Knee Point Detection
Knee Point Detection is a solution selection methodology in multi-objective optimization that identifies the most preferred trade-off solution on the Pareto front where marginal improvements in one objective cease to justify losses in another, thereby distinguishing itself from general compromise-seeking techniques by focusing on high-impact transition points in objective trade-offs.
30
Publications
3K
Citations
112
Authors
50
Institutions
Publications per year
2017–2026
21
30
Finding a "Kneedle" in a Haystack: Detecting Knee Points in System Behavior
Ville Satopää, Jeannie Albrecht, David Irwin et al. · 2011 · 1.3K citations
Nonlinear health evaluation for lithium-ion battery within full-lifespan
Heze You, Jiangong Zhu, Xueyuan Wang et al. · Journal of Energy Chemistry · 2022 · 153 citations · Full text
Engineering, Cloud Computing, Aging +15
1–5 of 30
112
5
h-index
5
h-index
4
h-index
1
h-index
1
h-index
1–5 of 112
50
Honda (Germany)
Frankfurt am Main, Germany
5 h-index
6 publications
207 citations

University of Surrey
Guildford, United Kingdom
5 h-index
9 publications
371 citations

Beihang University
Beijing, China
2 h-index
6 publications
726 citations
Dalian University of Technology
Dalian, China
2 h-index
8 publications
288 citations

National and Kapodistrian University of Athens
Athens, Greece
1 h-index
1 publications
28 citations

Indian Institute of Science Bangalore
Bengaluru, India
1 h-index
7 publications
126 citations
Aalborg University
Aalborg, Denmark
1 h-index
1 publications
87 citations

University of Electronic Science and Technology of China
Chengdu, China
1 h-index
2 publications
24 citations
1–8 of 50
3 publications · 288 citations
3
h-index
1 publications · 151 citations
1
h-index
1 publications · 27 citations
1
h-index
SHM · 1 publications · 27 citations
1
h-index
1 publications · 90 citations
1
h-index
1–5