A Fuzzy Approach to the Synthesis of Cognitive Maps for Modeling Decision Making in Complex Systems

The object of this study is fuzzy cognitive modeling as a means of studying semistructured socio-economic systems. The features of constructing cognitive maps, providing the ability to choose management decisions in complex semistructured socio-economic systems, are described. It is shown that further improvement of technologies necessary for developing decision support systems and their practical use is still relevant. This work aimed to improve the accuracy of cognitive modeling of semistructured systems based on a fuzzy cognitive map of structuring nonformalized situations (MSNS) with the evaluation of root-mean-square error (RMSE) and mean average squared error (MASE) coefficients. In order to achieve the goal, the following main methods were used: systems analysis methods, fuzzy logic and fuzzy sets theory postulates, theory of integral wavelet transform, correlation and autocorrelation analyses. As a result, a new methodology for constructing MSNS was proposed—a map of structuring nonformalized situations that combines the positive properties of previous fuzzy cognitive maps. The solution of modeling problems based on this methodology should increase the reliability and quality of analysis and modeling of semistructured systems and processes under uncertainty. The analysis using open datasets proved that compared to the classical ARIMA, SVR, MLP, and Fuzzy time series models, our proposed model provides better performance in terms of MASE and RMSE metrics, which confirms its advantage. Thus, it is advisable to use our proposed algorithm in the future as a mathematical basis for developing software tools for the analysis and modeling of problems in semistructured systems and processes. Doi: 10.28991/ESJ-2022-06-02-012 Full Text: PD

COVID-19 and Digital Transformation -- Developing an Open Experimental Testbed for Sustainable and Innovative Environments (ETSIE) using Fuzzy Cognitive Maps

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 (Gray et al. 2013). 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.Comment: 21 pages, 11 figures and 17 tables; keywords: soft computing; fuzzy cognitive maps; digital transformation; COVID-19; decision making; sustainability; integrated world system modelin

Dynamics under Uncertainty: Modeling Simulation and Complexity

The dynamics of systems have proven to be very powerful tools in understanding the behavior of different natural phenomena throughout the last two centuries. However, the attributes of natural systems are observed to deviate from their classical states due to the effect of different types of uncertainties. Actually, randomness and impreciseness are the two major sources of uncertainties in natural systems. Randomness is modeled by different stochastic processes and impreciseness could be modeled by fuzzy sets, rough sets, Dempster–Shafer theory, etc

Big data-driven fuzzy cognitive map for prioritising IT service procurement in the public sector

YesThe prevalence of big data is starting to spread across the public and private sectors however, an impediment to its widespread adoption orientates around a lack of appropriate big data analytics (BDA) and resulting skills to exploit the full potential of big data availability. In this paper, we propose a novel BDA to contribute towards this void, using a fuzzy cognitive map (FCM) approach that will enhance decision-making thus prioritising IT service procurement in the public sector. This is achieved through the development of decision models that capture the strengths of both data analytics and the established intuitive qualitative approach. By taking advantages of both data analytics and FCM, the proposed approach captures the strength of data-driven decision-making and intuitive model-driven decision modelling. This approach is then validated through a decision-making case regarding IT service procurement in public sector, which is the fundamental step of IT infrastructure supply for publics in a regional government in the Russia federation. The analysis result for the given decision-making problem is then evaluated by decision makers and e-government expertise to confirm the applicability of the proposed BDA. In doing so, demonstrating the value of this approach in contributing towards robust public decision-making regarding IT service procurement.EU FP7 project Policy Compass (Project No. 612133

Exploring the interactions among factors impeding the diffusion of prefabricated building technologies: Fuzzy Cognitive Maps

Purpose – The purpose of this paper is to identify the interactions of factors impacting the widespread adoption of prefabricated building technologies and the intervention strategies to facilitate the development of prefabrication based on fuzzy cognitive maps (FCMs). Design/methodology/approach – Through in-depth interviews with six stakeholder groups, namely, the government, developers, designers, contractors, manufacturers and researchers, 13 critical factors were identified and used to construct stakeholder-grouped FCMs, which were further aggregated into a collective FCM. The complexity and density of the collective FCM and the centrality of factors in the FCM were examined. Subsequently, a series of “what-if” simulations of the collective FCM were conducted to analyze the effectiveness of different interventions in promoting prefabrication. Findings – The results show that three factors including market demand, cost, and policies and regulations have been mentioned by all stakeholder groups. However, these factors were ranked differently by stakeholder groups, implying that different stakeholder groups perceive the barriers to prefabricated building technologies differently. FCM simulations show that strengthening policies and regulations yield the strongest overall effect stimulating prefabrication, alleviating the organizational and environmental barriers more than the technological barriers, while improving the knowledge and expertise alleviate the technological barriers more. These measures need to be accompanied by other approaches, such as reducing cost and improving quality. Research limitations/implications – It is a tough task to promote prefabrication as it is affected by numerous barriers with complex interactions, which have been overlooked by previous studies. This study clearly shows which strategy could tackle which barriers to prefabrication through the FCM simulations. This provides valuable references for the enterprises’ decision making and the governments’ policy making to facilitate the diffusion of prefabricated building technologies. Originality/value – Few studies aim to analyze the interactions among the barriers to prefabrication, while this study specifically investigates this issue by illustrating the complex interactions using FCMs. Few studies also aim to identify the intervention strategies promoting prefabrication based on a quantitative approach, while this study employs FCM simulations to directly simulate the effectiveness of different strategies to facilitate prefabrication in a quantitative manner.Xiao-Long Gan, Rui-Dong Chang, Craig Langston, Tao We

The Encyclopedia of Neutrosophic Researchers - vol. 3

This is the third volume of the Encyclopedia of Neutrosophic Researchers, edited from materials offered by the authors who responded to the editor’s invitation. The authors are listed alphabetically. The introduction contains a short history of neutrosophics, together with links to the main papers and books. Neutrosophic set, neutrosophic logic, neutrosophic probability, neutrosophic statistics, neutrosophic measure, neutrosophic precalculus, neutrosophic calculus and so on are gaining significant attention in solving many real life problems that involve uncertainty, impreciseness, vagueness, incompleteness, inconsistent, and indeterminacy. In the past years the fields of neutrosophics have been extended and applied in various fields, such as: artificial intelligence, data mining, soft computing, decision making in incomplete / indeterminate / inconsistent information systems, image processing, computational modelling, robotics, medical diagnosis, biomedical engineering, investment problems, economic forecasting, social science, humanistic and practical achievements

Omnichannel Management in B2B. Complexity-based model. Empirical evidence from a panel of experts based on Fuzzy Cognitive Maps

In recent years, academics and professionals have proposed omnichannel management as the best approach to offering multiple channels to end customers. This approach has been reinforced by the recent crisis caused by Covid-19 and the consequent demand for digital channels. In the current literature there is an evident gap in the study of omnichannel management for manufacturing or wholesale companies and their relationships with other companies, which typically use B2B models. This article includes a model that permits the identification of causal characteristics in omnichannel management based on fuzzy cognitive maps (FCM), the simulation of possible scenarios and the impact that changes in the environment or in the organization's internal activities may have on omnichannel management. From the results of a Delphi process based on an international Panel of Experts and using complexity theory, a Fuzzy Cognitive Map (FCM) was built that can serve as a reference for B2B omnichannel management. The main value of the research is provided by the practical model that allows simulating what-if scenarios, that is, with the modification of the input conditions with respect to a base scenario and thus favors directing the omnichannel strategy to be followed in a B2B field

The Application of Artificial Intelligence in Project Management Research: A Review

The field of artificial intelligence is currently experiencing relentless growth, with innumerable models emerging in the research and development phases across various fields, including science, finance, and engineering. In this work, the authors review a large number of learning techniques aimed at project management. The analysis is largely focused on hybrid systems, which present computational models of blended learning techniques. At present, these models are at a very early stage and major efforts in terms of development is required within the scientific community. In addition, we provide a classification of all the areas within project management and the learning techniques that are used in each, presenting a brief study of the different artificial intelligence techniques used today and the areas of project management in which agents are being applied. This work should serve as a starting point for researchers who wish to work in the exciting world of artificial intelligence in relation to project leadership and management