Planning the forest transport systems based on the principles of sustainable development of territories

The article identifies a new method of dynamic modeling in the design of the transport system in the forest fund (TSFF), which is based on economic and mathematical modeling and fuzzy logic tools. The combination of the indicated methods is designed to reduce the disadvantages of their use and increase the benefits. The article substantiates the choice of assessing the forecast level of the impact of risks on the activities of forestry enterprises (the method of expert assessments), using the methodological tools of fuzzy logic. The indicated method makes it possible to take into account a large variety of risk factors of the internal and external environment. At the same time, methodological aspects of fuzzy logic make it possible to formulate a quantitative assessment of qualitative indicators. The article substantiates the choice of tools for economic and mathematical modeling in order to state the design problem of the planned TSFF. Since the indicated method enables the formalization of the functioning of the timber transport system in the given conditions. The article presents a developed model that correctly takes into account the influence of risk factors when planning a TSFF, through the combination of fuzzy logic methods and economic and mathematical modeling. The advantages of the developed model include: considering the multivariance of material flows, vehicles, points of overload, etc.; automated processing of input parameters and effective data; using the model for forecasting, i.e. the possibility of deriving a fuzzy estimate of the efficiency of the timber transport system by identifying cause-effect relationships between the modeling object and the influence of risk factors on its functioning. © 2019 IOP Publishing Ltd

Modelling and optimizing multiple attribute decisions by using fuzzy sets

The purpose of this paper is to present a coherent perspective of modeling and optimizing multiple attribute decisions by using fuzzy sets. In management practice we face most of the time the situation in which a problem have several possible solutions and each solution can be analyzed using multiple criteria models. In the same time, in real life decision making process there is a given level of uncertainty which makes difficult a clear cut analytical analysis. The object of this article is to build a model approach for making multiple criteria decision using fuzzy sets of objects. Elaborating multiple attribute decisions involves performing an assessment and selecting from a given and finite set of possible alternative courses of action in the presence of a given and finite, and usually conflicting set of attributes and criteria.decision making, fuzzy sets, modeling, multiple criteria optimization.

Proposal of fuzzy object oriented model in extended JAVA

The knowledge imperfections should be considered when modeling complex problems. A solution is to develop a model that reduces the complexity and another option is to represent the imperfections: uncertainty, vagueness and incompleteness in the knowledge base. This paper proposes to extend the classical object oriented architecture in order to allow modeling of problems with intrinsic imperfections. The aim is to use the JAVA object oriented architecture to carry out this objective. In consequence, it is necessary to define the semantics for this extension of JAVA and it will be called Fuzzy JAVA. The NCR FuzzyJ library allows represent the vagueness (fuzziness) and uncertainty in class attributes. JAVA extended allows to model fuzzy inheritance.Applications in Artificial Intelligence - Knowledge EngineeringRed de Universidades con Carreras en Informática (RedUNCI

Conceptual Spaces in Object-Oriented Framework

The aim of this paper is to show that the middle level of mental representations in a conceptual spaces framework is consistent with the OOP paradigm. We argue that conceptual spaces framework together with vague prototype theory of categorization appears to be the most suitable solution for modeling the cognitive apparatus of humans, and that the OOP paradigm can be easily and intuitively reconciled with this framework. First, we show that the prototypebased OOP approach is consistent with Gärdenfors’ model in terms of structural coherence. Second, we argue that the product of cloning process in a prototype-based model is in line with the structure of categories in Gärdenfors’ proposal. Finally, in order to make the fuzzy object-oriented model consistent with conceptual space, we demonstrate how to define membership function in a more cognitive manner, i.e. in terms of similarity to prototype

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

Designing Software Architectures As a Composition of Specializations of Knowledge Domains

This paper summarizes our experimental research and software development activities in designing robust, adaptable and reusable software architectures. Several years ago, based on our previous experiences in object-oriented software development, we made the following assumption: ‘A software architecture should be a composition of specializations of knowledge domains’. To verify this assumption we carried out three pilot projects. In addition to the application of some popular domain analysis techniques such as use cases, we identified the invariant compositional structures of the software architectures and the related knowledge domains. Knowledge domains define the boundaries of the adaptability and reusability capabilities of software systems. Next, knowledge domains were mapped to object-oriented concepts. We experienced that some aspects of knowledge could not be directly modeled in terms of object-oriented concepts. In this paper we describe our approach, the pilot projects, the experienced problems and the adopted solutions for realizing the software architectures. We conclude the paper with the lessons that we learned from this experience