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PL
Artykuł przedstawia podejście do identyfikacji rodzaju szkła oparte na teorii zbiorów przybliżonych w programie RSES. Przedstawiono teoretyczne podstawy tej metody, opisano proces analizy danych oraz zaprezentowano wyniki identyfikacji rodzaju szkła.
EN
The article presents an approach to glass type identification based on rough set theory in the RSES program. The theoretical basis of this method is presented, the data analysis process is described and the results of glass type identification are presented.
PL
Artykuł skupia się na analizie danych z wykorzystaniem teorii zbiorów przybliżonych oraz różnych metod, takich jak algorytm genetyczny, klasyfikacja za pomocą zestawu reguł i metoda walidacji krzyżowej. Przedstawiono także kompletny proces analizy danych przy użyciu programu RSES. Wykorzystany zbiór danych oraz wyniki analizy zostałyomówione w kontekście teorii zbiorów przybliżonych. Artykuł kończy się podsumowaniem i wnioskamiskupiającymi się na aspekcie skuteczności wspomnianych metod w analizie zbioru danych oraz efektywności programu w kwestii przeprowadzania w nim analiz.
EN
The article focuses on data analysis using rough set theory and various methods such as the genetic algorithm, rule set classification and the cross-validation method. The complete data analysis process using RSES is also presented. The data set used and the results of the analysis are discussed in the context of rough set theory. The article concludes with a summary and conclusions focusing on the aspect of the effectiveness of aforementioned methods in analysing the dataset and the efficiency of the programin terms of performing analysis in it.
EN
The Lower Indus River (LIR) in the Southern Sindh has experienced by multiple measurable changes in its planform and longitudinal profiles over the last 100 years. This research deals with a hydrodynamic model coupled with rough set theory (RST) model findings that accounts for the prediction of lateral and vertical morphodynamic evolution observed over the 32 km reach during the flood episode of 2020. Human interferences and hydrodynamic aspects during high flood periods were assessed in the context of channel morphology. Surveyed cross-sections were used to construct the geometry using two-dimensional (2D) Hydrologic Engineering Center's River Analysis System (HEC-RAS) model, and simulation was completed under the unsteady flow values among the highest runoff and bankfull values. The island and natural bend of the river have higher values of velocities and shear stresses, and consequently higher erosion and incision rate was observed. The bank erosion was computed with high precision (R2 = 0.83) based on improved connection of erodibility coefficient and excess shear stress technique. The present study findings will be helpful to assist in the implementation of river protection works at the given locations of Indus River and will serve as a framework for similar river reaches.
PL
W pracy sprawdzono przydatność wybranych metod prognostycznych do szacowania lokalnego wskaźnika ilości generowanych odpadów komunalnych a tym samym potencjału energetycznego odpadów, które będą mogły być wykorzystane w instalacjach termicznego przetwarzania odpadów. Prognozy stawiano w oparciu o metody: sztucznych sieci neuronowych (ANN), drzewa regresyjne (CART), wielozmienną regresję adaptacyjną z użyciem funkcji sklejanych (MARS), losowy las dla regresji (RFR), teorii zbiorów przybliżonych (RST), wzmacniane drzewa regresyjne (SRT) a także metody kombinowane będące połączeniem kilku metod prognostycznych.
EN
In this paper, the usefulness of selected forecasting methods was tested to estimate the local rate of municipal waste generation, and thus the energy potential of waste, which can be utilised in thermal waste treatment plants. Forecasts were made on the basis of the following methods: artificial neural networks (ANN), regression trees (CART), multivariate adaptive regression with glued functions (MARS), random forest for regression (RFR), rough set theory (RST), boosted regression trees (SRT), and combined methods which are a combination of several forecasting methods.
EN
Ductile iron is a material that is very sensitive to the conditions of crystallization. Due to this fact, the data on the cast iron properties obtained in tests are significantly different and thus sets containing data from samples are contradictory, i.e. they contain inconsistent observations in which, for the same set of input data, the output values are significantly different. The aim of this work is to try to determine the possibility of building rule models in conditions of significant data uncertainty. The paper attempts to determine the impact of the presence of contradictory data in a data set on the results of process modeling with the use of rule-based methods. The study used the well-known dataset (Materials Algorithms Project Data Library, n.d.) pertaining to retained austenite volume fraction in austempered ductile cast iron. Two methods of rulebased modeling were used to model the volume of the retained austenite: the decision trees algorithm (DT) and the rough sets algorithm (RST). The paper demonstrates that the number of inconsistent observations depends on the adopted data discretization criteria. The influence of contradictory data on the generation of rules in both algorithms is considered, and the problems that can be generated by contradictory data used in rule modeling are indicated.
EN
Big data, artificial intelligence and the Internet of things (IoT) are still very popular areas in current research and industrial applications. Processing massive amounts of data generated by the IoT and stored in distributed space is not a straightforward task and may cause many problems. During the last few decades, scientists have proposed many interesting approaches to extract information and discover knowledge from data collected in database systems or other sources. We observe a permanent development of machine learning algorithms that support each phase of the data mining process, ensuring achievement of better results than before. Rough set theory (RST) delivers a formal insight into information, knowledge, data reduction, uncertainty, and missing values. This formalism, formulated in the 1980s and developed by several researches, can serve as a theoretical basis and practical background for dealing with ambiguities, data reduction, building ontologies, etc. Moreover, as a mature theory, it has evolved into numerous extensions and has been transformed through various incarnations, which have enriched expressiveness and applicability of the related tools. The main aim of this article is to present an overview of selected applications of RST in big data analysis and processing. Thousands of publications on rough sets have been contributed; therefore, we focus on papers published in the last few years. The applications of RST are considered from two main perspectives: direct use of the RST concepts and tools, and jointly with other approaches, i.e., fuzzy sets, probabilistic concepts, and deep learning. The latter hybrid idea seems to be very promising for developing new methods and related tools as well as extensions of the application area.
EN
Achieving energy conservation and emission reduction in the industry is an inevitable way to promote harmony between society and nature and achieve sustainable human development. China’s infrastructure construction industry is developing rapidly. Still, there is a lack of a well-established industry standard for evaluating the potential and level of energy reduction in infrastructure construction. A severe lack of quantitative research on energy-saving and CO2 outflow decreases the benefits of green development advances. This study takes the energy conservation and outflow decrease of construction waste slurry treatment in Guangdong Province, China, as the background, establishes an evaluation system with three rule levels: social, economic, and environmental, and adopts rough set theory to determine the weights of each index to ensure the objectivity of each index. According to the recommendations of the carbon emission calculation guidelines, select the relevant data to evaluate the energy-saving and emission reduction benefits of the new green construction technology of grouted piles in a road project in Guangdong Province. The results show that the development level and potential of energy saving and emission reduction technology in the construction sector in Guangdong Province are increasing year by year. It’s potential changes with the increase or decrease of highway mileage, and it is an urgent need to increase investment in pollution control. The research results can evaluate the benefits of energy-saving and carbon dioxide emission reduction in the construction industry,also be used as a reference to assess energy-saving and emission reduction in the construction industry in other countries.
8
Content available remote Information granule system induced by a perceptual system
EN
Knowledge represented in the semantic network, especially in the Semantic Web, can be expressed in attributive language AL. Expressions of this language are interpreted in different theories of information granules: set theory, probability theory, possible data sets in the evidence systems, shadowed sets, fuzzy sets or rough sets. In order to unify the interpretations of expressions for different theories, it is assumed that expressions of the AL language can be interpreted in a chosen relational system called a granule system. In this paper, it is proposed to use information granule database and it is also demonstrated that this database can be induced by the measurement system of the adequacy of information retrieval, called a perceptual system. It can simplify previous formal description of the information granule system significantly. This paper also shows some examples of inducing rough and fuzzy granule databases by some perceptual systems.
9
Content available Slime mould games based on rough set theory
EN
We define games on the medium of plasmodia of slime mould, unicellular organisms that look like giant amoebae. The plasmodia try to occupy all the food pieces they can detect. Thus, two different plasmodia can compete with each other. In particular, we consider game-theoretically how plasmodia of Physarum polycephalum and Badhamia utricularis fight for food. Placing food pieces at different locations determines the behavior of plasmodia. In this way, we can program the plasmodia of Physarum polycephalum and Badhamia utricularis by placing food, and we can examine their motion as a Physarum machine—an abstract machine where states are represented as food pieces and transitions among states are represented as movements of plasmodia from one piece to another. Hence, this machine is treated as a natural transition system. The behavior of the Physarum machine in the form of a transition system can be interpreted in terms of rough set theory that enables modeling some ambiguities in motions of plasmodia. The problem is that there is always an ambiguity which direction of plasmodium propagation is currently chosen: one or several concurrent ones, i.e., whether we deal with a sequential, concurrent or massively parallel motion. We propose to manage this ambiguity using rough set theory. Firstly, we define the region of plasmodium interest as a rough set; secondly, we consider concurrent transitions determined by these regions as a context-based game; thirdly, we define strategies in this game as a rough set; fourthly, we show how these results can be interpreted as a Go game.
EN
In the article are described problems related to creation and maintenance of situational awareness systems. The definitions of concepts of situation and its identification are presented. An approach based on situational knowledge representation with ontological models is selected for attaining situational awareness in complex intelligent enterprise systems, where objects can be in several situations in the same time and some situations are defined imprecisely. Granular computing approach is used for reduction of situational knowledge management complexity. In order to work with situation defined imprecisely, rough set approximations are proposed for situation definition. The usage of mechanisms inherent to ontological modeling for situation representation and reasoning about them are also discussed.
EN
The method based on rough set theory (RST) was used in the study to establish the rate of mass accumulation of waste in households in rural areas, which are characterised by different economic types, in case of which traditional statistical analyses are usually hardy reliable. The following indicators available in the General Statistical Office’s statistics were used in the analysis: population density, income level, main source of income, economic type of the municipality, area of agricultural land, age of the buildings and participation of gaseous fuels in meeting heat demands. The method shown should not be considered as a competition for statistical methods, but it could complement them, especially in cases when there are few objects to analyse, the more so as it proves useful in cases where input data are general, imprecise and uncertain. As has been shown in the study, with such data and a small number of objects, the relative error of estimation was 13% on average.
PL
Celem artykułu jest wykorzystanie teorii zbiorów przybliżonych do indukcji reguł decyzyjnych warunkujących zastosowanie ekologicznej oceny cyklu życia w zidentyfikowanych modelach biznesowych MŚP. Wykorzystano w tym celu wyniki badania ankietowego przeprowadzonego w ramach projektu PARP „Wzorce zrównoważonej produkcji” oraz zdefiniowane typy modeli biznesu. W opracowaniu przedstawiono typologię modeli biznesu MŚP, dokonano klasyfikacji zmiennych na decyzyjne i warunkowe oraz wyznaczono reguły decyzyjne dla poszczególnych typów modeli, które prowadzą do zastosowania ekologicznej oceny cyklu życia.
EN
The aim of the paper is to use Rough Set approach to induce decision rules on LCA use in selected business models of SMEs. For that purpose the results of “Sustainable production patterns” PARP survey are used together with defined business model types. The typology of SME business models are presented in the paper, and is used to classify companies to different business model types. It is followed by development of condition attributes and decision attribute sets and induction of decision rules for different business model types.
EN
The article presents a way to quickly implement a method of analyzing the significance of attributes by using soft reduction of conditional attributes in the rough set theory. The analysis is a universal instrument for testing the significance of attributes and may be successfully used in many fields, including transport. It uses the rules that can be considered useful and allows reducing those attributes that do not cause a significant decrease in the number of rules generating entirely certain rules. At the same time it is a rapid mechanism of analyzing large data sets such as encoded attributes of rules. For implementation purposes we propose to use the mechanisms of modern relational databases and the capabilities presently offered by the SQL language, including its expansion with conditional CASE queries.
PL
W artykule przedstawiono sposób na szybką implementację metody analizy istotności atrybutów poprzez wykorzystanie miękkiej redukcji atrybutów warunkowy w teorii zbiorów przybliżonych. Analiza ta wykorzystuje reguły, które można uznać za użyteczne i pozwala na redukcję atrybutów, które nie powodują znacznego spadku liczby reguł generujących całkowicie pewne reguły. Jest przy tym szybkim mechanizmem analizy dużych zbiorów danych jakim są zakodowane atrybuty reguł. Do celów implementacyjnych zaproponowano wykorzystanie mechanizmów współczesnych relacyjnych baz danych oraz możliwości jakie obecnie daje język SQL, w tym rozbudowanie go o zapytania warunkowe typu CASE.
PL
Celem pracy była ocena przydatności teorii zbiorów przybliżonych w analizie zużycia endoprotez. W pracy wyodrębnić można dwie zasadnicze części: w pierwszej opisano badania tribologiczne endoprotez stawu biodrowego, natomiast w drugiej dokonano analizy wyników tych badań, wykorzystując metodę generowania reguł decyzyjnych w oparciu o teorię zbiorów przybliżonych. W efekcie stwierdzono, że wygenerowane reguły decyzyjne nie są sprzeczne z aktualnym stanem wiedzy, a zaproponowana metoda analizy może być przydatna w analizie tego rodzaju zagadnień.
EN
The aim of the study was to evaluate the usefulness of rough set theory in the analysis of endoprosthesis wear. In the article, two main parts can be distinguished: the first describes the tribological study of hip endoprosthesis, while the second analyses the results of these tests using the method of generating decision rules based on rough set theory. There were generated two sets of decision rules describing the impact of roughness, friction, wear and the angle of the prosthesis head on the chromium, and cobalt ions emission. As a result, it was found that the generated decision rules are consistent with the current state of knowledge, and the proposed method of analysis may be useful in the analysis of such issues.
EN
Models for estimating execution times of parallel program loops are discussed. The significance of parameters used for such estimation is analyzed. The significance analysis permits to determine the validity of parameters selected for estimation and to identify low significance parameters that may be eliminated.
PL
W artykule przedstawiono modele szacowania czasów wykonywania się pętli programowych w formie zrównoleglonej oraz przedstawiono analizę istotności parametrów stosowanych do tego szacowania. Analiza istotności pozwala określić trafność doboru poszczególnych parametrów oraz wskazać parametry o niskiej istotności, które można byłoby zredukować.
PL
Zaprezentowane w artykule badania skupiają się na analizie danych dotyczących preferencji zakupowych kobiet i mężczyzn. Główny nacisk położono na metodę użytą w badaniu – teorię zbiorów przybliżonych. Metodę tę zastosowano do identyfikacji reguł zachowania kobiet i mężczyzn podczas kupowania telefonów komórkowych i akcesoriów. Otrzymane wyniki pozwalają na sformułowanie wniosku, że teoria zbiorów przybliżonych może być z powodzeniem użyta w praktyce jako skuteczne narzędzie dla tego typu analizy danych. Stworzona baza reguł dotyczących preferencji zakupowych kobiet i mężczyzn może służyć firmom produkującym telefony komórkowe i akcesoria jako źródło wiedzy informujące, na co zwracają uwagę kobiety i mężczyźni przy zakupie oferowanych produktów.
EN
The research presented in the article was focused on the data analysis concerning purchase preferences of men and women. The main emphasis is put on the method which was used in the research – the rough set theory. This method was applied to identify rules of male and female behavior while buying cellular phones. The received results allow conclusion that the used method of artificial intelligence i.e. rough set method can be successfully used in practice as an effective tool for this type of data analysis. The created basis of purchase preferences rules for men and women can be used as a base of knowledge for companies producing cellular phones and accessories and can be a direction showing what this two groups of consumers pay attention to while buying products offered by these companies.
17
Content available remote Complexity as an indicator of aesthetic quality of landscape
EN
The purpose of the article is to describe the complexity index as a quantitative parameter and indicate the position in the hierarchy of factors affecting urban riverside landscape on the example of the Odra River in Wroclaw.
PL
Celem niniejszego artykułu jest opisanie wskaźnika złożoność jako parametru ilościowego oraz wskazanie miejsca w hierarchii czynników oddziałujących na wartość krajobrazu nadrzecznego miast na przykładzie Odry we Wrocławiu.
PL
Przetwarzanie znaczących ilości informacji pochodzących z obrazów radiograficznych oraz automatyczne wykrywanie wad połączeń spawalniczych z dużą dokładnością jest możliwe dzięki zastosowaniu rozwiązań opartych na teorii zbiorów przybliżonych oraz zastosowaniu jej w systemach komputerowych, które umożliwiają szybkie przetwarzanie znaczących ilości danych. Wspomniana metoda ma solidne podstawy matematyczne, których zastosowanie umożliwia określenie istotności atrybutów mających znaczenie dla identyfikacji niedoskonałości, natomiast ostateczna ocena reguł tworzy bazę wiedzy umożliwiająca komputerowe wskazywanie określonej klasy wady spawu. Opisana technika umożliwiła klasyfikację wad w bardzo wysoką dokładnością dla rzeczywistych danych pochodzących ze zdjęć rentgenowskich połączeń spawalniczych.
EN
Processing of large amount of information deriving from radiographic images and automatically detecting of welding joints imperfections with high accuracy is possible by applying solutions based on rough sets theory and usage of this theory on computer systems that are capable to make fast calculations on huge number of information. The theory posses solid and confirmed mathematical foundation that allows applying it for calculation of attribute importance that have huge significance for identification of weld imperfections, whereas final extracting rules creates knowledge base that gives possibility for computer aided pointing specific class of weld imperfection. Technique that is described in the paper was capable of classification of weld defects with very high accuracy for real data originating from radiographic images of weld joints.
EN
Flotation tailings dumps represent a potential threat to the environment. To corroborate this, numerous environmental disasters have occurred worldwide in the past. Pollution caused by breaking of tailings dump dams and overflowing of hazardous materials is still present, after several decades, and continue to threaten the environment. This paper presents a method for determining the most appropriate location for the flotation tailings dump using rough set theory. The review of the criteria that influence the choice of flotation tailings dump location is given. Based on these criteria, an analysis and evaluation of the proposed locations for the flotation tailings dump are done using rough set theory and the most suitable location that meets all the requirements is suggested.
PL
Składowiska odpadów poflotacyjnych stanowią potencjalne zagrożenie dla środowiska naturalnego. Dla potwierdzenia, wymieniać można różnorakie katastrofy dla środowiska, które miały miejsce w przeszłości. Skażenie spowodowane przerwaniem tam zabezpieczających składowiska utrzymuje się nadal, nawet po upływie kilku dekad a przelewanie się materiałów niebezpiecznych wciąż stanowi zagrożenie dla środowiska. W pracy przedstawiono metodę wyboru najodpowiedniejszej lokalizacji składowiska odpadów poflotacyjnych w oparciu o teorię zbiorów przybliżonych. Zaprezentowano przegląd kryteriów w oparciu o które dokonuje się wyboru lokalizacji składowiska. W oparciu o powyższe kryteria, przeprowadzono analizę i ocenę proponowanych lokalizacji składowisk odpadów poflotacyjnych przy zastosowaniu teorii zbiorów przybliżonych i na tej podstawie dokonano wyboru odpowiedniej lokalizacji, spełniającej wszystkie powyższe kryteria.
EN
The article discusses the possibilities of employing an algorithm based on the Rough Set Theory for generating engineering knowledge in the form of logic rules. The logic rules were generated from the data set characterizing the influence of process parameters on the ultimate tensile strength of austempered ductile iron. The paper assesses the obtained logic rules with the help of the rule quality evaluation measures, that is, with the help of the measures of confidence, support, and coverage, as well as the proposed rule quality coefficient.
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