Standout Papers

A quantitative discriminant method of elbow point for the optimal number of clusters in clustering algorithm 2021 2026 2022 2024181
  1. A quantitative discriminant method of elbow point for the optimal number of clusters in clustering algorithm (2021)
    Congming Shi, Shoulin Wei et al. EURASIP Journal on Wireless Communications and Networking

Immediate Impact

3 standout
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Citing Papers

AutoBPS: A tool for urban building energy modeling to support energy efficiency improvement at city-scale
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2 intermediate papers

Works of Congming Shi being referenced

A quantitative discriminant method of elbow point for the optimal number of clusters in clustering algorithm
2021 Standout

Author Peers

Author Last Decade Papers Cites
Congming Shi 13 36 6 17 15 4 186
Dauda Usman 20 36 17 26 16 4 250
Wen Wang 16 64 7 24 23 5 214
Gregory W. Corder 10 34 13 13 20 4 250
A. Santhakumaran 15 43 8 24 15 6 208
Youguo Li 16 34 6 26 18 2 169
Dale I. Foreman 10 34 15 12 20 3 255
Vatsal Patel 17 46 11 15 10 7 228
Justice Aning 10 55 15 11 15 6 178
Allan G. Bluman 26 22 4 7 15 5 259
Rory Mitchell 10 71 15 11 17 7 249

All Works

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2026