Modeling of neuro-fuzzy system as a support in decision-making processes

In the paper is presented Neuro-Fuzzy System as a decision-making support in the selection of construction machines (the example of selecting a loader is provided). Construction characteristics of a loader make the basis for selection, but also other elements of importance. The data for Neuro-Fuzzy System modeling are prepared using the Multi-Criteria Decision Making (MCDM) methods: Logarithm Methodology of Additive Weights (LMAW), VIKOR, TOPSIS, MOORA and SAW. The paper also presents the method of aggregation of weights of rules premises (AWRP), which defines the key rules of Neuro-Fuzzy System. Finally, the training of the model is tested. The data for the selection of input variables and for model training are obtained by engaging experts.

Development of a methodological approach for processing different types of data in systems of special purpose

The object of research is intelligent decision making support systems. Processing different types of intelligence from a variety of information sources requires significant computational operations with strict time constraints. It leads to the search for new scientific approaches to the processing of various types of geospatial information to increase the efficiency of special purpose systems. This work solves the problem of developing a methodological approach to processing different data types in decision making support systems. During the research, the authors used the main provisions of the queuing theory, the theory of automation, the theory of complex technical systems and general scientific methods of cognition, namely analysis and synthesis. The proposed methodological approach was developed taking into account the practical experience of the authors of this work during the military conflicts of the last decade. The results of the research will be useful in: – development of new algorithms for processing different types of data; – substantiation of recommendations for improving the efficiency of processing various data types; – analysis of the operational situation during the hostilities (operations); – creating promising technologies to increase the efficiency of processing various data types; – assessment of the adequacy, reliability, sensitivity of the scientific and methodological apparatus of processing various data types; – development of new and improvement of existing simulation models of various processing data types. Areas of further research will be aimed at developing a methodology for processing various data types in intelligent decision making support systems.

Decision-Making Support for People With Alzheimer’s Disease: A Narrative Review

The proportion of people with dementia has been increasing yearly, and the decision-making capacity of these people has become a major concern in fields such as the financial industry and in medical settings. In this narrative review, we discuss decision-making in people with Alzheimer’s disease (AD), and we propose the support for decision-making in people with AD, especially financial and medical decision-making. We summarize several hypotheses and theories on the decision-making capacity of people with AD. These include the frontal lobe hypothesis, physiological theory, dysfunction of the hypothalamic-pituitary-adrenal (HPA) axis, and the Person-Task-Fit (PTF) framework. Both internal and external factors can affect decision-making by people with AD. Internal factors are affected by changes in the brain and neurotransmitters, as well as alterations in cognitive ability and emotion. External factors include task characters, task contents, and situation influence. Since feedback has a significant effect on decision-making capacity, a series of suggestions may be helpful to improve this capacity, such as explicit advice, simple options, pleasant rewards, the Talking Mats approach, memory and organizational aid, support by caregivers, cognitive training and feedback. Thus, in providing decision-making support for people with AD, it is important to identify the internal and external factors that impair this process and to deal with these factors.

Computational approach to synthesis of the multiversion structure of distributed information decision-making support system

The computational approach to synthesis of the multiversion structure of distributed information decision-making support system is presented. A formal model of the local information system is given. This system is intended to ensure the functioning of a complex control system based on the multiversion approach and consisting of a set of multiversion objects. The problem of distribution of objects by local information subsystems has been solved. For a set of valid queries in a distributed system, the answers for the decision maker are formed sequentially without repeating queries. To take into account certain requirements regarding the structure of a distributed system, it is necessary to formulate these requirements in formalized constraints and introduce them into the mathematical description of the problem. Note that the effectiveness of the targeted use of the system depends both on the results of synthesis (structure and parameters of the system) and on the correct organization of the subsystem for monitoring its technical condition during operation.