Computer Analysis of Human Belligerency
War is a cause of gains and losses. Economic historians have long stressed the extreme importance of considering the economic potential of society for belligerency, the role of management of chaos to bear the costs of battle and casualties, and ingenious and improvisation methodologies for emergency...
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doaj-31a2f14b61894a80be8088dddd2fb0d82020-11-25T02:56:02ZengMDPI AGMathematics2227-73902020-07-0181201120110.3390/math8081201Computer Analysis of Human BelligerencyJosé A. Tenreiro Machado0António M. Lopes1Maria Eugénia Mata2Department of Electrical Engineering, Institute of Engineering, Polytechnic of Porto, Rua Dr. António Bernardino de Almeida, 431, 4249-015 Porto, PortugalLAETA/INEGI, Faculty of Engineering, University of Porto, Rua Dr. Roberto Frias, 4200-465 Porto, PortugalNova SBE, Nova School of Business and Economics (Faculdade de Economia da Universidade Nova de Lisboa), Rua da Holanda, 1, 2775-405 Carcavelos, PortugalWar is a cause of gains and losses. Economic historians have long stressed the extreme importance of considering the economic potential of society for belligerency, the role of management of chaos to bear the costs of battle and casualties, and ingenious and improvisation methodologies for emergency management. However, global and inter-temporal studies on warring are missing. The adoption of computational tools for data processing is a key modeling option with present day resources. In this paper, hierarchical clustering techniques and multidimensional scaling are used as efficient instruments for visualizing and describing military conflicts by electing different metrics to assess their characterizing features: time, time span, number of belligerents, and number of casualties. Moreover, entropy is adopted for measuring war complexity over time. Although wars have been an important topic of analysis in all ages, they have been ignored as a subject of nonlinear dynamics and complex system analysis. This paper seeks to fill these gaps in the literature by proposing a quantitative perspective based on algorithmic strategies. We verify the growing number of events and an explosion in their characteristics. The results have similarities to those exhibited by systems with increasing volatility, or evolving toward chaotic-like behavior. We can question also whether such dynamics follow the second law of thermodynamics since the adopted techniques reflect a system expanding the entropy.https://www.mdpi.com/2227-7390/8/8/1201data visualizationmultidimensional scalinghierarchical clusteringentropycomplex systems |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
José A. Tenreiro Machado António M. Lopes Maria Eugénia Mata |
spellingShingle |
José A. Tenreiro Machado António M. Lopes Maria Eugénia Mata Computer Analysis of Human Belligerency Mathematics data visualization multidimensional scaling hierarchical clustering entropy complex systems |
author_facet |
José A. Tenreiro Machado António M. Lopes Maria Eugénia Mata |
author_sort |
José A. Tenreiro Machado |
title |
Computer Analysis of Human Belligerency |
title_short |
Computer Analysis of Human Belligerency |
title_full |
Computer Analysis of Human Belligerency |
title_fullStr |
Computer Analysis of Human Belligerency |
title_full_unstemmed |
Computer Analysis of Human Belligerency |
title_sort |
computer analysis of human belligerency |
publisher |
MDPI AG |
series |
Mathematics |
issn |
2227-7390 |
publishDate |
2020-07-01 |
description |
War is a cause of gains and losses. Economic historians have long stressed the extreme importance of considering the economic potential of society for belligerency, the role of management of chaos to bear the costs of battle and casualties, and ingenious and improvisation methodologies for emergency management. However, global and inter-temporal studies on warring are missing. The adoption of computational tools for data processing is a key modeling option with present day resources. In this paper, hierarchical clustering techniques and multidimensional scaling are used as efficient instruments for visualizing and describing military conflicts by electing different metrics to assess their characterizing features: time, time span, number of belligerents, and number of casualties. Moreover, entropy is adopted for measuring war complexity over time. Although wars have been an important topic of analysis in all ages, they have been ignored as a subject of nonlinear dynamics and complex system analysis. This paper seeks to fill these gaps in the literature by proposing a quantitative perspective based on algorithmic strategies. We verify the growing number of events and an explosion in their characteristics. The results have similarities to those exhibited by systems with increasing volatility, or evolving toward chaotic-like behavior. We can question also whether such dynamics follow the second law of thermodynamics since the adopted techniques reflect a system expanding the entropy. |
topic |
data visualization multidimensional scaling hierarchical clustering entropy complex systems |
url |
https://www.mdpi.com/2227-7390/8/8/1201 |
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