Article
Computer Science, Artificial Intelligence
Chao Wang, Jing Liu, Kai Wu, Chaolong Ying
Summary: IBMTEA-FCM is a random inactivation-based batch many-task evolutionary algorithm proposed to learn large-scale FCMs. By modeling the FCM learning problem as a many-task optimization problem, separating tasks into batches, and employing a many-task framework, IBMTEA-FCM achieves higher accuracy and lower computational cost in learning large-scale FCMs compared to existing classical methods.
APPLIED SOFT COMPUTING
(2021)
Article
Computer Science, Artificial Intelligence
Yihan Wang, Fusheng Yu, Wladyslaw Homenda, Witold Pedrycz, Yuqing Tang, Agnieszka Jastrzebska, Fang Li
Summary: This article proposes an adaptive fuzzy cognitive map (FCM) method based on trend fuzzy granules for long-term time series prediction. Compared with traditional models, this method overcomes the cumulative errors caused by iterations and achieves better prediction performance.
IEEE TRANSACTIONS ON FUZZY SYSTEMS
(2022)
Article
Automation & Control Systems
Guoliang Feng, Wei Lu, Witold Pedrycz, Jianhua Yang, Xiaodong Liu
Summary: A direct, rapid, and robust learning method is proposed in this article to learn fuzzy cognitive maps (FCMs) from noisy data, especially for large-scale FCMs. By transforming the learning problem of FCMs into a classic-constrained convex optimization problem, the proposed algorithm ensures the robustness of the learned FCM and regularizes the distribution of the weights.
IEEE TRANSACTIONS ON CYBERNETICS
(2021)
Article
Green & Sustainable Science & Technology
Oguz Emir, Sule Onsel Ekici
Summary: In recent years, waste management has gained attention due to sustainability concerns and the depletion of natural resources. Food waste management is particularly important given the growing population and hunger crisis. Integrated assessment models (IAMs) have been commonly used to study food waste and provide insights to policymakers, while the Fuzzy Cognitive Map (FCM) extended with intuitionistic fuzzy sets offers a framework for analyzing interactions between factors and prioritizing policies.
JOURNAL OF CLEANER PRODUCTION
(2023)
Article
Computer Science, Artificial Intelligence
Mehrin Kiani, Javier Andreu-Perez, Hani Hagras, Elpiniki Papageorgiou, Mukesh Prasad, Chin-Teng Lin
Summary: This article presents a novel approach to estimate effective connectivity in human brain signals, using enhanced fuzzy cognitive maps. The proposed method outperforms other methods and provides insights into the role of oxyhemoglobin and deoxy-hemoglobin in cognitive activity.
IEEE TRANSACTIONS ON COGNITIVE AND DEVELOPMENTAL SYSTEMS
(2022)
Article
Computer Science, Artificial Intelligence
Piotr Szwed
Summary: Fuzzy Cognitive Maps (FCMs) are a soft computing technique used in various fields like system behavior modeling, time series prediction, decision making, and process control. This study introduces an FCM based classifier with a fully connected map structure, learning weights with a gradient algorithm. The aim is to create a descent general purpose classifier with performance comparable to classical methods, and preliminary results show promising outcomes.
APPLIED SOFT COMPUTING
(2021)
Article
Computer Science, Information Systems
Yuzhen Li, Yabin Shao
Summary: In real life, uncertainty problems arise due to the vagueness of concepts, making it difficult to determine if an object conforms to a particular concept. Fuzzy methods are suitable for dealing with such uncertain events. The D-number cognitive maps and D-number fuzzy cognitive maps are intelligent framework models that can handle multiple sources of information with uncertainty and incomplete information, addressing the challenge of knowledge combination.
Article
Computer Science, Artificial Intelligence
Tianming Yu, Qunfeng Gan, Guoliang Feng, Guangxin Han
Summary: In recent years, classification based on fuzzy cognitive maps (FCM) has attracted extensive attention and has been successfully applied in many engineering problems. However, existing methods lack universality and low classification accuracy. In this study, a new model integrating capsule network into inference rules is proposed to enhance the interpretability, universality, and classification performance. Experimental results demonstrate the superiority of the proposed method over low-level cognitive maps.
KNOWLEDGE-BASED SYSTEMS
(2022)
Article
Computer Science, Artificial Intelligence
Istvan A. Harmati, Miklos F. Hatwagner, Laszlo T. Koczy
Summary: Fuzzy cognitive maps are an effective modeling tool for complex systems. Global stability is not always essential, as multiple fixed points are preferred in many applications.
NEURAL COMPUTING & APPLICATIONS
(2023)
Article
Computer Science, Artificial Intelligence
Abdullah Almuhaimeed, Mohammed A. Alhomidi, Mohammed N. Alenezi, Emad Alamoud, Saad Alqahtani
Summary: With the widespread of data resources on the internet, overlapping between these resources can provide researchers with more information. Extracting and calculating the semantic similarity between these resources is a challenging task due to their varying descriptions. To address this issue, the paper presents a new semantic similarity method that considers different factors to calculate the semantic similarity between different resources. By utilizing node descriptions and relations from multiple ontologies, this method strengthens the similarity relations between resources and discovers new semantic similarities.
EXPERT SYSTEMS WITH APPLICATIONS
(2022)
Article
Computer Science, Artificial Intelligence
Gonzalo Napoles, Nevena Rankovic, Yamisleydi Salgueiro
Summary: This paper proposes a post-hoc explanation method for computing concept attribution in Fuzzy Cognitive Map (FCM) models, which combines SHapley Additive exPlanations (SHAP) values and the dynamic properties of the FCM model. The relevance of neural concepts is computed by considering the initial activation values and hidden states of the model. Experimental results demonstrate the effectiveness of the proposed method.
KNOWLEDGE-BASED SYSTEMS
(2023)
Article
Computer Science, Interdisciplinary Applications
Hilla De-Leon, Dvir Aran
Summary: Since the first detection of SARS-CoV-2 in China three years ago, hundreds of millions of people have been infected and millions have died. The COVID-19 epidemic has emphasized the need for mathematical models that can accurately predict the spread of the pandemic. The susceptible-infectious-removed (SIR) model has been widely used but with limited success. In this study, a dynamic Monte-Carlo Agent-based Model (MAM) is introduced, which outperforms the SIR model in predicting the outbreak of COVID-19.
JOURNAL OF BIOMEDICAL INFORMATICS
(2023)
Article
Computer Science, Artificial Intelligence
Omid Orang, Petronio Candido de Lima e Silva, Frederico Gadelha Guimaraes
Summary: Among various soft computing approaches, fuzzy cognitive maps (FCMs) have shown remarkable results in time series forecasting. FCMs are a mixture of fuzzy logic, neural network, and expert system aspects, making them a powerful tool for simulating and studying complex systems. This survey paper presents an overview of the most relevant FCM-based time series forecasting models and provides ideas for future research to enhance their capabilities.
ARTIFICIAL INTELLIGENCE REVIEW
(2023)
Article
Mathematics
Alina Vladimirovna Petukhova, Anna Vladimirovna Kovalenko, Anna Vyacheslavovna Ovsyannikova
Summary: This paper proposes a scenario analysis algorithm based on fuzzy cognitive maps for decision support in complex systems. The algorithm effectively obtains the initial state of the system using the theory of neutrosophic fuzzy equations, reducing the time required for problem-solving.
Article
Medicine, General & Internal
Anand Krishnan, Lalit Dar, Ritvik Amarchand, Aslesh Ottapura Prabhakaran, Rakesh Kumar, Prabu Rajkumar, Suman Kanungo, Sumit Dutt Bhardwaj, Avinash Choudekar, Varsha Potdar, Alok Kumar Chakrabarti, C. P. Girish Kumar, Giridara Gopal Parameswaran, Shivram Dhakad, Byomkesh Manna, Ashish Choudhary, Kathryn E. Lafond, Eduardo Azziz-Baumgartner, Siddhartha Saha
Summary: This study focuses on a multicentric community-dwelling cohort of older adults in India to estimate incidence, study risk factors, healthcare utilisation, and the economic burden associated with influenza and RSV. It involves participants from four sites, where data collection and surveillance have begun, including the identification of individual and household-level risk factors for acute respiratory infections.
Article
Physics, Multidisciplinary
Philip Rutten, Michael H. Lees, Sander Klous, Peter M. A. Sloot
Summary: The study investigates human motion patterns at a large dance event, finding intermittent and persistent motion patterns among participants. It reveals that displacement distributions deviate from exponential distribution and are best fit by a stretched exponential distribution. Although no evidence of Levy walks is found, individuals exhibit directional persistence and superdiffusivity within the scale set by the stadium size.
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
(2021)
Article
Computer Science, Theory & Methods
Nikolay O. Nikitin, Pavel Vychuzhanin, Mikhail Sarafanov, Iana S. Polonskaia, Ilia Revin, Irina V. Barabanova, Gleb Maximov, Anna Kalyuzhnaya, Alexander Boukhanovsky
Summary: The proposed approach aims to automate the design of composite machine learning pipelines, combining key ideas of automated machine learning and workflow management systems. It provides additional algorithms for flexibility in identifying pipeline structure, sensitivity analysis, atomization, and hyperparameter tuning. Experimental results confirm the correctness and effectiveness of the approach in various tasks.
FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE
(2022)
Letter
Multidisciplinary Sciences
Karoline B. S. Huth, Adam Finnemann, Maarten W. J. van den Ende, Peter M. A. Sloot
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
(2022)
Article
Multidisciplinary Sciences
Valentin R. Melnikov, Georgios Christopoulos, Valeria V. Krzhizhanovskaya, Michael H. Lees, Peter M. A. Sloot
Summary: Urban heat islands and other phenomena have raised concerns about the outdoor thermal comfort of city residents. Designing urban spaces that ensure and promote pedestrian thermal comfort is a major challenge for large cities. Understanding pedestrian behavior in urban thermal environments is crucial for achieving this goal. However, current research lacks controlled experimentation, which hinders the quantitative modeling of such complex behavior.
SCIENTIFIC REPORTS
(2022)
Article
Engineering, Multidisciplinary
Koen van der Zwet, Ana Barros, Tom M. van Engers, Peter M. A. Sloot
Summary: This paper analyzes the contributions of computational modeling methods for the analysis of insurgent conflicts. Through studying 64 computational models, the authors identify promising directions and topics for designing specific simulation models, as well as specific pitfalls in validity issues for each modeling method.
JOURNAL OF DEFENSE MODELING AND SIMULATION-APPLICATIONS METHODOLOGY TECHNOLOGY-JDMS
(2022)
Review
Psychology, Clinical
Maarten W. J. van den Ende, Sacha Epskamp, Michael H. Lees, Han L. J. van der Maas, Reinout W. Wiers, Peter M. A. Sloot
Summary: This paper reviews and categorizes formal models of addiction, including psychological and social models. The authors argue that these models are too disjointed and recommend integrating intra- and inter-individual factors to unravel the complexities of addiction.
ADDICTIVE BEHAVIORS
(2022)
Review
Endocrinology & Metabolism
Nadege Merabet, Paul J. Lucassen, Loes Crielaard, Karien Stronks, Rick Quax, Peter M. A. Sloot, Susanne E. la Fleur, Mary Nicolaou
Summary: Chronic stress contributes to the onset of type 2 diabetes, but the exact mechanisms are not fully understood. Responses to stress are influenced by various factors and involve a complex network of neurotransmitters and hormones. Stress can also be influenced by behavioral, metabolic, and environmental factors. Therefore, studying the impact of chronic stress on metabolic health is a complex and emergent process.
FRONTIERS IN NEUROENDOCRINOLOGY
(2022)
Article
Critical Care Medicine
Paul P. M. van Zuijlen, H. Ibrahim Korkmaz, Vivek M. Sheraton, Tsjitske M. Haanstra, Anouk Pijpe, Annebeth de Vries, Cornelis H. van der Vlies, Eelke Bosma, Evelien de Jong, Esther Middelkoop, Fred J. Vermolen, Peter M. A. Sloot
Summary: Healthcare is undergoing a technological transformation, and professionals in burn care need to adapt to these changes with new thinking and strategies. Complexity science provides direction for the future of burn care by studying the interactions between different components and their environment, helping to manage complex situations.
JOURNAL OF BURN CARE & RESEARCH
(2022)
Article
Psychology, Multidisciplinary
Loes Crielaard, Jeroen F. Uleman, Bas D. L. Chatel, Sacha Epskamp, Peter M. A. Sloot, Rick Quax
Summary: This article describes the process of using causal loop diagrams (CLDs) and computational system dynamics models (SDMs) to study and simulate complex problems. By incorporating expert knowledge and converting it into a computational model, we can better understand the interactions and effects of different parts of a system, as well as the outcomes under different conditions. This approach can be applied to a broader range of complex problems and advances the application of computational science methods to biopsychosocial systems.
PSYCHOLOGICAL METHODS
(2022)
Editorial Material
Computer Science, Interdisciplinary Applications
Sergey Kovalchuk, Valeria V. Krzhizhanovskaya, Maciej Paszynski, Dieter Kranzlmuller, Jack Dongarra, Peter M. A. Sloot
JOURNAL OF COMPUTATIONAL SCIENCE
(2022)
Article
Multidisciplinary Sciences
Philip Rutten, Michael H. Lees, Sander Klous, Hans Heesterbeek, Peter M. A. Sloot
Summary: Understanding contact patterns in crowd movement is important for assessing infection spread at mass gathering events. This study uses Wi-Fi mobility data from sports and entertainment events in the Johan Cruijff ArenA stadium in Amsterdam to examine contact patterns. The results show that crowd movement at these events is not uniform, but consists of alternating periods of movement and rest. Contact duration distributions are heavy-tailed, which challenges existing models. The study also investigates the impact of heavy-tailed contact duration on infection spread using random walk models, finding that increased contact duration can pose a higher transmission risk than increased contact frequency.
SCIENTIFIC REPORTS
(2022)
Article
Critical Care Medicine
Alex R. R. Schuurman, Peter M. A. Sloot, W. Joost Wiersinga, Tom van der Poll
Summary: "Sepsis through the lens of complexity theory" is an article that discusses the importance of understanding the complexity of sepsis and highlights the role of computational modeling and network-based analysis in this regard. The article also identifies barriers in measurement, research approaches, and clinical applications and advocates for more continuous biological data collection in sepsis. The authors emphasize the importance of interdisciplinary collaboration and provide an example of an immunological predictive model that could inform personalized treatments.
Article
Health Care Sciences & Services
Gabriele Spini, Emiliano Mancini, Thomas Attema, Mark Abspoel, Jan de Gier, Serge Fehr, Thijs Veugen, Maran van Heesch, Daniel Worm, Andrea De Luca, Ronald Cramer, Peter M. A. Sloot
Summary: This paper presents a novel and efficient approach to HIV clinical decision support systems, which extracts valuable information from patient records to assist treatment prescription while preserving privacy and confidentiality.
JOURNAL OF MEDICAL SYSTEMS
(2022)
Meeting Abstract
Cell Biology
H. Ibrahim Korkmaz, Vivek M. Sheraton, Anouk Pijpe, Bouke B. Boekema, Evelien De Jong, Stephan G. F. Papendorp, Esther Middelkoop, Peter M. A. Sloot, Paul P. M. Van Zuijlen
WOUND REPAIR AND REGENERATION
(2022)
Article
Humanities, Multidisciplinary
Koen van der Zwet, Ana Barros, Tom M. van Engers, Peter M. A. Sloot
Summary: The outbreak of the COVID-19 pandemic has led to a surge in protests. This paper proposes a holistic approach to explore the relationship between societal conditions and the emergence of protests during the pandemic. A quantitative analysis comparing protest dynamics in 27 countries is conducted using statistical and computational modelling. The results highlight the need for alternative modelling approaches to better capture the complexity and underlying dynamics of protests.
HUMANITIES & SOCIAL SCIENCES COMMUNICATIONS
(2022)
