scholarly journals Bayesian Belief Networks for Integrating Scientific and Stakeholders’ Knowledge to Support Nature-Based Solution Implementation

2021 ◽  
Vol 9 ◽  
Author(s):  
Albert Scrieciu ◽  
Alessandro Pagano ◽  
Virginia Rosa Coletta ◽  
Umberto Fratino ◽  
Raffaele Giordano
Keyword(s):  
Knowledge Integration ◽  
Cognitive Maps ◽  
Bayesian Belief Networks ◽  
Hydraulic Modeling ◽  
Fuzzy Cognitive Maps ◽  
Decision Makers ◽  
Belief Networks ◽  
Integration Process ◽  
Problem Structuring ◽  
Risk Reduction Measures

There is a growing interest worldwide on the potential of nature-based solutions (NBSs) as measures for dealing with water-related risks while producing multiple co-benefits that can contribute to several societal challenges and many of the sustainable development goals. However, several barriers still hamper their wider implementation, such as mainly the lack of stakeholders’ engagement and the limited integration of stakeholders’ knowledge throughout the phases of NBS design and implementation. This is a crucial aspect to guarantee that the multidimensional implications of NBSs are adequately understood and considered by decision-makers. Innovative methods and tools for improving NBS design and supporting decision-makers in overcoming the main barriers to implementation, ultimately enhancing their effectiveness, are therefore needed. The present work proposes a combined approach based on the integration of fuzzy cognitive maps, hydraulic modeling, and participatory Bayesian belief networks aiming to facilitate the stakeholders’ engagement and the knowledge integration process in NBS design and assessment. The approach was developed and implemented within the NAIAD project in the Lower Danube demo site, specifically oriented to support the process of the Potelu Wetland restoration. First, fuzzy cognitive maps are adopted as a problem structuring method for eliciting stakeholders’ risk perception and problem understanding, and for constructing a causal model describing the system as a whole, with specific attention to the expected role of the NBS in reducing flood risk and addressing the key local challenges. Second, hydraulic modeling is used to analyze the effect of extreme floods starting from the retrospective analysis of a specific event and to model the potential benefits of risk reduction measures. Last, a Bayesian belief network is used to support the model integration process and a scenario analysis with a user-friendly tool. The whole process can be replicated in other areas and is particularly suitable to support an active engagement of stakeholders (both institutional and not) in the process of NBS design and assessment.

Application of Bayesian belief networks and fuzzy cognitive maps in intrusion analysis

2018 ◽  
Vol 35 (1) ◽  
pp. 111-122
Author(s):  
Yit Yin Wee ◽  
Wooi Ping Cheah ◽  
Shih Yin Ooi ◽  
Shing Chiang Tan ◽  
Kuokkwee Wee
Keyword(s):  
Cognitive Maps ◽  
Bayesian Belief Networks ◽  
Fuzzy Cognitive Maps ◽  
Belief Networks

Exploring ecosystem service issues across diverse knowledge domains using Bayesian Belief Networks

2011 ◽  
Vol 35 (5) ◽  
pp. 681-699 ◽  
Author(s):  
Roy Haines-Young
Keyword(s):  
Ecosystem Services ◽  
Social Values ◽  
Early Stage ◽  
Bayesian Belief Networks ◽  
Decision Makers ◽  
Belief Networks ◽  
Knowledge Domains ◽  
Study Materials ◽  
Shared Social Values

The analysis of the relationships between people and nature is complex, because it involves bringing together insights from a range of disciplines, and, when stakeholders are involved, the perspectives and values of different interest groups. Although it has been suggested that analytical-deliberate approaches may be useful in dealing with some of this complexity, the development of methods is still at an early stage. This is particularly so in relation to debates around the concept of ecosystem services where biophysical, social and economic insights need to be integrated in ways that can be accessed by decision-makers. The paper draws on case studies to examine the use of Bayesian Belief Networks (BBNs) as a means of implementing analytical-deliberative approaches in relation to mapping ecosystem services and modelling scenario outcomes. It also explores their use as a tool for representing individual and group values. It is argued that when linked with GIS techniques BBNs allow mapping and modelling approaches rapidly to be developed and tested in an efficient and transparent way, and that they are a valuable scenario-building tool. The case-study materials also show that BBNs can support multicriteria forms of deliberative analysis that can be used to capture stakeholder opinions so that different perspectives can be compared and shared social values identified.

A model for assessment of uncertainty in tacit knowledge acquisition

2018 ◽  
Vol 22 (2) ◽  
pp. 413-431 ◽  
Author(s):  
Peyman Akhavan ◽  
Ali Shahabipour ◽  
Reza Hosnavi
Keyword(s):  
Decision Making ◽  
Sensitivity Analysis ◽  
Knowledge Management ◽  
Cognitive Maps ◽  
Bayesian Belief Networks ◽  
Uncertainty Assessment ◽  
Assessment Method ◽  
Fuzzy Cognitive Maps ◽  
Content Type ◽  
Accurate Knowledge

Purpose Expert systems have come to the forefront in the modeling of problems. One of the major problems facing the expert system designers is to develop an accurate knowledge base and a meaningful model of uncertainty associated with complex models. Decision-making is based on knowledge, and decision system support needs a knowledge base as well. An adequate knowledge acquisition (KA) process leads to accurate knowledge and improves the decision-making process. To manage the risk of a medical service (twin pregnancy in this case) a knowledge management system was created. The captured knowledge may be associated with an uncertainty. This study aims to introduce a method for evaluating the reliability of a tacit KA model. It assisted engineering managers in assessing and prioritizing risks. The study tried to use this method in risk management and new case in the health domain. Design/methodology/approach In this study, relevant variables were identified in the knowledge management literature reviews and the domain of expertise management. They are validated by a group of domain experts. Kendall’s W indicator was used to assess the degree of consensus. On the basis of combined cognitive maps, a cognitive network was constructed. Using Bayesian belief networks and fuzzy cognitive maps, an uncertainty assessment method of tacit KA was introduced. To help managers focus on major variables, a sensitivity analysis was conducted. Reliability of model was calculated for optimistic and pessimistic values. The applicability and efficacy of the proposed method were verified and validated with data from a medical university. Findings Results show that tacit KA uncertainty can be defined by independent variables, including environmental factors, personality and acquisition process factors. The reliability value shows the accuracy of the captured knowledge and the effectiveness of the acquisition process. The proposed uncertainty assessment method provides the reliability value of the acquisition model for knowledge engineers, so it can be used to implement the project and prevent failures in vital factors through necessary actions. If there is not a satisficed level of reliability, the KA project reliability can be improved by risk factors. The sensitivity analysis can help to select proper factors based on the resources. This approach mitigated some of the disadvantages of other risk evaluation methods. Originality/value The contribution of this study is to combine the uncertainty assessment with tacit KA based on fuzzy cognitive maps and the Bayesian belief networks approach. This approach used the capabilities of both narrative and computational approaches.

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.

Aggregation cognitive maps procedure for group decision analysis

Kybernetes ◽  
2016 ◽  
Vol 45 (4) ◽  
pp. 589-603 ◽  
Author(s):  
Annielli Araújo Rangel Cunha ◽  
José Leao Silva Filho ◽  
Danielle Costa Morais
Keyword(s):  
Group Decision ◽  
Cognitive Maps ◽  
Relevant Information ◽  
Decision Makers ◽  
Problem Structuring Methods ◽  
Problem Structuring ◽  
Content Type ◽  
Individual Perceptions ◽  
Single Structure ◽  
The Individual

Purpose – Cognitive maps are used in group decision processes to structure problems. The problem structuring methods helps decision makers to improve the comprehension of the problem, identifying alternative actions and conflicts. However, represents the individual perceptions in a representative group decision into a single structure can be a complex task. The paper aims to discuss these issues. Design/methodology/approach – The objective of this paper is to improve the process of discussion, obtaining the interests and views of the participants and provide parameters to assist the analyst to guide the process. Furthermore, it is possible to analyze how participants are aligned or diverge from the group. The literature review presents some approaches for cognitive maps analysis, but there is a lack of structured methods to analyze them. This paper proposes a structure procedure for the aggregation of cognitive maps in three parts: workshop to generate individual maps, the aggregation of individual maps and the refinement of the global map. Findings – An example illustrates the application of the proposed method and shows the construction of a global map that summarizes the concepts that participants consider important. Originality/value – This paper presents a new procedure that allows reducing the bias of the analyst in the aggregation of individual cognitive maps maintaining the relevant information and allows decision makers know and approve the aggregation procedure.

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