers authored by Muhammad Qamar Raza

Since Specialization
Citations

This map shows the geographic impact of Muhammad Qamar Raza's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Muhammad Qamar Raza with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Muhammad Qamar Raza more than expected).

Fields of papers citing papers by Muhammad Qamar Raza

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Muhammad Qamar Raza. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Muhammad Qamar Raza. The network helps show where Muhammad Qamar Raza may publish in the future.

Co-authorship network

The 25 scholars most cited alongside Muhammad Qamar Raza, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Muhammad Qamar Raza Line = papers co-authored together Muhammad Qamar Raza links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 20227
2 202039
3 202013
4 201987
5 201857
6 201882
7 20175
8 201736
9 20162
10 20163
11 201670
12
A review on artificial intelligence based load demand forecasting techniques for smart grid and buildingsbreakdown →
2015726
13 20156
14 20144
15 20144
16 201414
17 201433
18 201320
19 20138
20 201219

About Muhammad Qamar Raza

Muhammad Qamar Raza is a scholar working on Energy Engineering and Power Technology, Artificial Intelligence and Electrical and Electronic Engineering, having authored 28 papers that have together received 1.7k indexed citations. Recurring topics across this work include Energy Load and Power Forecasting (20 papers), Solar Radiation and Photovoltaics (12 papers), Photovoltaic System Optimization Techniques (5 papers), Smart Grid Energy Management (4 papers), Electric Power System Optimization (4 papers), Hydrological Forecasting Using AI (3 papers), Microgrid Control and Optimization (3 papers) and Image and Signal Denoising Methods (2 papers). The work is most often cited by research in Renewable Energy, Sustainability and the Environment (496 citations), Artificial Intelligence (789 citations) and Electrical and Electronic Engineering (1.4k citations). Muhammad Qamar Raza has collaborated with scholars based in Australia, Malaysia and Pakistan. Frequent co-authors include Abbas Khosravi, N. Mithulananthan, Chandima Ekanayake, Zuhairi Baharudin, Kwang Y. Lee, Alex Summerfield, Duong Quoc Hung, Hoay Beng Gooi, Jiaming Li and Perumal Nallagownden. Their work appears in journals such as Renewable and Sustainable Energy Reviews, Applied Energy and IEEE Transactions on Power Systems.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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