Titlebook: Rough Sets in Knowledge Discovery 2; Applications, Case S Lech Polkowski,Andrzej Skowron Book 1998 Physica-Verlag Heidelberg 1998 artificia

只看該作者 · 發(fā)表于 2025-3-25 20:49:37

Data Mining: A Probabilistic Rough Set Approachs can be flexibly selected, background knowledge can be used to constrain rule generation, and . rules with strengths can be effectively acquired from large, complex databases in an incremental, bottom-up mode. In this paper, we focus on basic concepts and an implementation of our methodology.

只看該作者 · 發(fā)表于 2025-3-26 02:36:35

只看該作者 · 發(fā)表于 2025-3-26 08:13:14

Rough Sets in Industrial Applicationsg human operators of plants and processes and discovering rules governing their actions. The behavior of operators can often be specified by ., defined as sets of . coupled with rule selection mechanisms. Rough set theory [10, 11] can be used to generate such tables from ., containing the decisions of human operators [8].

只看該作者 · 發(fā)表于 2025-3-26 08:55:34

只看該作者 · 發(fā)表于 2025-3-26 15:27:34

只看該作者 · 發(fā)表于 2025-3-26 17:23:08

		自動登錄	找回密碼
密碼			To register

關(guān)于派博傳思			派博傳思旗下網(wǎng)站			友情鏈接
派博傳思介紹	公司地理位置	論文服務(wù)流程	影響因子官網(wǎng)	吾愛論文網(wǎng)	大講堂	北京大學(xué)	Oxford Uni.	Harvard Uni.
發(fā)展歷史沿革	期刊點評	投稿經(jīng)驗總結(jié)	SCIENCEGARD	IMPACTFACTOR	派博系數(shù)	清華大學(xué)	Yale Uni.	Stanford Uni.
\|Archiver\|手機版\|小黑屋\| 派博傳思國際 ( 京公網(wǎng)安備110108008328) GMT+8, 2026-1-24 13:06
Copyright © 2001-2015 派博傳思京公網(wǎng)安備110108008328 版權(quán)所有 All rights reserved