Minbo Ma

545 citations
9 papers · 311 · 1 hit paper · h-index 7

Impact in

Papers in

Minbo Ma

9 papers receiving 303 citations

Minbo Ma's Hit Papers

Long sequence time-series forecasting with deep learning: A survey 2023 · 164 citations
1640+1+2Years since publication50100150

Peers

Minbo Ma
Comparison fields: 5 of 77
  • Signal Processing 63
  • Transportation 29
  • Management Science and Operations Research 52
  • Building and Construction 52
  • Artificial Intelligence 113
Replace Deqiang Kong with:
Deqiang Kong China
King Ma Canada
Xuehan Wu China
Shouxu Jiang China
Edoardo Prezioso Italy
Razvan-Gabriel Cirstea Denmark
Chujie Tian China
Phi Le Nguyen Vietnam
Minbo Ma relative to Deqiang Kong China Deqiang Kong's profile →
Citations per field
00.5×2.9×
Deqiang Kong · 1×
Citations per year

Countries citing papers authored by Minbo Ma

Since Specialization
Citations

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

Fields of papers citing papers by Minbo Ma

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 24 scholars most cited alongside Minbo Ma, 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 Minbo Ma Line = papers co-authored together Minbo Ma links everyone, so they are left out of the graph.

All Works

9 of 9 papers shown
#Work
1
Long sequence time-series forecasting with deep learning: A survey
Hit paper breakdown →
2023164
2 202346
3 202333
4 202326
5 202318
6 202411
7 20236
8 20245
9 20232

About Minbo Ma

Minbo Ma is a scholar working on Computer Vision and Pattern Recognition, Signal Processing, Atmospheric Science, Artificial Intelligence and Management Science and Operations Research, having authored 9 papers that have together received 311 indexed citations. Recurring topics across this work include Time Series Analysis and Forecasting (3 papers), Forecasting Techniques and Applications (2 papers), Meteorological Phenomena and Simulations (2 papers), Hydrological Forecasting Using AI (2 papers), Stock Market Forecasting Methods (2 papers), Energy Load and Power Forecasting (2 papers), Data Management and Algorithms (1 paper) and Thermal Analysis in Power Transmission (1 paper). The work is most often cited by research in Signal Processing (63 citations), Transportation (29 citations), Management Science and Operations Research (52 citations), Building and Construction (52 citations) and Artificial Intelligence (113 citations). Minbo Ma has collaborated with scholars based in China, Denmark and United Arab Emirates. Frequent co-authors include Tianrui Li, Hongjun Wang, Chongshou Li, Shenggong Ji, Peng Xie, Junbo Zhang, Pengfei Zhang, Wei Huang, Ping Deng and Dexian Wang. Their work appears in journals such as Information Fusion, Information Sciences, IEEE Transactions on Knowledge and Data Engineering, Knowledge-Based Systems and SHILAP Revista de lepidopterología.

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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