This contribution provides an exhaustive explanation of the graded approach to the monotonicity property (of a fuzzy relation) and its non-graded version. Our framework is algebraic. We present a wide variety of examples to support our claims relating to the well defined notion and suitability for fuzzy rule base applications and moreover, to improve the readability of the following mathematica...

Credit-risk evaluation is a very challenging and important problem in the domain of financial analysis. Many classification methods have been proposed in the literature to tackle this problem. Statistical and neural network based approaches are among the most popular paradigms. However, most of these methods produce so-called ‘‘hard’’ classifiers, those generate decisions without any accompanyi...

Understand the behavior of Fuzzy Rule-based Systems (FRBSs) at inference level is a complex task that allows the designer to produce simpler and powerful systems. The fuzzy inference-grams –known as fingrams– establish a novel and mighty tool for understanding the structure and behavior of fuzzy systems. Fingrams represent FRBSs as social networks made of nodes representing fuzzy rules and edge...

Two main concepts are established in the literature for the Parameter Setting Problem (PSP) of metaheuristics: Parameter Tuning Strategies (PTS) and Parameter Control Strategies (PCS). While PTS result in a fixed parameter setting for a set of problem instances, PCS are incorporated into the metaheuristic and adapt parameter values according to instance-specific performance feedback. The idea o...

Although Mamdani-type fuzzy rule-based systems (FRBSs) became successfully performing clearly interpretable fuzzy models, they still have some lacks related to their accuracy when solving complex problems. A variant of these kinds of systems, which allows to perform a more accurate model representation, are the so-called approximate FRBSs. This alternative representation still cannot avoid the ...

In this paper we present an application of rule-based expert systems to a farming problem. Concretely the prediction of the breeding value in Manchego ewes is studied for the early stage of their life in which the standard (BLUP) methodology cannot be applied. In this case the pedigree index (arithmetical mean between parents’ breeding value) is used to make the estimation. An alternative to th...

The paper presents a generalization of the Pittsburgh approach to learn fuzzy classification rules from data. The proposed approach allows us to obtain a fuzzy rule-based system with a predefined level of compromise between its accuracy and interpretability (transparency). The application of the proposed technique to design the fuzzy rule-based classifier for the well known benchmark data sets ...

A robust new approach for describing and segmenting landforms which is directly applicable to precision farming has been developed in Alberta. The model uses derivatives computed from DEMs and a fuzzy rule base to identify up to 15 morphologically defined landform facets. The procedure adds several measures of relative landform position to the previous classification of Pennock et al. [39, 40]....

In this study, a fuzzy logic controller is developed using a new methodology for designing its rule-base. This controller consists of two rule-base blocks and a logical switch in between. The rule-base blocks admit two inputs one of which is newly devised and called “normalized acceleration” and the other one is the classical “error”. The newly devised input gives a relative value about the “fa...