Wyniki wyszukiwania - BazTech

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Methodologies of knowledge discovery from data and data mining methods in mechanical engineering

Rogalewicz M., Sika R.

Management and Production Engineering Review

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2016

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Vol. 7, No. 4

97--108

EN

The paper contains a review of methodologies of a process of knowledge discovery from data and methods of data exploration (Data Mining), which are the most frequently used in mechanical engineering. The methodologies contain various scenarios of data exploring, while DM methods are used in their scope. The paper shows premises for use of DM methods in industry, as well as their advantages and disadvantages. Development of methodologies of knowledge discovery from data is also presented, along with a classification of the most widespread Data Mining methods, divided by type of realized tasks. The paper is summarized by presentation of selected Data Mining applications in mechanical engineering.

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Selection of data mining method for multidimensional evaluation of the manufacturing process state

Rogalewicz M., Piłacińska M., Kujawińska A.

Management and Production Engineering Review

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2012

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Vol. 3, No. 2

27-35

EN

The article deals with the issues involved in evaluating the process state on the basis of many measures, including: process parameters, diagnostic signals and events occurring during the process. These measures as well as those measurements traditionally used in the evaluation of process capability, offer a relevant source of information about the manufacturing process and the authors attempted to ascertain the most suitable method, or group of methods, for achieving this. They present the main criteria for the categorization division of the methods of the manufacturing process state evaluation and, from those identified, distinguish the traditional from Data Mining methods. The authors then specify some basic requirements regarding the desired method or group of methods and focus on the classification problem. A division and classification of the methods is made and briefly described. Finally, the authors specify the criteria for their selection of the Data Mining method type as being the most appropriate for the evaluation of the manufacturing process state and, from within this type, offer the most suitable groups of methods. Some directions for further research are discussed at the end of the article.

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Przegląd i klasyfikacja zastosowań, metod oraz technik eksploracji danych

Mirończuk Marcin

Studia i Materiały Informatyki Stosowanej

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2010

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nr 2

35--46

PL

Wzrost ilości danych jak i informacji w aktualnych systemach informacyjnych wymusił powstanie nowych procesów oraz technik i metod do ich składowania, przetwarzania oraz analizowania. Do analizy dużych zbiorów danych aktualnie wykorzystuje się osiągnięcia z obszaru analizy statystycznej oraz sztucznej inteligencji (ang. artificial intelligence). Dziedziny te wykorzystane w ramach procesu analizy dużych ilości danych stanowią rdzeń eksploracji danych. Aktualnie eksploracja danych pretenduje do stania się samodzielną metodą naukową wykorzystywaną do rozwiązywania problemów analizy informacji pochodzących m.in. z systemów ich zarządzania. W niniejszym artykule dokonano przeglądu i klasyfikacji zastosowań oraz metod i technik wykorzystywanych podczas procesu eksploracji danych. Dokonano w nim także omówienia aktualnych kierunków rozwoju i elementów składających się na tą młodą stosowaną dziedzinę nauki.

EN

The large quantity of the data and information accumulated into actual information systems and their successive extension extorted the development of new processes, techniques and methods to their storing, processing and analysing. Currently the achievement from the statistical analyses and artificial intelligence area are use to the analysis process of the large data sets. These fields make up the core of data exploration - data mining. Currently the data mining aspires to independent scientific method which one uses to solving problems from range of information analysis comes from the data bases menagments systems. In this article was described review and use's classification, methods and techniques which they are using in the process of the data exploration. In this article also was described actual development direction and described elements which require this young applied discipline of the science.