Search Results - subject:"Clustering Algorithm"

Evaluating accession decisions in customs unions : a dynamic machine learning approach

Naeher, Dominik; De Lombaerde, Philippe; Saber, Takfarinas - In: International economics and economic policy 22 (2024) 1, pp. 1-27

Persistent link: https://www.econbiz.de/10015188919

Inner areas matter : a place-sensitive approach for the identification of the Daily Life Spaces in the Italian Abruzzo region

Compagnucci, Fabiano; Morettini, Gabriele - In: Socio-economic planning sciences : the international … 93 (2024), pp. 1-21

Persistent link: https://www.econbiz.de/10014548999

Evaluating accession decisions in customs unions: a dynamic machine learning approach

Naeher, Dominik; De Lombaerde, Philippe; Saber, Takfarinas - In: International Economics and Economic Policy 22 (2024) 1

Previous work in the literature on regional economic integration has proposed the use of machine learning algorithms to evaluate the composition of customs unions, specifically, to estimate the degree to which customs unions match “natural markets” arising from trade flow data or appear to...

Persistent link: https://www.econbiz.de/10015361342

Democracy, military expenditure and economic growth : a heterogeneous perspective

Wang, Xinyi; Hou, Na; Chen, Bo - In: Defence and peace economics 34 (2023) 8, pp. 1039-1070

Persistent link: https://www.econbiz.de/10014390200

Policy evaluation with nonlinear trended outcomes : COVID-19 vaccination rates in the US

Morgan, Lynn Bergeland; Phillips, Peter C. B.; Sul, Donggyu - 2023

Persistent link: https://www.econbiz.de/10014538947

Minimum cost consensus model with loss aversion based large-scale group decision making

Liang, Yingying; Ju, Yanbing; Qin, Jindong; Pedrycz, Witold - In: Journal of the Operational Research Society 74 (2023) 7, pp. 1712-1729

Persistent link: https://www.econbiz.de/10014336288

Evaluating accession decisions in customs unions : a dynamic machine learning approach

Naeher, Dominik; De Lombaerde, Philippe; Saber, Takfarinas - 2023

Persistent link: https://www.econbiz.de/10014583024

TMsDP: two-stage density peak clustering based on multi-strategy optimization

MaJie, Jie; Hao, Zhiyuan; Hu, Mo - In: Data Technologies and Applications 58 (2022) 3, pp. 380-406

Purpose The density peak clustering algorithm (DP) is proposed to identify cluster centers by two parameters, i.e. ρ …

Persistent link: https://www.econbiz.de/10015342714

An improved data aggregation for fog computing devices in internet of things

Jalasri, M.; Lakshmanan, L. - In: International journal of networking and virtual … 30 (2024) 2, pp. 114-133

Persistent link: https://www.econbiz.de/10015066414

Capturing locational effects : application of the K-means clustering algorithm

Ryu, Doojin; Hong, Jengei; Jo, Hyunjae - In: The annals of regional science : an international … 73 (2024) 1, pp. 265-289

Persistent link: https://www.econbiz.de/10015045740