Use Of Fuzzy Cognitive Maps Research Articles

Логистический подход к стратегическому планированию эксплуатации малоинтенсивных железнодорожных линий

Purpose: To develop a logistics approach to strategic planning for the operation of low-intensity railway lines, based on the improved concept of SPACE analysis. Methods: Methods of control theory, SPACE analysis and fuzzy cognitive modeling have been used. Results: A new approach to strategic planning of logistics processes on low-intensity railway lines is proposed based on the use of improved SPACE analysis, in terms of the use of fuzzy cognitive maps to estimate parameter values. Possible scenarios for the operation of low-intensity lines based on the concept of SPACE analysis are considered. Practical significance: The proposed logistics approach to the strategic planning of logistics processes for the operation of low-intensity lines will allow for the effective distribution of technical and technological resources, taking into account the requirements of consumers of transport services.

A fuzzy cognitive map-based algorithm for predicting water consumption in Spanish healthcare centres

The management of water consumption in healthcare centres can have positive impacts on both the environmental performance and profitability of health systems. Computational tools assist in the decision-making process of managing the operation and maintenance of healthcare centres. This research aimed to integrate the empirical knowledge of experts in Healthcare Engineering and the historical data from 66 healthcare centres in a Fuzzy Cognitive Map. The outputs of the predictive model included water consumption, water cost, and CO2 emissions in healthcare facilities, along with eleven variables to discover the causes and consequences of water consumption in healthcare centres. A healthcare centre with about 12 350 users, located in a city that experiences an average of 1100 heating degree days, whose facilities be moderately energy-efficient contributing over 50% with renewable energies is expected to consume 8.4 dam3 of water with 32.1 k€ of cost, and contribute realising 30.8 ton CO2eq emissions. The use of Fuzzy Cognitive Maps for prediction can provide a high level of effectiveness in identifying the factors that contribute to water consumption and in designing key performance indicators to manage the environmental performance of healthcare buildings. This tool is extremely effective in enhancing the performance of the management division of health systems.

Cognitive approach to the formation of a robotic system in education

The article deals with the features of modeling systems for managing educational processes using robot assistants based on a cognitive approach. The main objective of the study is the use of hybrid human-machine intelligence in the education system. The authors propose a new version of the use of fuzzy cognitive maps and the capabilities of the corresponding software systems to solve a number of practical problems using examples of automated learning. Within the framework of the cognitive approach, which allows to take into account the various linguistic features of people, it is possible to use appropriate fuzzy cognitive maps that allow you to determine cause-and-effect networks that reflect the subjective view of researchers about the system in the form of a set of semantic categories called factors or concepts.The study shows that taking into account the NON-factors that take place in the educational process, as well as the possibilities of their application for the formation of individual learning trajectories in the context of the use of human-machine intelligence, it is possible to obtain fundamentally new opportunities for training personnel.The authors propose a fuzzy cognitive model of strategic management with the participation of a robotic system, identify the main concepts for its construction and analysis. The parameters of the cognitive map are identified using the principles of intelligent generation of the best alternatives based on the modified method of pair comparisons. The study is aimed at employees of educational institutions responsible for the digitalization of education and teachers.

МНОГОФАКТОРНЫЙ КОГНИТИВНЫЙ АНАЛИЗ ЗАЩИЩЕННОСТИ ОБЪЕКТОВ КУЛЬТУРНО-ИСТОРИЧЕСКОГО НАСЛЕДИЯ РОССИИ

This article studies the issue of preserving the cultural and historical heritage of Russian cities in the face of a significant expansion of the range of threats, changes in the conditions of financing and economic activity. Analysis and ranking of risk factors for violation of the appearance and characteristics of objects of cultural and historical heritage make it possible to determine the most effective methods and means of mitigating threats and develop an optimal protection strategy. The application of analytical methods of factor analysis to solve those issues is difficult due to the qualitative nature and heterogeneity of risk factors. It is shown that the method of cognitive modeling and multivariate analysis based on a fuzzy cognitive map, which is a special type of semantic network, can be used to identify the subject area. To illustrate the proposed approach, the author opted for the State Memorial and Natural Reserve Museum-estate of L.N. Tolstoy “Yasnaya Polyana”, located in the Tula region. For the numerical solution of the issue, the author’s method of multivariate cognitive analysis based on the use of fuzzy cognitive maps by V.B. Silov. When identifying a fuzzy cognitive map, three groups of concepts were identified: threat factors; methods and means of protection; target factors. After transforming the original cognitive matrix to a transitive-closed form, the system indicators of the fuzzy cognitive map are calculated. As a result, the concepts that have a dominant weight influence on the protection of the Museum-estate “Yasnaya Polyana” are determined. The results of the study make it possible to substantiate a set of effective measures aimed at preserving the chosen object of cultural and historical heritage.

Neutrosophic Cognitive Maps for Violence Cause Analysis

Among the most valuable AI methods for modeling complicated things at the moment is the use of fuzzy cognitive mapping (FCMs). Conventional FCMs, on the other hand, can't handle the ambiguity that often arises in decision-making scenarios. A novel expansion of conventional FCMs called neutrosophic cognitive mapping (NCMs) was developed to address this shortcoming. However, the indeterminacy is not well handled by the NCMs stated in the citations since the level of indeterminacy is not quantified. In certain cases, choices should be seen as a series of steps that are only loosely related to one another. This occurs in project assessment when several activities depend on one another. Another difficult aspect of FCMs is that there isn't an appropriate topology for representing these types of decision-making difficulties. To aid in making decisions over several time periods, this research introduces a neutrosophic cognitive map built on triangular neutrosophic values (MS-TrNCM) for violence analysis. Through the use of triangular neutrosophic numbers, the suggested model allows experts to express their choices while considering various extents of truth, indeterminacy, and falsity in the underlying map linkages.

Fuzzy Cognitive Maps of Social-Ecological Complexity: Applying Mental Modeler to the Bonneville Salt Flats

Although often limited in terms of extent or accuracy, mental models—i.e., explanations of the surrounding world and how things work within it—provide confidence and frameworks to navigate life's uncertainties. Unfortunately, differing and yet similar mental models held collectively by groups can lead to problematic behavior, misunderstandings, and conflict on large scales. Such challenges are likely familiar to natural resource managers who, in the course of their work, must consider issues that are neither simple nor exclusively ecological or social in nature. Building mental models of various groups’ understanding of a complex natural resource may help managers address the impacts of resource-related behaviors but can be a difficult task when collecting modeling data from large and diverse user groups. Using a sequential, exploratory approach, our study addresses the utility of surrogate mental modeling to explore (a) mental models held by key players from six stakeholder groups associated with Utah's Bonneville Salt Flats (US), and (b) whether these key players were confident that their personal subjective models represented their own group's thinking about Bonneville. We sought to illuminate and compare stakeholder groups’ mental models of subjectively important social and ecological concepts related to Bonneville through the use of fuzzy cognitive maps (FCMs; i.e., semi-quantitative representations of mental models) constructed in Mental Modeler. Analysis revealed differences among groups’ FCMs and levels of perceived complexity, as well as areas of agreement regarding the strength, direction, and character of certain social-ecological relationships. Intersections and divergences in stakeholder mental models may provide logical starting points for communal knowledge-building that can perhaps lessen tension among groups attributable to conceptual misunderstandings of resource-specific complexity.

Understanding the Cognitive Components of Coastal Risk Assessment

Nowadays, erosion and flooding risks represent a serious threat to coastal areas and this trend will be worsened due to climate change. The increasing concentration of population in coastal areas has a negative impact on the coastal ecosystem due to change in land use and the exploitation of natural resources, which has also increased exposure to coastal hazards. Risk assessment is hence a primary topic in coastal areas and are often affected by mismanagement and competition of interest between stakeholders. This paper presents an integrated model for coastal risk assessment as well as its application on a test site in the Puglia Region (Southern Italy). An innovative approach has been developed combining a traditional index-based model, exploiting a Drivers-Pressures-State-Impact-Response framework (DPSIR), with stakeholder’s and policy makers’ engagement by using the Future Workshop method and complementary individual working sessions structured through the use of Fuzzy-Cognitive Maps. The study shows that stakeholders’ and policy makers’ risk perception play a key role in coastal risk management and that the integration of physical risk with social perception is relevant to develop more effective management following the basics of Integrated Coastal Zone Management.

Unveiling the dynamics of social credit determinants using fuzzy cognitive mapping and system dynamics

AbstractFighting poverty and social inequality are baseline principles of social credit. This type of microcredit has thus increasingly attracted academics and practitioners’ attention, particularly after Muhammad Yunus was awarded the 2006 Nobel Peace Prize. Researchers acknowledge that social credit is extremely important and that it should be taken seriously. However, studies examining the dynamics of its determinants are still extremely rare. This gap needs to be filled because the objectives of social credit are quite different from those of other types of credit, going beyond profit and embracing social concerns. Adopting a constructivist, process‐oriented stance that combined fuzzy cognitive mapping and the system dynamics (SD) approach, the present research sought to develop and analyze a cognitive structure that elucidates the dynamics of social credit determinants over time. Face‐to‐face group work sessions were held with a panel of professional credit analysts, and the results reveal that the combined use of fuzzy cognitive mapping and SD provides a clearer understanding of the dynamics of these determinants over time. The advantages, limitations, and implications of the proposed methodology are discussed.

Means of IoT and Fuzzy Cognitive Maps in Reactive Navigation of Ubiquitous Robots

Development of accessible and cheap sensors as well as the possibility to transfer and process huge amounts of data offer new possibilities for many areas utilizing till now conventional approaches. Navigation of robots and autonomous vehicles is no exception in this aspect and Internet of Things (IoT), together with the means of computational intelligence, represents a new way for construction and use of robots. In this paper, the possibility to move sensors from robots to their surroundings with the help of IoT is presented and the modification of the IoT concept in the form of intelligent space as well as the concept of ubiquitous robot are shown in the paper. On an example of route tracking, we will clarify the potential of distributed networked sensors and processing their data with the use of fuzzy cognitive maps for robotic navigation. Besides, two modifications of adaptation approaches, namely particle swarm optimization and migration algorithm, are presented here. A series of simulations was performed, which are discussed and future research directions are proposed.

Key Factors in the Implementation of the Internet of Things in the Hotel Sector

Many factors can influence decision-making, and if you wish to know which are the most influential factors in a decision, they must be classified by their degrees of influence. This study seeks to determine the most influential factors in the decision of hotels to accept and implement the Internet of Things in their services through a literary review and a causal study carried out on experts in technology and hotels. The methodology involves the use of fuzzy cognitive maps and the FCMappers tool. The results obtained show that the following factors are among the most influential (in order of relevance): the perceived reliability of the technology, the relative advantage it gives, the level of top management support, compatibility, customer pressure, information systems provider support, security, business partner pressure, characteristics of the leader or manager, government pressure or incentives, pressure from competitors, technological organizational readiness, complexity, size of the company, and the perceived cost.

Detecting Errors in Cognitive Models Using Visualization Metaphors of Fuzzy Cognitive Maps

Verification of cognitive models is one of the most important stages in their construction, since reliability of results of subsequent modeling largely depends on the successful implementation of verification. The paper considers the problem of verifying cause-and-effect relationships in cognitive models based on the use of fuzzy cognitive maps. It is noted that increasing the effectiveness of cognitive model verification is possible by activating analyst's cognitive potential. The most natural way of such activation is to increase cognitive clarity of the model through the use of visualization capabilities. For this purpose, a number of metaphors for visualizing fuzzy cognitive maps have been proposed, aimed at increasing their cognitive clarity during verification. Each of the metaphors is focused on the visualization of a certain type of fragments of a fuzzy cognitive map potentially containing errors, redundancy or incompleteness and therefore of interest from the point of view of verification. The first considered visualization metaphor is intended to display the cycles that are part of a cognitive graph. The second metaphor focuses on the mapping of transitive paths between concepts. Finally, the third metaphor is aimed at eliminating cognitive model incompleteness, which consists in the lack of relationships between some concepts. Examples are given of applying the proposed visualization metaphors to increase cognitive clarity of the visual image of the verified fuzzy cognitive map.

Towards the Operationalization of the Value Creation Network in Airlines

In times of uncertainty like the present, value creation is a critical factor that determines airlines’ competitive capacity and their ability to survive. Understanding the value creation process in a more realistic way and facilitating a tool that helps managers to anticipate performance under simulated scenarios is the objective of this article. A Delphi survey of 28 executives from major airlines around the world was conducted that procured the knowledge for the so-called Airline Value Creation Network (AVCN), an operational analytical framework presented in this article along with its benefits and limitations. Implications for researchers and managers are discussed. For researchers, novel data and methodological inroads are offered that address the creation of value as a complex adaptive system. The use of Fuzzy Cognitive Maps for modeling and simulation proves to be a viable computational method in this context. For managers, the research reveals key empirical evidence of reality that explains the creation of value as a network and provides an easy-to-use, fast-to-grow tool that can help inform airlines' value creation policies and decision-making.

The relationship between organizational culture and the performance of a technology startup: A Fuzzy Cognitive Maps based analysis

New organizations, such as startups, are more exposed to failure due to their vulnerability when arriving the market. Therefore, monitoring and managing performance indicators becomes essential, since they enable the achievement of strategic objectives. However, this process is impacted by the organizational culture, which guides the company’s behavioral patterns. Therefore, this paper proposes the use of fuzzy cognitive maps to quantify the causal relations between Hofstede's cultural dimensions and the performance of a technology startup. The employed methodology is composed of three stages: literature review, computational model development and conduction of an illustrative application. It is classified as quantitative, axiomatic and normative, since it proposes a model from the identified gaps and the opinions of specialists, suggesting an approach that integrates the research concepts. The results indicate that the time for development is the most impacted indicator by culture. It can be concluded, therefore, that it was possible to consider the inherent subjectivity to the evaluation of the causal relations between culture and performance by applying the fuzzy cognitive map. Hence, action plans can be proposed to foster improvement initiatives that promote the culture-performance alignment.

Participatory modelling for poverty alleviation using fuzzy cognitive maps and OWA learning aggregation.

Participatory modelling is an emerging approach in the decision-making process through which stakeholders contribute to the representation of the perceived causal linkages of a complex system. The use of fuzzy cognitive maps (FCMs) for participatory modelling helps policy-makers develop dynamic quantitative models for strategising development interventions. The aggregation of knowledge from multiple stakeholders provides consolidated and more reliable results. Average aggregation is the most common aggregation method used in FCMs-based modelling for weighted interconnections between concepts. This paper proposes a new aggregation method using learning OWA (ordered weighted averaging) operators for aggregating FCM weights assigned by various stakeholders. Besides, we report a comparative analysis of 'OWA learning aggregation' with the conventional average aggregation method, while evaluating the theory of change for the world's most extensive poverty alleviation programme in India. The results of the FCMWizard web-based tool show that the proposed method provides an opportunity to policy-makers for evaluating outcomes of proposed policies while addressing social resilience and economic mobility.

Use of fuzzy cognitive maps to develop policy strategies for the optimization of municipal waste management: A case study of the land of fires (Italy)

This paper applies an analytical method for developing policy strategies to optimize municipal waste management systems (MWMSs) to the case of the Land of Fires (LoF). The LoF is an area of Italy’s Campania region that is characterized by a legacy of authoritarian environmental governance and the improper dumping and burning of waste. In this paper, we employ the fuzzy cognitive maps (FCM) method, which draws on a participatory approach. Specifically, the complexity of the investigated system was determined from the causal relations identified by relevant stakeholders and experts. The results show that the most effective policy strategies to improve the LoF MWMS, as identified by informants, include: fostering social innovation (e.g. communication and information campaigns); promoting technological innovation (e.g. material and process design); and supporting scientific and technological cooperation among actors. The overall diversity of the identified policy strategies suggests that policy makers must move beyond a simple “best option” approach, given the systemic complexity of the waste management sector.

Multidimensional medical data modeling based on fuzzy cognitive maps and k-means clustering

Abstract The paper concerns the use of fuzzy cognitive maps and k-means clustering to solve the problem of modeling multidimensional medical data. A fuzzy cognitive map is a recurrent neural network that describes the analyzed phenomenon in the form of key concepts and causal relationships between them. It is an effective tool for modeling decision support systems and is widely used in medicine. The aim of this paper is to analyze the use of fuzzy cognitive maps with k-means clustering to model decision support systems based on multidimensional data related to Parkinson’s disease. K-means method was applied to group the data, and then a separate fuzzy cognitive map was built for each cluster to increase forecasting accuracy. The learning process was realized with the use of the previously developed Individually Directional Evolutionary Algorithm. The obtained results confirm that the analyzed approach provides much better forecasting accuracy than the standard approach based on one model.

Анализ рисков кибербезопасности с помощью нечетких когнитивных карт

Анализ рисков кибербезопасности с помощью нечетких когнитивных карт

Cognitive modelling of Chinese herbal medicine's effect on breast cancer.

Traditional Chinese medicine (TCM) has recently attracted increasing interests in cancer treatment. It was found that TCM-based treatment, combined with other therapies, can help improve patients' life quality. However, the existing research in TCM lacks a systematic modelling for the causal relationship of the factors related to the diagnosis and decision making. In this paper, we proposed the use of fuzzy cognitive map (FCM) to represent the cognition of TCMs usage in cancer treatment. Through a case analysis, we analyse and summarise the effects of Chinese herbal medicine in breast cancer management. FCMs can visually represent the cognitive knowledge, particularly the causal relationship among key factors of TCM effects and the related breast cancer status.

ANALYZING THE DETERMINANTS OF E-COMMERCE IN SMALL AND MEDIUM-SIZED ENTERPRISES: A COGNITION-DRIVEN FRAMEWORK

The increasing use of information technology in enterprises’ daily operations has led to multiple innovative ways to run a business, including electronic commerce (hereafter, e-commerce). However, firms with fewer resources, such as small and medium-sized enterprises (SMEs), are more reluctant to use electronic channels during transactions. This aversion to contemporary business models is a result of these companies’ lack of knowledge and capabilities regarding e-commerce. To improve their businesses, SMEs’ managers and decision makers could benefit from a methodological framework that fosters a deeper understanding of the determinants of e-commerce. This study sought to explore the use of fuzzy cognitive mapping to address this need. The results are grounded in the knowledge and experience of a panel of experts in e-commerce. The fuzzy cognitive map (FCM) developed shows that entrepreneur profile, market, operational management, marketing and promotions, website and digital platform, and products present the highest centrality indices as determinants of SME e-commerce. The findings offer a better understanding of the cause-and-effect relationships between these determinants. The advantages, limitations, and shortcomings of our constructivist proposal are also discussed.

The use of fuzzy cognitive maps in the development of an experimental model of automation of production accounting of material flows

Automation of enterprise management on the basis of economic and mathematical models, information technology is one of the main stages of development for all enterprises. The use of cognitive modeling allows making management decisions under uncertainty. The article considers the construction of an experimental model of automation of production accounting of material flows based on the use of fuzzy cognitive maps. The algorithm of cognitive modeling is presented. The main advantages of cognitive tools are noted: 1) the ability to study the fine structure of management decisions (the necessary sequence of management actions, the necessary degree of activity of these actions, the study of the dynamic stability of strategies, etc.); 2) the opportunity to explore the dynamics of management decisions at a qualitative level, without attracting for this purpose hard-to-access and not always reliable quantitative information, which is extremely important in a rapidly changing business environment and the growing pace of technological innovation.It is emphasized that none of the known management support tools has the above capabilities. Cognitive dynamic analysis significantly expands the tool base of management, based today mainly on the means of static situational analysis and prescription schemes of decision-making.In the construction of the experimental model, the target factors of the cognitive map are determined, the connectivity analysis is carried out and the process of propagation of disturbances on the graph is studied.The analysis showed that the proposed model is quite efficient and can be used to predict economic activity and determine the expected values of a number of parameters that need to be monitored to diagnose trends in the development of an industrial enterprise. The results of the work should be considered as a solution to a number of management tasks.