Ely Salwana

35 papers receiving 886 citations

Ely Salwana's Hit Papers

Deep Learning for Stock Market Prediction 2020 · 226 citations
2260+2+4Years since publication50100150200

Peers

Ely Salwana
Comparison fields: 5 of 126
  • Management Science and Operations Research 223
  • Health Informatics 9
  • Environmental Engineering 100
  • Artificial Intelligence 165
  • Finance 51
Replace Emmanuel Pintelas with:
Emmanuel Pintelas Greece
Usha A. Kumar India
Mukta Paliwal India
Yu Song China
Shahrokh Asadi Iran
Jihoon Moon South Korea
Muhammad Muneeb Pakistan
V. Vijayakumar India
Amelia Ritahani Ismail Malaysia
J. F. Torres Spain
Ely Salwana relative to Emmanuel Pintelas Greece Emmanuel Pintelas's profile →
Citations per field
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Emmanuel Pintelas · 1×
Citations per year

Countries citing papers authored by Ely Salwana

Since Specialization
Citations

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

Fields of papers citing papers by Ely Salwana

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Ely Salwana, 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 Ely Salwana Line = papers co-authored together Ely Salwana links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 41 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Deep Learning for Stock Market Prediction
Hit paper breakdown →
2020226
2 2020104
3 201995
4 201966
5 201955
6 201949
7 201932
8 202031
9 202330
10 202028
11 202025
12 202025
13 202024
14 202019
15 202115
16 201715
17 202013
18 20219
19 20188
20
An Ontology for the Waste Management Domain
20187

About Ely Salwana

Ely Salwana is a scholar working on Information Systems, Artificial Intelligence, Environmental Engineering, Management Science and Operations Research and Management Information Systems, having authored 41 papers that have together received 923 indexed citations. Recurring topics across this work include Hydrological Forecasting Using AI (5 papers), Stock Market Forecasting Methods (4 papers), Semantic Web and Ontologies (4 papers), Energy Load and Power Forecasting (4 papers), Hydrology and Watershed Management Studies (4 papers), Big Data and Business Intelligence (3 papers), Hydrology and Sediment Transport Processes (3 papers) and Hydraulic flow and structures (3 papers). The work is most often cited by research in Management Science and Operations Research (223 citations), Health Informatics (9 citations), Environmental Engineering (100 citations), Artificial Intelligence (165 citations) and Finance (51 citations). Ely Salwana has collaborated with scholars based in Malaysia, Iran and Vietnam. Frequent co-authors include Amir Mosavi, Shahaboddin Shamshirband, S. Shahab, Mojtaba Nabipour, Pooyan Nayyeri, Kwok‐wing Chau, J.H.M. Tah, Amirhosein Mosavi, Saeed Samadianfard and Alireza Baghban. Their work appears in journals such as IEEE Access, Engineering Applications of Computational Fluid Mechanics, Measurement, Water and IEEE Sensors Journal.

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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