粗集
数据挖掘
计算机科学
数据集
集合(抽象数据类型)
人工智能
程序设计语言
作者
Danial Rezaei,Mohsen Maleki,Hamid Hasani,Seyed Mohammad Jafar Jalali
出处
期刊:Asian journal of management science and applications
[Inderscience Enterprises Ltd.]
日期:2018-01-01
卷期号:3 (2): 156-156
被引量:12
标识
DOI:10.1504/ajmsa.2018.10011961
摘要
Today's organisations perform their activities in difficult situations with uncertainty, rapid changes of technology, global markets and etc. There are a lot of factors which affect their performances. In this study we mostly concentrate on qualitative factors to consider organisational performance. So, we use a data mining framework based on rough set theory (RST) for classification and description usage of the organisational performance in some Iranian petrochemical companies. The proposed framework consists of three stages: 1) problem definition and data collection; 2) RST analysis (rules generation and evaluation); 3) usage of derived rules. For this purpose, 28 Iranian petrochemical companies are considered. Ten most important factors which affect organisational performance are examined. Total number of indices is 28, so it makes this work, an exhaustive research study. There are two different usages of this study. One of them is classification (predictive) usage and the other is descriptive usage.
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