Entropy weight method
← Most-used equations and models
Weights indicators by how much their values vary across units, often to build composite indices.
LaTeX: e_j = -\frac{1}{\ln n}\sum_{i=1}^{n} p_{ij}\ln p_{ij},\quad w_j = \frac{1 - e_j}{\sum_k (1 - e_k)}
Key findings
- Entropy weight method was mentioned in 7 papers in the last 30 days (2026-09-27 to 2026-10-26), ranking #75 of the 104 equations and models mentioned.
- By journal category: Economics (3), Finance (2), AI (1) and Operations Research (1).
- Most of them appeared in Economic Analysis and Policy (2), International Review of Economics & Finance (2) and Expert Systems with Applications (1).
- Often mentioned together with Mediation model (indirect effect) (2), TOPSIS (1) and Linear and integer programming (1).
- Datasets named in the same papers: CSMAR (2), China City Statistical Yearbook (1) and Chinese Industrial Enterprises Database (1).
- From Apr 2024 to Sep 2026, 68 archived papers mentioned Entropy weight method in their title, abstract or keywords, most of them in Feb 2025 (6).
Mentions over 30 months
| Trend | Apr 24–Sep 24 | Oct 24–Sep 25 | Oct 25–Sep 26 | 30 months |
|---|---|---|---|---|
| 16 | 45 | 7 | 68 |
Cite this page
Scholar4AI. (2026). Entropy weight method. Journal Research Rankings. Retrieved October 26, 2026, from https://scholar4ai.com/equations/entropy-weight-method
@misc{scholar4ai-equations-entropy-weight-method,
author = {{Scholar4AI}},
title = {Entropy weight method},
year = {2026},
howpublished = {\url{https://scholar4ai.com/equations/entropy-weight-method}},
urldate = {2026-10-26},
note = {Journal Research Rankings; data from OpenAlex (CC0); licensed CC BY-NC 4.0}
}