This paper introduces an application of type-2 fuzzy sets in data linguistic summarization. The original approach by Yager (1982) based on representing natural language statements via type-1, i.e., the Zadeh sets, is generalized with applied as models linguistically expressed quantities and/or properties objects. Type-2 extend known summarization procedures handling values stored databases, and allow to represent a term few different membership functions (e.g., provided experts), which makes...

The discussion in this paper is closely related to our idea of <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">a type-2 linguistic summary a database</i> presented by Niewiadomski [A. Niewiadomski, ¿A fuzzy approach summarization data,¿ xmlns:xlink="http://www.w3.org/1999/xlink">IEEE Trans. Fuzzy Syst.</i> , vol. 16, no. 1, pp. 198-213, Feb. 2008], which intended be an efficient tool knowledge discovery from large databases. In that approach, we...

The paper contains remarks on similarities and differences between interval-valued interval type-2 fuzzy sets. definitions of basic characteristics, like cardinality or support, are provided related to the canonical forms linguistically quantified propositions under both groups sets, discussed real degrees truth proposed. In conclusions, advantages drawbacks methods shown, briefly commented linked with context knowledge mining via so-called data linguistic summarization.

Automatic summary of databases is an important tool in strategic decision-making. This paper applies the concept linguistic summaries to outlier detection. The definition closely related type data analyzed and its context. Outlier detection data-mining technique, which finds applications a wide range domains. It can identify defects, remove impurities from data, and, most all, it significant decision-making processes. authors propose novel outlier, based on quantifiers summaries. Linguistic...

Automatic summary of databases is an important tool in strategic decision-making. This paper presents the application linguistic summaries to outlier detection containing both text and numeric attributes. The proposed method applies Yager's standard based on interval-valued fuzzy sets. Fuzzy similarity measures are features which looked for. Detection outliers can identify defects, remove impurities from data, and, most all, it may provide basis for decision-making processes. In this paper,...

The main aim of this work is the estimation health risks arising from exposure to ozone or other air pollutants by different statistical models taking into account delayed effects. This paper presents risk hospitalization due bronchitis and asthma exacerbation in adult inhabitants Silesian Voivodeship 1 January 2016 31 August 2017. Data were obtained daily register hospitalizations for acute (code J20–J21, International Classification Diseases, Tenth Revision – ICD-10) (J45–J46) which...

Abstract The problem of note onset detection in musical signals is considered. proposed solution based on known approaches which an function defined the basis spectral characteristics audio data. In our approach, several functions are used simultaneously to form input vector for a multi-layer non-linear perceptron, learns detect onsets training This contrast standard methods thresholding with moving average or median. Our approach also different from most current machine-learning-based...

Calculation of similarity measures exact matching texts is a critical task in the area pattern that needs great attention. There are many existing literature but best methods do not exist for closeness measurement two strings. The objective this paper to explore grammatical properties and features generalized n-gram technique find text electronic computer applications. Three new have been proposed improve performance method. assigned high values price with low running time. experiment...

Abstract The article presents our research on applications of fuzzy logic to reduce air pollution by DeNOx filters. aim is manage data Selective Catalytic Reduction (SCR) process responsible for reducing the emission nitrogen oxide (NO) and dioxide (NO 2 ). Dedicated traditional Fuzzy Logic Systems (FLS) Type-2 (T2FLS) are proposed with use new methods learning rules types implications (the so-called ”engineering implications”). obtained results consistent provided experts. main advantage...

Abstract This paper presents research on applications of fuzzy logic and higher-order systems to control filters reducing air pollution [1]. The use Selective Catalytic Reduction (SCR) method and, as for now, this process is controlled manually by a human expert. goal the an SCR system responsible emission nitrogen oxide (NO) dioxide (NO2) air, using with ammonia (NH3). There are two presented, applying interval-valued sets type-2 sets, respectively. Fuzzy higher order describe...

Abstract Uncertainty appearing in datasets (stochastic, linguistic, of measurements, etc.), if not handled properly, may negatively affect information analysis or retrieval procedures. One possible methods dealing with uncertain (rare, strange, unexampled) data is to treat them as “outliers” “exceptions”. Among different definitions and algorithms for detecting outliers, we are especially interested those based on linguistic represented type-2 fuzzy logic. We introduce new outliers terms...

An approach to performing linguistic summaries of graph datasets, with particular focus on usage ontologies is presented in this paper. This well-known mining technique based fuzzy set theory, which used model natural language words (e.g. 'many', 'tall'), and result - generates na tural-like sentences describing the data. Although intensely developed, before our work method has been applied only relational databases, while more data available model. A special case such datasets Semantic Web,...