AbstractIn this paper, we propose a Configurable Model Based DSS capable of dealing with generic problems being modeled by Linear Programming (LP) and by Fuzzy Sets (FS) in a deterministic and uncertain context, respectively. The DSS assumes the transformation of the original model with fuzzy coefficients into an equivalent crisp model where the fuzzy coefficients are represented as alpha-parametric values, which can vary in a predefined interval based on the alpha parameter. Through the DSS, solutions obtained by solving the deterministic model and the equivalent crisp model for different alpha-values are compared based on the objectives and performance parameters defined by the Decision Maker (DM). Due to the uncertainty in data, expected...
Uncertainty is a pervasive element of many real-world applications and very often existing sources o...
Full thesis submitted in paper.Fuzzy system modeling (FSM)– meaning the construction of a representa...
In this thesis, a framework for generic uncertainty analysis is developed. The two basic uncertainty...
AbstractIn this paper, we propose a Configurable Model Based DSS capable of dealing with generic pro...
[EN] In this paper, we propose a Configurable Model Based DSS capable of dealing with generic proble...
Abstract. A complex system usually encompasses agents, as they are known from modern Artificial Inte...
12a OIS TRIBUTIONAVAILABILITY STATEMENT 12t0 OSTP:BUTCT. CODE Approved For [lUllic release-, distrib...
Consideration about the possibility to integrate vague uncertainty notions into numerical simulation...
The second edition of this textbook provides a fully updated approach to fuzzy sets and systems that...
The integration of uncertainty notions into numerical simulation modeling tools is an interesting r...
The focus of this paper is to clarify the concepts of solutions of linear equations in interval, pro...
AbstractResults of research into the use of fuzzy sets for handling various forms of uncertainty in ...
In the process of solving the control tasks of complex objects often have to deal with the uncertain...
This paper presents a fuzzy set based decision support model for taking uncertainty into account whe...
Multistage decision-making in robots involved in real-world tasks is a process affected by uncertain...
Uncertainty is a pervasive element of many real-world applications and very often existing sources o...
Full thesis submitted in paper.Fuzzy system modeling (FSM)– meaning the construction of a representa...
In this thesis, a framework for generic uncertainty analysis is developed. The two basic uncertainty...
AbstractIn this paper, we propose a Configurable Model Based DSS capable of dealing with generic pro...
[EN] In this paper, we propose a Configurable Model Based DSS capable of dealing with generic proble...
Abstract. A complex system usually encompasses agents, as they are known from modern Artificial Inte...
12a OIS TRIBUTIONAVAILABILITY STATEMENT 12t0 OSTP:BUTCT. CODE Approved For [lUllic release-, distrib...
Consideration about the possibility to integrate vague uncertainty notions into numerical simulation...
The second edition of this textbook provides a fully updated approach to fuzzy sets and systems that...
The integration of uncertainty notions into numerical simulation modeling tools is an interesting r...
The focus of this paper is to clarify the concepts of solutions of linear equations in interval, pro...
AbstractResults of research into the use of fuzzy sets for handling various forms of uncertainty in ...
In the process of solving the control tasks of complex objects often have to deal with the uncertain...
This paper presents a fuzzy set based decision support model for taking uncertainty into account whe...
Multistage decision-making in robots involved in real-world tasks is a process affected by uncertain...
Uncertainty is a pervasive element of many real-world applications and very often existing sources o...
Full thesis submitted in paper.Fuzzy system modeling (FSM)– meaning the construction of a representa...
In this thesis, a framework for generic uncertainty analysis is developed. The two basic uncertainty...