scholarly journals COVID-19 and digital transformation: developing an open experimental testbed for sustainable and innovative environments using Fuzzy Cognitive Maps

F1000Research ◽  
2021 ◽  
Vol 10 ◽  
pp. 264
Author(s):  
Wolfgang Höhl
Keyword(s):  
Social Impact ◽  
Cognitive Maps ◽  
Digital Transformation ◽  
Fuzzy Cognitive Maps ◽  
Minor Role ◽  
Initial State ◽  
New Approach ◽  
Innovative Environments ◽  
Experimental Testbed ◽  
A Minor

This paper sketches a new approach using Fuzzy Cognitive Maps (FCMs) to operably map and simulate digital transformation in architecture and urban planning. Today these processes are poorly understood. Many current studies on digital transformation are only treating questions of economic efficiency. Sustainability and social impact only play a minor role. Decisive definitions, concepts and terms stay unclear. Therefore this paper develops an open experimental testbed for sustainable and innovative environments (ETSIE) for three different digital transformation scenarios using FCMs. A traditional growth-oriented scenario, a COVID-19 scenario and an innovative and sustainable COVID-19 scenario are modeled and tested. All three scenarios have the same number of components, connections and the same driver components. Only the initial state vectors are different and the internal correlations are weighted differently. This allows for comparing all three scenarios on an equal basis. The Mental Modeler software is used. This paper presents one of the first applications of FCMs in the context of digital transformation. It is shown that the traditional growth-oriented scenario is structurally very similar to the current COVID-19 scenario. The current pandemic is able to accelerate digital transformation to a certain extent. But the pandemic does not guarantee for a distinct sustainable and innovative future development. Only by changing the initial state vectors and the weights of the connections an innovative and sustainable turnaround in a third scenario becomes possible.

FUZZY COGNITIVE MAPS WITH GENETIC ALGORITHM FOR GOAL-ORIENTED DECISION SUPPORT

2004 ◽  
Vol 12 (supp02) ◽  
pp. 31-42 ◽  
Author(s):  
M. SHAMIM KHAN ◽  
SEBASTIAN KHOR ◽  
ALEX CHONG
Keyword(s):  
Genetic Algorithm ◽  
Decision Making ◽  
Genetic Algorithms ◽  
Decision Support ◽  
Directed Graphs ◽  
Cognitive Maps ◽  
Fuzzy Cognitive Maps ◽  
Initial State ◽  
Initial Stimulus ◽  
Over Time

Fuzzy cognitive maps are signed directed graphs used to model the evolution of scenarios with time. FCMs can be useful in decision support for predicting future states given an initial state. Genetic algorithms (GA) are well-established tools for optimization. This paper concerns the use of FCMs in goal-directed analysis of scenarios for aiding decision making. A methodology for GA-based goal-directed analysis is presented. The search for the initial stimulus state, that over time leads to a target state of interest, is optimized using GA. This initial state found can be used to answer the question – what course of events leads to a certain state in a given scenario?

Study on Utilizing Customer Reviews through Knowledge Integration Approach

2013 ◽  
Vol 380-384 ◽  
pp. 4767-4770
Author(s):  
Biao Ma ◽  
Tian Tian Yuan ◽  
Cheng Chen
Keyword(s):  
Knowledge Integration ◽  
Comprehensive Evaluation ◽  
Cognitive Maps ◽  
Fuzzy Cognitive Maps ◽  
New Approach ◽  
Online Store ◽  
Customer Reviews ◽  
Integration Approach ◽  
Proposal A ◽  
Unstructured Information

Nowadays, customer reviews or comments have become a golden mine for B2C companies. How to exploit these reviews more effectively has attracted researchers attention. This paper proposal a new approach of utilizing the reviews, which integrates the reviews unstructured information based on fuzzy cognitive maps and nonlinear Habbian learning. The approach aims to provide an effective way of generating a comprehensive evaluation of an online store.

scholarly journals Global stability of fuzzy cognitive maps

2021 ◽  
Author(s):  
István Á. Harmati ◽  
Miklós F. Hatwágner ◽  
László T. Kóczy
Keyword(s):  
Fixed Point ◽  
Global Stability ◽  
Cognitive Maps ◽  
Fuzzy Cognitive Maps ◽  
Initial Vector ◽  
Asymptotically Stable ◽  
Global Asymptotical Stability ◽  
Initial State ◽  
Globally Asymptotically Stable ◽  
Multiple Fixed Points

AbstractComplex systems can be effectively modelled by fuzzy cognitive maps. Fuzzy cognitive maps (FCMs) are network-based models, where the connections in the network represent causal relations. The conclusion about the system is based on the limit of the iteratively applied updating process. This iteration may or may not reach an equilibrium state (fixed point). Moreover, if the model is globally asymptotically stable, then this fixed point is unique and the iteration converges to this point from every initial state. There are some FCM models, where global stability is the required property, but in many FCM applications, the preferred scenario is not global stability, but multiple fixed points. Global stability bounds are useful in both cases: they may give a hint about which parameter set should be preferred or avoided. In this article, we present novel conditions for the global asymptotical stability of FCMs, i.e. conditions under which the iteration leads to the same point from every initial vector. Furthermore, we show that the results presented here outperform the results known from the current literature.

The Effect of Path Length and Display Size on Memory for Spatial Information

2012 ◽  
Vol 59 (3) ◽  
pp. 147-152 ◽  
Author(s):  
Katherine Guérard ◽  
Sébastien Tremblay
Keyword(s):  
Path Length ◽  
Potential Role ◽  
Spatial Information ◽  
Recall Performance ◽  
Minor Role ◽  
Length Effect ◽  
Serial Memory ◽  
Fixed Reference ◽  
A Minor

In serial memory for spatial information, some studies showed that recall performance suffers when the distance between successive locations increases relatively to the size of the display in which they are presented (the path length effect; e.g., Parmentier et al., 2005) but not when distance is increased by enlarging the size of the display (e.g., Smyth & Scholey, 1994). In the present study, we examined the effect of varying the absolute and relative distance between to-be-remembered items on memory for spatial information. We manipulated path length using small (15″) and large (64″) screens within the same design. In two experiments, we showed that distance was disruptive mainly when it is varied relatively to a fixed reference frame, though increasing the size of the display also had a small deleterious effect on recall. The insertion of a retention interval did not influence these effects, suggesting that rehearsal plays a minor role in mediating the effects of distance on serial spatial memory. We discuss the potential role of perceptual organization in light of the pattern of results.

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