BCSSS

International Encyclopedia of Systems and Cybernetics

2nd Edition, as published by Charles François 2004 Presented by the Bertalanffy Center for the Study of Systems Science Vienna for public access.

About

The International Encyclopedia of Systems and Cybernetics was first edited and published by the system scientist Charles François in 1997. The online version that is provided here was based on the 2nd edition in 2004. It was uploaded and gifted to the center by ASC president Michael Lissack in 2019; the BCSSS purchased the rights for the re-publication of this volume in 200?. In 2018, the original editor expressed his wish to pass on the stewardship over the maintenance and further development of the encyclopedia to the Bertalanffy Center. In the future, the BCSSS seeks to further develop the encyclopedia by open collaboration within the systems sciences. Until the center has found and been able to implement an adequate technical solution for this, the static website is made accessible for the benefit of public scholarship and education.

A B C D E F G H I J K L M N O P Q R S T U V W Y Z

TREND 1)3)

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A more or less general regularity in a process.

Different trends appear according to time horizon. Some are related to short, other to median, long or very long term (in a relative sense). These different time scales are interconnected and the observer must define the process level in which he/she is specifically interested, in view that any trend is normally related to a specific aspect of the process. The simple statistic analysis of data proposed by operation research and called trend analysis, while technically useful, is insufficient and even risky as a forecasting tool, if short term trends are not distinguished as fluctuations in the longer term trends (at various time horizons at that!).

In systems in dynamic equilibrium, the longer term trend generally constitutes a limiting frame for the oscillations of the shorter ones. When the short term trend line nears the limit (superior or inferior) of the longer one, a reversal of the short one generally takes place and a short term threshold is crossed. For this reason, any extrapolation of a shorter term trend is risky and doubtful, if nothing is known about the longer ones.

Of course, the time scales of trends observations are conventional as they depend on the type of processes which are observed.

While one day is a long span in a mayfly's life, one year amounts to practically nothing at geological scale. However, even in this case, a sudden discontinuity may happen at any time, as a chaotic event: an earthquake produced by the slow evolution of a geological fault.

Short term trends may appear as being random if related to long term ones. However, they may well depend from some micro-determinism whose visible expression may even be statistical. In this sense, M. BELlS states: "During the progress of some phenomenon, the necessity, as dominant trend, opens its way through the multiplicity of fortuitous events" (1987, p.59).

While no prediction can ever be absolutely guaranteed, the observation of long term trends combined with shorter ones is the most reliable tool at our disposal.

Categories

  • 1) General information
  • 2) Methodology or model
  • 3) Epistemology, ontology and semantics
  • 4) Human sciences
  • 5) Discipline oriented

Publisher

Bertalanffy Center for the Study of Systems Science(2020).

To cite this page, please use the following information:

Bertalanffy Center for the Study of Systems Science (2020). Title of the entry. In Charles François (Ed.), International Encyclopedia of Systems and Cybernetics (2). Retrieved from www.systemspedia.org/[full/url]

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