A novel semi-quantitative Fuzzy Cognitive Map model for complex systems for addressing challenging participatory real life problems

Obiedat, Mamoon; Samarasinghe, Sandhya

doi:10.1016/j.asoc.2016.06.001

Cited by 28 publications

(14 citation statements)

References 44 publications

(90 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The difficult part is to assign the weight to the causal links. Some researchers have used a linguistic evaluation (Mourhir, Rachidi, & Karim, 2015;Obiedat & Samarasinghe, 2016). However, the difficulty is only shifted because the question remains on how to translate a linguistic evaluation into a quantitative evaluation.…”

Section: Methodsmentioning

confidence: 99%

A scenario-based modeling method for controlling ECM performance

López

Ishizaka

2018

Expert Systems with Applications

View full text Add to dashboard Cite

Section: Methodsmentioning

confidence: 99%

A scenario-based modeling method for controlling ECM performance

López

Ishizaka

2018

Expert Systems with Applications

View full text Add to dashboard Cite

“…FCM was used as a navigation to address the connections between Internet of Things and intelligent space [19]. FCM approach has also been used for modelling and simulating the uncertainty in socio-ecological, economic and environmental systems [20][21][22][23]. Next section presents the proposed FCM approach to present the uncertainty of the QoS domain and then simulate the FCM system to reach outcomes that could reveal suggestions for selecting an appropriate QoS for stakeholders.…”

Section: Perspectives On Fcmmentioning

confidence: 99%

Representing and Simulating Uncertainty of the Quality of Service of Web Services using Fuzzy Cognitive Map Approach

Obiedat¹,

Khasawneh²,

Banikhalaf³

et al. 2020

IJACSA

Self Cite

View full text Add to dashboard Cite

Web services are growing rapidly to provide clients, either organizations or individuals, with multiple Internet services and to offer solutions for the integration of many applications. Quality of Service (QoS) of a Web service is the key consideration of both service providers and users. Thus, measuring the QoS requires, in addition to its normative requirements, engaging the views of clients and service providers and environmental factors. Human intervention and the environment may lead to uncertainty and result in uncertain factors in assessing QoS. In such a case, traditional computing and statistical techniques cannot provide an accurate representation of inherited uncertainties, especially when uncertain variables are connected with ambiguous (fuzzy) relationships. An alternative is to use a soft computing approach. This paper proposes a Fuzzy Cognitive Map (FCM) model as a soft computing approach that can represent and simulate the uncertainty of QoS. FCM represents the uncertain variables in the domain knowledge and their connections in the form of a signed directed graph consisting of nodes representing the variables and directed arrows representing the cause-effect relationships. In addition, it allows representing imprecise data either using numeric data, i.e. in the ranges [0, 1] and [-1, 1], or linguistic data, i.e., "low, medium, high". For calculations, FCM is converted to an adjacency matrix to find the effects of variables on each other. Scenario simulations can also be implemented to help decision makers to investigate appropriate outcomes. Finally, the proposed approach is tested by an experiment to demonstrate its reasonability and admissibility of the representation and simulation of the uncertainty of the QoS domain knowledge.

show abstract

“…The FCM community has touched upon issues related to traceability in FCM building (e.g. Vanwindekens et al ., ) or started to collect common difficulties and pitfalls in FCM practices (Jetter and Kok, ), and there have been proposals to solve technical difficulties for individual map aggregation and condensation (Mourhir et al ., ; Obiedat and Samarasinghe, ). However, these authors also detect space for improvement at least in the reporting of source data, collection and treatment methods.…”

Section: Introductionmentioning

confidence: 97%

“…The issue of transparency and reproducibility is more problematic in social and integrated sciences where the evaluation of the reliability of findings might be challenging and thus jeopardize the credibility of the studies for decision makers. However, many complex and dynamic real‐life problems cannot be solved with quantitative approaches, either because there is a lack of data or because the data is qualitative (Obiedat and Samarasinghe, ). This challenge often calls for the use of methods based on expert elicitation or participatory processes that help understand systems that are characterized by data scarcity, scattered knowledge among multiple agents or high complexity (Olazabal and Reckien, ; Obiedat and Samarasinghe, ).…”

Section: Introductionmentioning

confidence: 99%

Transparency and Reproducibility in Participatory Systems Modelling: the Case of Fuzzy Cognitive Mapping

2018

View full text Add to dashboard Cite

By aggregating semi‐quantitative mind maps from multiple agents, fuzzy cognitive mapping (FCM) allows developing an integrated, cross‐sectoral understanding of complex systems. However, and especially for FCM based on individual interviews, the map‐building process presents potential pitfalls. These are mainly related to the different understandings of the interviewees about the FCM semantics as well as the biases of the analyst during the elicitation and treatment of data. This paper introduces a set of good practice measures to increase transparency and reproducibility of map‐building processes in order to improve credibility of results from FCM applications. The case study used to illustrate the proposed good practices assesses heatwave impacts and adaptation options in an urban environment. Agents from different urban sectors were interviewed to obtain individual cognitive maps. Using this set of data, we suggest good practices to collect, digitalize, interpret, pre‐process and aggregate the individual maps in a traceable and coherent way. © 2018 The Authors Systems Research and Behavioral Science published by International Federation for Systems Research and John Wiley & Sons Ltd

show abstract

A novel semi-quantitative Fuzzy Cognitive Map model for complex systems for addressing challenging participatory real life problems

Cited by 28 publications

References 44 publications

A scenario-based modeling method for controlling ECM performance

A scenario-based modeling method for controlling ECM performance

Representing and Simulating Uncertainty of the Quality of Service of Web Services using Fuzzy Cognitive Map Approach

Transparency and Reproducibility in Participatory Systems Modelling: the Case of Fuzzy Cognitive Mapping

Contact Info

Product

Resources

About