Morad Behandish

33 papers receiving 339 citations

Peers

Morad Behandish
Comparison fields: 5 of 48
  • Industrial and Manufacturing Engineering 146
  • Automotive Engineering 115
  • Civil and Structural Engineering 141
  • Mechanical Engineering 105
  • Ocean Engineering 40
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Countries citing papers authored by Morad Behandish

Since Specialization
Citations

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

Fields of papers citing papers by Morad Behandish

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 15 scholars most cited alongside Morad Behandish, 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 Morad Behandish Line = papers co-authored together Morad Behandish links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 34 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201861
2 202044
3 201438
4 202236
5 201933
6 201916
7
Real-time pump scheduling using genetic algorithm and artificial neural network based on graphics processing unit
201211
8 201911
9 201510
10 201510
11 20129
12 20219
13 20229
14 20219
15
Comparing methods of parallel genetic optimization for pump scheduling using hydraulic model and GPU-based ANN meta-model
20127
16 20165
17 20135
18 20224
19 20233
20 20133

About Morad Behandish

Morad Behandish is a scholar working on Industrial and Manufacturing Engineering, Civil and Structural Engineering, Automotive Engineering, Mechanical Engineering and Computational Mechanics, having authored 34 papers that have together received 353 indexed citations. Recurring topics across this work include Manufacturing Process and Optimization (12 papers), Additive Manufacturing and 3D Printing Technologies (6 papers), Water Systems and Optimization (5 papers), Topology Optimization in Engineering (5 papers), Composite Material Mechanics (4 papers), Water resources management and optimization (3 papers), Protein Structure and Dynamics (3 papers) and Teleoperation and Haptic Systems (3 papers). The work is most often cited by research in Industrial and Manufacturing Engineering (146 citations), Automotive Engineering (115 citations), Civil and Structural Engineering (141 citations), Mechanical Engineering (105 citations) and Ocean Engineering (40 citations). Morad Behandish has collaborated with scholars based in United States, South Korea and Sweden. Frequent co-authors include Saigopal Nelaturi, Amir M. Mirzendehdel, Johan de Kleer, Zheng Yi Wu, Aaditya Chandrasekhar, Krishnan Suresh, Kazem Kazerounian, Ilenia Battiato, Horea Ilieş and Giovanna Bucci. Their work appears in journals such as Computer-Aided Design, Journal of Computational Science, Transport in Porous Media, Production & Manufacturing Research and Computers & Graphics.

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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