Use Of Fuzzy Relations Research Articles

Fast and automatic hesitant fuzzy clustering applied to image segmentation

Image segmentation is a very studied area, looking for the best clustering of pixels. However, it is sometimes a complicated task, especially when these pixels are at the edges of regions, where there is a gradient and it is difficult to decide to which region to assign it. Hesitating fuzzy sets (HFS) better describe these situations, allowing to have multiple possible values for each element, giving more flexibility. This type of sets has been mainly applied in decision-making problems, obtaining better results than other types of fuzzy sets. This research proposes a fast and automatic method based on fuzzy hesitant clustering (FAHFC), which does not require parameters since it is capable of determining the number of clusters, using the Calinski-Harabasz index, in which the segmentation is performed, solving the initialization problem in clustering; it also proposes an alternative to construct the HFS through the use of fuzzy relations. The experiments show superiority in terms of clustering quality and convergence over some selected state-of-the-art algorithms.

ПІДТРИМКА ПРИЙНЯТТЯ РІШЕННЯ ЩОДО ВИБОРУ МАЙБУТНЬОЇ ПРОФЕСІЇ З ВИКОРИСТАННЯМ НЕЧІТКИХ ВІДНОСИН

The article suggests one of the ways to solve the problem of vocational guidance for applicants in choosing a future profession through the use of artificial intelligence systems, namely, fuzzy relations. On the basis of fuzzy relations, a number of additional concepts are defined that are used to construct fuzzy models of complex systems. An example of the use of fuzzy relations is provided to support the decision-making on the choice of the future profession. To clarify the result, since the Applicant can choose several professions with the same rating, was proposed to apply an alternative operation of compositing two binary fuzzy relations – (max-prod)-composition.

Toward the Use of Fuzzy Relations in the Definition of Mathematical Morphology Operators

In this paper we present a definition of erosions and dilations in terms of fuzzy relations and adjoint triples. We firstly show that we can represent any algebraic erosion and dilation in such a terms and secondly, we present a set of approaches that can be covered by our definition of relational erosions and dilations.

Use of fuzzy relations to produce landslide susceptibility map of a landslide prone area (West Black Sea Region, Turkey)

Preparation of landslide susceptibility maps is important for engineering geologists and geomorphologists. However, due to complex nature of landslides, producing a reliable susceptibility map is not easy. For this reason, many procedures have been used to produce such maps. In this study, a new attempt is tried to produce landslide susceptibility map of a part of West Black Sea Region of Turkey. To obtain the fuzzy relations for producing the susceptibility map, a landslide inventory database is compiled by both field surveys and airphoto studies. A total of 266 landslides are identified in the study area, and dominant mode of failure is rotational slide while the other mode of failures are soil flow and shallow translational slide. The landslide inventory and the parameter maps are analyzed together using a computer program (FULLSA) developed in this study. The computer program utilizes the fuzzy relations and produces the landslide susceptibility map automatically. According to this map, 9.6% of the study area is classified as very high susceptibility, 10.3% as high susceptibility, 8.9% as moderate susceptibility, 27.5% as low susceptibility and 43.8% as very low susceptibility or nonsusceptible areas. The prediction performance of the susceptibility map is checked by considering actual landslides in the study area. For this purpose, strength of the relation ( r ij ) and the root mean square error (RMSE) values are calculated as 0.867 and 0.284, respectively. These values show that the produced landslide susceptibility map in the present study has a sufficient reliability. It is believed that the approach employed in this study mainly prevents the subjectivity sourced from the parameter selection and provides a support to improve the landslide susceptibility mapping studies.

Analytical Redundancy Management in Reconfigurable Control Systems

This paper presents an approach to analytical redundancy management in control reconfigurable systems using fuzzy implication relations. The redundancy management involves a decision, upon the identification of some failures, on whether and how a control reconfiguration should take place in order to maintain a certain system performance level. It is shown that use of fuzzy relations can ensure reliable decisions. A notion of diagnostic resolution is introduced, based on which t radcoffs among diagnostic resolution, system complexity, and control robustness are delineated .

An orthodontic expert system

A Fuzzy Relational Inference Language, FRIL has been used to generate an expert system to help non-specialist dentists with orthodontic problems. The use of fuzzy relations, descriptors and numbers has been found useful in modelling the thought processes of orthodontic specialists.

Use of fuzzy relations in rule-based decision support systems for business planning problems

Most decision support systems require to formulate knowledge about behavioral relationships in terms of mathematical functions. This paper presents an alternative approach on the basis of user-supplied verbal descriptions. A motivation of this approach is the fact that many decision makers in the business domain are not accustomed to express knowledge in strict mathematical terms. Verbal descriptions are transformed into relations of fuzzy sets. Rules using only binary truth values are compared with fuzzy rules allowing gradual transition of truth values between the extremes of truth and non-truth. The paper shows how fuzzy rules may be identified on the basis of empirical data using an optimization technique. An application example demonstrates identification and use of fuzzy relations (rules) in the context of business planning problems.

Inference of a knowledge source for the recognition of nasals in continuous speech

A system for the automatic recognition of bilabial /m/ and alveolar /n/ in vowel-consonant-vowel utterances extracted from continuous speech is presented. It is based on a syntactic pattern recognition approach and the use of fuzzy relations for evaluating phonemic hypotheses. The knowledge source, based on very simple transition networks with associated simple semantic rules, is inferred from experiments. Results obtained for four male speakers are presented together with an acoustic-phonetic motivation of the approach used. These show how accounting for coarticulation effects gives substantially better performances than previous approaches.

Use Of Fuzzy Relations For Affordability De-Cisions In High Technology

Use Of Fuzzy Relations For Affordability De-Cisions In High Technology