Fuzzy Cognitive Map

The aim of this research is to analyze the relationship among Internet of Things (IoT) application factors in supply chain of home appliances industry using Fuzzy Cognitive Map (FCM). The statistical population consisted of experts in home appliance business in Bushehr province. These experts were aware of the concept of IoT and supply chain management, out of which 10 were selected. First, after reviewing the literature 38 factors were identified and then using Delphi technique and experts opinion these factors were classified into 9 groups including: product, operational processes, inventory, economics, suppliers, technical support, information, customer, and organization mission. Using Fuzzy Cognitive Map, the results show that all relationship between IoT application factors was positive and information as the most important factor that directly effects on all other factors. The results also show that customer factor was placed in the second ranked. So, home appliance industry managers should increase their competitive ability by better planning and automating processes, optimizing operations, improving customer services, and increasing capital return across the supply chain.

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.

Fund management is a major function for most financial sector enterprises with geographically dispersed activities. The risk associated to such managerial decisions affects directly the continuity, profitability and reputation of the enterprise. This paper presents a knowledge modeling methodology tool to act as a decision support mechanism for geographically dispersed financial enterprises. The underlying research addresses the problem of financial information capture and representation by utilizing the soft computing ...

Fuzzy cognitive maps (FCMs) have been used recently for representing and analysing complex systems evolving with time. Results of such analysis can be used for decision support. This paper describes the use of an FCM for analysing the diffusion process of a data warehouse in a bank. An introduction to FCMs is given, and the process of building the FCM

Urinary Tract Infection (UTI) is a bacterial infection that affects any part of the urinary tract. It can be classified as uncomplicated (patients with urinary tracts that are normal from both structural and functional perspective) and complicated. The treatment of uncomplicated urinary tract infections is a complex medical task where a number of parameters, tests, symptoms and laboratory results are present. The knowledge of physicians according to the symptoms and clinical measurements are the main point to succeed a diagnosis, suggest a therapeutic treatment and monitoring patient status. This paper presents the results of our investigation on the problem of handling medical knowledge for decision making by using the soft computing technique of fuzzy cognitive maps. The fuzzy cognitive map (FCM) is an efficient technique for modeling and representing experts' knowledge. Due to its easy graphical representation and simulation process the proposed FCM can be used to make the medical knowledge widely available through computer consultation systems.

The responsiveness and efficiency of distributed and multi-echelon supply chains are increasingly reliant upon reduced cycle times within forward and reverse logistics operations. Within the high-tech industry, Reverse Logistics (RL) in the form of end-of-life, stock balancing, defective/warranty, recycle, and re-use product returns, is particularly important owing to the complexity and dependency that exist throughout the extended supply chain in order to maintain brand loyalty and customer satisfaction (source, OEM vendors and end customers alike). RL is fast becoming a strategy to acquire an organisational competitive advantage, making the quest to exploit such a function a premeditated decision. The introduction of Third-Party Logistics (3PL) providers has become a necessity for those supply-chain operations where issues of cost and risk mitigation need to be balanced with agility and responsiveness. This paper develops a conceptual framework of the factors influencing Reverse 3PL based upon Information Systems (IS) and associated Resource Commitment (RC) factors. The framework is then tested using a mixed-method research based approach using a 3PL organisation based in Thailand. The research findings reveal that among the proposed factors, IS- and RC-based operating performance, resource cost-effectiveness and RC (at financial, managerial and technological levels in the firm) were deemed to have a stronger positive relationship and input into reverse 3PL operations for the firm in context. The model is validated using the techniques of System Dynamics and Fuzzy Cognitive Mapping.

FCMs are appropriate to explicitly encode the knowledge and experience accumulated on the operation of a complex system. Once constructed for a particular domain, an FCM allows a qualitative simulation of the system. In this paper, we investigate a first approach to introduce intuitionistic fuzzy logic into the construction process of FCMs for improved medical decision making. The theory of intuitionistic fuzzy sets provides a sound mathematical model suitable for modeling the imprecision that is inherent in real world problems. It is employed to the step where the fuzzy if-then rules are used for the determination of cause-effect relationships assigning linguistic weights among the concepts. The novel intuitionistic FCM proposed in this paper are implemented by introducing a factor of hesitancy into the weights of a standard FCM. This factor provides an additional cue on the cause-effect relationships among concepts. The results from its experimental evaluation on a medical decision making problem that is critical to patient safety, indicate its effectiveness and open perspectives for its general applicability.

ABSTRACT This paper presents an improvement in the fuzzy cognitive maps (FCMs) theory used in modelling dynamical systems. The dynamic behaviour of a system focuses on a stable behaviour reaching equilibrium state at fixed points. Multicollinearity in FCMs, is examined as a phenomenon possibly present in any dynamic modelling. Cases in which the activation level of a concept is constantly driven towards +1 or -1 are investigated. In addition, concepts stabilizing at levels other than those reflecting the actual environment are also considered. These experiments are performed by selectively inserting bias nodes in the map so as to increase the reliability of the dynamic model. Following the theoretical background of FCMs and the mathematical formulation of bias nodes we demonstrate their use and contribution in terms of a case study that deals with the Cyprus issue in view of the Turkish full EU membership.

The development of bio-refi neries has becom e a relevant topic in the EU's agenda. However, the promotion of a new indus try in rural areas is typically hindered by the scarcity of human capital, lack of information, infrastructures, and competin g interests. In this context, public support is unavoidable to assist promotion of this innovative secto r. The various policy option s reveal some strengths and drawbacks, posing the problem of fi nding the best trade-off to public decision makers. In this paper we aim at developing a methodology to support policy decision making within the biore fi nery framework, with the purpose of determining a way to identify the most suitable policy option given the actual uncertainty in developin g the bio-re fi nery industry in rural areas. The empi rical experiment, based on a simula tion of the enforcem ent of four identi fi ed policy instrument s, highlights that, although subsidies and incentives to pro fi tability of dedicated crops appe...

Supply chain is a non-deterministic system in which uncontrollable external states with probabilistic behaviors (e.g., machine failure rate) influence on internal states (e.g., inventory level) significantly through complex causal relationships. Thanks to Radio frequency identification (RFID) technology, real time monitoring of the states is now possible. The current research on processing RFID data is, however, limited to statistical information. The goal of this research is to mine bidirectional cause-effect knowledge from the state data. In detail, fuzzy cognitive map (FCM) model of supply chain is developed. By using genetic algorithm, the weight matrix of the FCM model is discovered with the past state data, and forward (what-if) analysis is performed. Also, when sudden change in a certain state is detected, its cause is sought from the past state data throughout backward analysis. Simulation based experiments are provided to show the performance of the proposed forward–backward analysis methodology.