Ali Fiaz

1.3k citations
7 papers · 972 indexed · 1 hit paper · h-index 7
Topics
Stock Market Forecasting Methods (4 papers)Energy Load and Power Forecasting (3 papers)Image and Signal Denoising Methods (2 papers)
Journals
IEEE AccessEnergiesEspace ÉTS (ETS)

In The Last Decade

Ali Fiaz

7 papers receiving 923 citations

Hit Papers

Optimal Deep Learning LSTM Model for Electric Load Foreca...20182026202020232018200400600

Peers

Ali Fiaz
Comparison fields: 5 of 106
  • Electrical and Electronic Engineering 608
  • Artificial Intelligence 243
  • Management Science and Operations Research 224
  • Building and Construction 178
  • Environmental Engineering 116
Replace Heng Shi with:
Heng Shi United Kingdom
Minghao Xu United Kingdom
Guo‐Feng Fan Taiwan
J. F. Torres Spain
Xueheng Qiu Singapore
Jihoon Moon South Korea
Grzegorz Dudek Poland
Sinvaldo Rodrigues Moreno Brazil
Stephen Haben United Kingdom
Ioannis P. Panapakidis Greece
Ali Fiaz relative to Heng Shi United Kingdom Heng Shi's profile →
Citations per field
00.5×1.5×
Heng Shi · 1×
Citations per year

Countries citing papers authored by Ali Fiaz

Since Specialization
Citations

This map shows the geographic impact of Ali Fiaz'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 Ali Fiaz with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ali Fiaz more than expected).

Fields of papers citing papers by Ali Fiaz

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Ali Fiaz. 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 Ali Fiaz. The network helps show where Ali Fiaz may publish in the future.

Co-authorship network of co-authors of Ali Fiaz

This figure shows the co-authorship network connecting the top 25 collaborators of Ali Fiaz. A scholar is included among the top collaborators of Ali Fiaz based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Ali Fiaz. Ali Fiaz is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

7 of 7 papers shown
#WorkIndexed citations
1 178
2 6
3 60
4 8
5 60
6
Optimal Deep Learning LSTM Model for Electric Load Forecasting using Feature Selection and Genetic Algorithm: Comparison with Machine Learning Approaches †breakdown →
646
7 14

About Ali Fiaz

Ali Fiaz is a scholar working on Management Science and Operations Research, Transportation and Orthopedics and Sports Medicine, having authored 7 papers that have together received 972 indexed citations. Recurring topics across this work include Stock Market Forecasting Methods (4 papers), Energy Load and Power Forecasting (3 papers) and Image and Signal Denoising Methods (2 papers). The work is most often cited by research in Management Science and Operations Research (224 citations), Building and Construction (178 citations) and Electrical and Electronic Engineering (608 citations). Ali Fiaz has collaborated with scholars based in United Arab Emirates, Canada and Zimbabwe. Frequent co-authors include Ali Ouni, Mohamed Adel Serhani, Salah Bouktif, Salah Bouktif, Mamoun Awad, Abroon Qazi and Muhammad Tahir Khan. Their work appears in journals such as IEEE Access, Energies and Espace ÉTS (ETS).

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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