Rough sets and dependency analysis among attributes in computer implementations of expert's inference models

Ai and Intelligent Industrial Applications: The Rough Set Perspective

“…Also rough sets can be used here in many cases. Cement kiln control algorithms obtained from observation of stoker actions and blast furnace control in iron and steel works are exemplary applications of rough set techniques in intelligent industrial control (Mrózek, 1989(Mrózek, , 1992 3) Decision support systems. Rough set based decision support systems can be widely used in many kinds of industrial decision making on various levels, stretching down from specific industrial process up to management and business decisions (Golan & Ziarko, 1995, Pawlak, 1994, Słowiński, 1992, Stepaniuk, 1996 (Arciszewski & Ziarko, 1987, signal and image processing (Kowalczyk, 1996), data bases and information retrieval (Beaubouef et al, 1995, Funakoshi & Tu Bao Ho, 1996 and others , Furuta et al, 1996, Rubin et al, 1996and Zak & Stefanowski, 1994.…”

“…In this section we will descuss briefly the application of the rough set approach to the rotary clinker kiln control (Mrózek, 1989). Fig.…”

“…His control decisions consist in setting values of the two following control parameters (decision attributes): 3 3 2 2 3 3 2 2 3 1 2 2 3 2 2 2 3 2 3 2 3 2 3 2 3 2 3 3 3 2 3 3 3 2 3 3 4 1 3 3 4 3 3 3 3 3 2 3 3 3 2 2 3 3 2 2 2 3 2 2 2 3 2 1 2 3 1 1 2 1 1 1 2 2 1 1 2 2 2 1 3 2 3 2 3 1 3 2 3 1 3 2 3 1 3 2 3 1 3 2 3 1 3 2 3 1 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 4 2 4 2 4 2 4 2 3 2 3 2 3 2 3 2 3 2 2 2 2 2 3 2 4 2 4 For details see Mrózek (1989). The quality of control by the stoker and the rough control algorithm is revealed in Table 6.…”

A Rough Set Approach for the Discovery of Classification Rules in Interval-Valued Information Systems

“…The theory of rough sets, proposed by Pawlak [28], has recently been used to analyze data sets for such a purpose. This theory is an extension of classical set theory for the study of systems characterized by insufficient and incomplete information, and has been demonstrated to be useful in fields such as pattern recognition, machine learning, and automated knowledge acquisition [14,27,[30][31][32]46,48]. Rough-set data analysis uses only internal knowledge, avoids external parameters, and does not rely on prior model assumptions such as probabilistic distribution in statistical methods, membership function in fuzzy sets theory, and basic probability assignment in Dempster-Shafer theory of evidence [7,33].…”

Reduction of the decision table: A rough approach

“…In this article, we will consider a special and important class of knowledge representation system (KR system), called a decision table, which plays an important role in many applications. A decision table [1][2][3][4][5] is a kind of prescription that specifies what decisions should be undertaken when some conditions are satisfied. Most decision problems can be formulated employing decision table formalism; therefore, this tool is particularly useful in decision making.…”