scholarly journals Growth and Development: A possible systemic understanding

2020 ◽  
Vol 3 ◽  
pp. 83-94
Author(s):  
Gianfranco Minati
Keyword(s):  
Complex System ◽  
Complex Systems ◽  
Growth And Development ◽  
Emergent Property ◽  
Logistic Growth ◽  
Growth Processes ◽  
Multiple Systems ◽  
Systemic Understanding

Approaches for representing quantitative processes of growth for single systems are considered focussing especially upon logistic growth processes. Attention is then extended to processes of growth for complex systems such as Multiple Systems comprising components belonging to more than one system. Complex system populations of growth processes are considered in an attempt to gain an understanding of their growth. We consider in this regard various possible approaches for understanding development and its being an emergent property. We present some possible ways of understanding emergent development which can not be suitably considered as being reducible to the properties of sequences of processes of growth.

In-Between and Through: Architecture and Complexity

2005 ◽  
Vol 3 (3) ◽  
pp. 335-354 ◽  
Author(s):  
Clarissa Ribeiro Pereira de Almeida ◽  
Anja Pratschke ◽  
Renata La Rocca
Keyword(s):  
Complex System ◽  
Software Engineering ◽  
Complex Systems ◽  
Design Process ◽  
Three Dimensional ◽  
Self Organization ◽  
Three Dimensional Modeling ◽  
Dimensional Modeling ◽  
Complex Thought ◽  
Basic Characteristics

This paper draws on current research on complexity and design process in architecture and offers a proposal for how architects might bring complex thought to bear on the understanding of design process as a complex system, to understand architecture as a way of organizing events, and of organizing interaction. Our intention is to explore the hypothesis that the basic characteristics of complex systems – emergence, nonlinearity, self-organization, hologramaticity, and so forth – can function as effective tools for conceptualization that can usefully extend the understanding of the way architects think and act throughout the design process. To illustrate the discussions, we show how architects might bring complex thought inside a transdisciplinary design process by using models such as software engineering diagrams, and three-dimensional modeling network environments such as media to integrate, connect and ‘trans–act’.

scholarly journals Ensemble bootstrap methodology for forecasting dynamic growth processes using differential equations: application to epidemic outbreaks

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Gerardo Chowell ◽  
Ruiyan Luo
Keyword(s):  
Differential Equations ◽  
Ensemble Method ◽  
Transmission Model ◽  
Logistic Growth ◽  
Ensemble Modeling ◽  
Growth Processes ◽  
Probabilistic Forecasts ◽  
Forecasting Performance ◽  
Dynamic Growth ◽  
The Individual

AbstractBackgroundEnsemble modeling aims to boost the forecasting performance by systematically integrating the predictive accuracy across individual models. Here we introduce a simple-yet-powerful ensemble methodology for forecasting the trajectory of dynamic growth processes that are defined by a system of non-linear differential equations with applications to infectious disease spread.MethodsWe propose and assess the performance of two ensemble modeling schemes with different parametric bootstrapping procedures for trajectory forecasting and uncertainty quantification. Specifically, we conduct sequential probabilistic forecasts to evaluate their forecasting performance using simple dynamical growth models with good track records including the Richards model, the generalized-logistic growth model, and the Gompertz model. We first test and verify the functionality of the method using simulated data from phenomenological models and a mechanistic transmission model. Next, the performance of the method is demonstrated using a diversity of epidemic datasets including scenario outbreak data of theEbola Forecasting Challengeand real-world epidemic data outbreaks of including influenza, plague, Zika, and COVID-19.ResultsWe found that the ensemble method that randomly selects a model from the set of individual models for each time point of the trajectory of the epidemic frequently outcompeted the individual models as well as an alternative ensemble method based on the weighted combination of the individual models and yields broader and more realistic uncertainty bounds for the trajectory envelope, achieving not only better coverage rate of the 95% prediction interval but also improved mean interval scores across a diversity of epidemic datasets.ConclusionOur new methodology for ensemble forecasting outcompete component models and an alternative ensemble model that differ in how the variance is evaluated for the generation of the prediction intervals of the forecasts.

scholarly journals Toward Reverse Engineering to Economic Analysis: An Overview of Tools and Methodology

2021 ◽  
Author(s):  
Marisa Faggini ◽  
Bruna Bruno ◽  
Anna Parziale
Keyword(s):  
Complex System ◽  
Nonlinear Dynamics ◽  
Economic Analysis ◽  
Complex Systems ◽  
Reverse Engineering ◽  
Underlying Mechanism ◽  
Economic Data ◽  
Agent Based ◽  
Economic Agents ◽  
Advantages And Disadvantages

AbstractFollowing the reverse engineering (RE) approach to analyse an economic complex system is to infer how its underlying mechanism works. The main factors that condition the difficulty of RE are the number of variable components in the system and, most importantly, the interdependence of components on one another and nonlinear dynamics. All those aspects characterize the economic complex systems within which economic agents make their choices. Economic complex systems are adopted in RE science, and they could be used to understand, predict and model the dynamics of the complex systems that enable to define and to control the economic environment. With the RE approach, economic data could be used to peek into the internal workings of the economic complex system, providing information about its underling nonlinear dynamics. The idea of this paper arises from the aim to deepen the comprehension of this approach and to highlight the potential implementation of tools and methodologies based on it to treat economic complex systems. An overview of the literature about the RE is presented, by focusing on the definition and on the state of the art of the research, and then we consider two potential tools that could translate the methodological issues of RE by evidencing advantages and disadvantages for economic analysis: the recurrence analysis and the agent-based model (ABM).

scholarly journals Detection of Emergent Situations in Complex Systems by Structural Invariant (MB, M)

MENDEL ◽  
2017 ◽  
Vol 23 (1) ◽  
pp. 163-170 ◽  
Author(s):  
Jiri Bila ◽  
Martin Novak
Keyword(s):  
Complex System ◽  
Complex Systems ◽  
Detection Method ◽  
Water Cycle ◽  
Ramsey Theorem ◽  
Structural Invariant

The paper introduces complete description of the detection method that uses structural invariant Matroid and its Bases (MB, M). There are recapitulated essential concepts from the used knowledge field as “complex system, emergent situations (A, B, C)”, Ramsey theorem and principal computation variables “power” and “complexity” of emergence phenomenon. The method is explained in details and the demonstration of its application is done by the detection of emergent situation – violation of Short Water Cycle in an ecosystem.

scholarly journals Assessing Cyber-Worthiness of Complex System Capabilities using MBSE: A new rigorous engineering methodology

2021 ◽  
Author(s):  
Stuart Fowler ◽  
Keith Joiner ◽  
Elena Sitnikova
Keyword(s):  
Complex System ◽  
Complex Systems ◽  
Systems Engineering ◽  
Cyber Attacks ◽  
Simulation Methods ◽  
Assessment Methodology ◽  
Cyber Attack ◽  
Cyber Threats ◽  
Attack Surface ◽  
Model Based Systems Engineering

<div>Cyber-worthiness as it is termed in Australian Defence, or cyber-maturity more broadly, is a necessary feature of modern complex systems which are required to operate in a hostile cyber environment. To evaluate the cyber-worthiness of complex systems, an assessment methodology is required to examine a complex system’s or system-of-system’s vulnerability to and risk of cyber-attacks that can compromise such systems. This assessment methodology should address the cyber-attack surface and threat kill chains, including supply chains and supporting infrastructure. A cyber-worthiness capability assessment methodology has been developed based on model-based systems engineering concepts to analyse the cyber-worthiness of complex systems and present a risk assessment of various cyber threats to the complex system. This methodology incorporates modelling and simulation methods that provide organisations greater visibility and consistency across diverse systems, especially to drive cybersecurity controls, investment and operational decisions involving aggregated systems. In this paper, the developed methodology will be presented in detail and hypothesised outcomes will be discussed.</div>

Industry 4.0 From the Systems Engineering Perspective

2020 ◽  
pp. 575-599
Author(s):  
Vladimír Bureš
Keyword(s):  
Complex System ◽  
Physical Activity ◽  
Complex Systems ◽  
Frequency Analysis ◽  
Systems Engineering ◽  
Industry 4.0 ◽  
Control Level ◽  
Design Development ◽  
Starting Point ◽  
And Control

Systems engineering focuses on design, development, and implementation of complex systems. Not only does the Industry 4.0 concept consist of various technical components that need to be properly set and interconnected, but it is also tied to various managerial aspects. Thus, systems engineering approach can be used for its successful deployment. Overemphasis of technological aspects of Industry 4.0 represents the main starting point of this chapter. Then, collocation analysis, word clusters identification, selection and exemplification of selected domain in the business management realm, and frequency analysis are used in order to develop a holistic framework of Industry 4.0. This framework comprises six levels – physical, activity, outcome, content, triggers, and context. Moreover, the information and control level is integrated. The new holistic framework helps to consider Industry 4.0 from the complex systems engineering perspective – design and deployment of a complex system with required parameters and functionality.

Cellular Automata

2008 ◽  
pp. 57-84 ◽  
Author(s):  
Terry Bossomaier
Keyword(s):  
Complex System ◽  
Cellular Automata ◽  
Complex Systems ◽  
Lava Flows ◽  
Edge Of Chaos ◽  
Complex Systems Modelling ◽  
Systems Modelling ◽  
Theoretical Issues

In this chapter we present a view of cellular automata (CAs) as the quintessential complex system and how they can be used for complex systems modelling. First we consider theoretical issues of the complexity of their behaviour, discussing the Wolfram Classification, the Langton, lambda parameter and the edge of chaos. Then we consider the input entropy as a way of quantifying complex rules. Finally we contrast explicit CA modelling of geophysical systems with heuristic particle based methods for the visualisation of lava flows.

The Dynamic Usage of Models (DYSAM) as a Theoretically-Based Phenomenological Tool for Managing Complexity and as a Research Framework

2010 ◽  
pp. 176-190 ◽  
Author(s):  
Gianfranco Minati
Keyword(s):  
Complex Systems ◽  
Large Volume ◽  
Growth And Development ◽  
Long Tail ◽  
Research Framework ◽  
Managing Complexity ◽  
Science Of Management

In this paper, after recalling some fundamental concepts used in the science of complexity, we focus on theoretical and applicative cases of interest for the science of management of complex systems, where processes of emergence occur with the acquisition of new properties. The tool proposed is the DYnamical uSAge of Models (DYSAM). Within this framework we then focus upon a) the theoretical difference between growth and development; b) the sustainability of development rather than of growth as originally introduced in the literature; c) the concept of long tail (when, after initial large volume sales, low-revenue and infrequent buying may become a very important percentage of the entire business) as in telecommunications and management of long-tailed systems; d) non-reductionist management of complexity not reduced to solutions, and e) a future line of research to model processes of emergence.

Complexity and Criticality

2020 ◽  
pp. 42-50
Author(s):  
Helmut Satz
Keyword(s):  
Complex System ◽  
Complex Systems ◽  
Critical Point ◽  
Correlation Length ◽  
Critical Behavior ◽  
Scale Free ◽  
Self Organized ◽  
Self Organized Criticality ◽  
Free Behavior

Complex systems and critical behavior in complex system are defined in terms of correlation between constituents in the medium, subject to screening by intermediate constituents. At a critical point, the correlation length diverges—as a result, one finds the scale-free behavior also observed for bird flocks. This behavior is therefore possibly a form of self-organized criticality.

scholarly journals Nomenclature for Multiple Systems Containing Close Binaries

2005 ◽  
Vol 13 ◽  
pp. 1000-1005
Author(s):  
C.D. Scarfe
Keyword(s):  
Complex System ◽  
Close Binaries ◽  
Multiple Systems

AbstractI would like to discuss the difficulty of developing and maintaining a hierarchical designation scheme for components of multiple systems, when components are found by more than one method. Such a sequence of discoveries can easily lead to conflict between the initial nomenclature, which gets established in the literature, and that based on a scheme that is in broader use, or is more physically representative, or both. I will describe as an example a hypothetical complex system whose hierarchical description depends on the sequence in which discoveries are made, and whose designation in discovery order is ambiguous. In the end I urge flexibility in designations.

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