About: Analysing the resilience of the European commodity production system with PyResPro, the Python Production Resilience package

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About: Analysing the resilience of the European commodity production system with PyResPro, the Python Production Resilience package Goto Sponge NotDistinct Permalink

An Entity of Type : schema:ScholarlyArticle, within Data Space : wasabi.inria.fr associated with source document(s)

Attributes	Values
type	Academic Article research paper schema:ScholarlyArticle
isDefinedBy	Covid-on-the-Web dataset
has title	Analysing the resilience of the European commodity production system with PyResPro, the Python Production Resilience package
Creator	Chatzopoulos, T De, Palma
Source	ArXiv
abstract	This paper presents a Python object-oriented software and code to compute the annual production resilience indicator. The annual production resilience indicator can be applied to different anthropic and natural systems such as agricultural production, natural vegetation and water resources. Here, we show an example of resilience analysis of the economic values of the agricultural production in Europe. The analysis is conducted for individual time-series in order to estimate the resilience of a single commodity and to groups of time-series in order to estimate the overall resilience of diversified production systems composed of different crops and/or different countries. The proposed software is powerful and easy to use with publicly available datasets such as the one used in this study.
has issue date	2020-06-16(xsd:dateTime)
has license	arxiv
sha1sum (hex)	f5af9568edf33b6727fd0544de28b91cad440bf2
resource representing a document's title	Analysing the resilience of the European commodity production system with PyResPro, the Python Production Resilience package
resource representing a document's body	covid:f5af9568edf33b6727fd0544de28b91cad440bf2#body_text
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