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This paper considers a number of alternative rough consequence logics which come in a natural way from the logics Lr and previously studied by Chakraborty and Banerjee. The systems have been compared to variants of S5, and the logic Triv of Hughes and Cresswell. A comparison has also been made with Lr and ...
For completely specified decision tables lower and upper approximations are unique, the lower approximation is the largest definable set contained in the approximated set X and the upper approximation of X is the smallest definable set containing X. For incomplete decision tables the existing definitions of upper approximations provide sets that, in general, are not minimal definable sets. The same...
A dominance-based rough set approach (DRSA) to multiple criteria ABC analysis (MCABC) is designed and compared to other approaches using a practical case study. ABC analysis is a well-known inventory planning and control approach, which classifies inventory items, or stock-keeping units (SKUs), based solely on their annual dollar usage. Recently, it has been suggested that MCABC can provide more managerial...
In this paper we will show that partially ordered monads contain appropriate structure for modeling rough sets in a generalized relational setting. Partially ordered monads are further shown to be useful in topological and generalized convergence frameworks. The paper thus demonstrates the use of monad constructions for applications to rough sets and even further towards entirely new types of applications...
This paper constitutes an account of the authors’ experiences and a presentation of results obtained in a real-life application of rough set theory’s methods and techniques in the identification and analysis of data dependencies and relationships on an empirical data. The data was collected in the course of an experiment on the biological control of the Leafy Spurge [13] weed in the prairies of Western...
In this paper, we mainly discuss the relationship between the extended Pawlak flow graph (EFG) with granular computing (GrC), and develop a both simple and concrete model for EFG using GrC. The distinct advantage is that we can resort to merits of GrC to benefit us in analyzing and processing data using flow graph, for its structure is inherently consistent with GrC, which provides us with both structured...
In this paper, we discuss an approach to structural objects based on a generalisation of indiscernibility relation used in rough set theory. The existing results in rough set theory are based on the assumption that objects are perceived by attribute value vectors. We propose the new point of view on rough set theory. We replace information systems with the knowledge representation models that...
Mereocat (mereological category), a theory of part-whole relations based on category theory, is proposed and its basic properties are discussed. The concepts of mereological sum is redefined in categorical framework. The theory is then applied to model some properties of component software architecture.
In different theories involving indiscernibility, it is assumed that at some level the objects involved are actually assignable distinct names. This can prove difficult in different application contexts if the main semantic level is distinct from the semantic-naming level. Set-theoretically too this aspect is of much significance. In the present research paper we develop a framework for a generalized...
Domain, or background, knowledge has proven to be a key component in the development of high-performance classification systems, especially when the objects of interest exhibit complex internal structures, as in the case of images, time series data or action plans. This knowledge usually comes in extrinsic forms such as human expert advices, often contains complex concepts expressed in quasi-natural...
The present paper investigates topological variations of information structures (together with the associated operators) from the theory of Information Quanta, namely Information Quantum Relational Systems (IQRSs) and Property Systems, with special emphasis put on approximation spaces from Rough Set Theory (RST) and contexts from Formal Concept Analysis (FCA), respectively. The main novelty of this...
In the paper, the accuracy of greedy algorithms for construction of partial covers, reducts and decision rules is considered. Bounds on the minimal complexity of partial covers, reducts and decision rules based on an information about greedy algorithm work are studied. The results of experiments with greedy algorithms are described.
Recently, clustering algorithms based on rough set theory have gained increasing attention. For example, Lingras et al. introduced a rough k-means that assigns objects to lower and upper approximations of clusters. The objects in the lower approximation surely belong to a cluster while the membership of the objects in an upper approximation is uncertain. Therefore, the core cluster, defined by the...
This paper gives an overview of the current version of the “Rough Sets Database System” (in short the RSDS system). The current version of the RSDS system includes a number of modifications, extensions and functional improvements. The RSDS system is a freely available database system, developed to facilitate the creation of the rough sets bibliography for various types of publications as well as their...
An implicit assumption of many machine learning algorithms is that all attributes are of the same importance. An algorithm typically selects attributes based solely on their statistical characteristics, without considering their semantic interpretations. In order to resolve difficulties associated with this unrealistic assumption, many researchers attempted to introduce user judgements of the importance...
This article gives a capsule view of research on rough set theory and applications ongoing at universities and laboratories in China. Included in this capsule view of rough set research is a brief description of the following things: Chinese research groups on rough set with their URLs for web pages, names of principal researchers (supervisors), numbers of graduate students, and topics being investigated...
This paper proposes an approach to classify faults that commonly occur in a High Voltage Direct Current (HVDC) power system. These faults are distributed throughout the entire HVDC system. The most recently published techniques for power system fault classification are the wavelet analysis, two-dimensional time-frequency representation for feature extraction and conventional artificial neural networks...
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