東華大學圖書館 |

語系: 繁體中文

說明(常見問題)

回圖書館首頁

手機版館藏查詢

登入

回首頁

切換: 標籤 | MARC模式 | ISBD

A hybrid intelligent system and its ...

Meesad, Phayung.

FindBook

Google Book

Amazon

博客來

A hybrid intelligent system and its application to medical diagnosis.

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	A hybrid intelligent system and its application to medical diagnosis./
作者:	Meesad, Phayung.
面頁冊數:	205 p.
附註:	Source: Dissertation Abstracts International, Volume: 63-06, Section: B, page: 2954.
Contained By:	Dissertation Abstracts International63-06B.
標題:	Engineering, Electronics and Electrical. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3057289
ISBN:	0493726349

A hybrid intelligent system and its application to medical diagnosis.
Meesad, Phayung.

A hybrid intelligent system and its application to medical diagnosis. - 205 p.

Source: Dissertation Abstracts International, Volume: 63-06, Section: B, page: 2954.

Thesis (Ph.D.)--Oklahoma State University, 2002.

<italic>Scope and method of study.</italic> A novel hybrid intelligent system (HIS) that provides a unified integration of numerical and linguistic knowledge representations is proposed. The proposed HIS is a hierarchical integration of an incremental learning fuzzy neural network (ILFN) and a linguistic model, i.e., fuzzy expert system (FES), optimized via the genetic algorithm (GA). The ILFN is a self-organizing network with the capability of fast, one-pass, online, and incremental learning. The linguistic model is constructed based on knowledge embedded in the trained ILFN or provided by the domain expert. The knowledge captured from the low-level ILFN can be mapped to the higher-level linguistic model and vice versa. The GA is applied to optimize the linguistic model to maintain high accuracy and comprehensibility.

ISBN: 0493726349Subjects--Topical Terms:

626636
Engineering, Electronics and Electrical.

A hybrid intelligent system and its application to medical diagnosis.
LDR:02621nmm 2200289 4500 001 1810643
005 20040329092831.5
008 130610s2002 eng d
020 $a 0493726349
035 $a (UnM)AAI3057289
035 $a AAI3057289
040 $a UnM $c UnM
100 1 $a Meesad, Phayung. $3 1900247
245 1 0 $a A hybrid intelligent system and its application to medical diagnosis.
300 $a 205 p.
500 $a Source: Dissertation Abstracts International, Volume: 63-06, Section: B, page: 2954.
500 $a Adviser: Gary G. Yen.
502 $a Thesis (Ph.D.)--Oklahoma State University, 2002.
520 $a <italic>Scope and method of study.</italic> A novel hybrid intelligent system (HIS) that provides a unified integration of numerical and linguistic knowledge representations is proposed. The proposed HIS is a hierarchical integration of an incremental learning fuzzy neural network (ILFN) and a linguistic model, i.e., fuzzy expert system (FES), optimized via the genetic algorithm (GA). The ILFN is a self-organizing network with the capability of fast, one-pass, online, and incremental learning. The linguistic model is constructed based on knowledge embedded in the trained ILFN or provided by the domain expert. The knowledge captured from the low-level ILFN can be mapped to the higher-level linguistic model and vice versa. The GA is applied to optimize the linguistic model to maintain high accuracy and comprehensibility.
520 $a <italic>Findings and conclusions.</italic> The resulting HIS is capable of dealing with low-level numerical computation and higher-level linguistic computation. After the system is successfully constructed, it can incrementally learn new information in both numerical and linguistic forms. To evaluate the system's performance, several data sets namely the Iris data set, the Wisconsin breast cancer data set, and the three medical data sets (Breast Cancer Data, Lymphograph Domain, and Primary Tumor Domain) from the Institute of Oncology, University Medical Center, Ljubliana, Yugoslavia, were used. The simulation results have shown that the proposed HIS achieved classification accuracy better than the individual standalone systems. The comparison results based on performance classification show that the linguistic rules extracted are competitive with some well-known approaches in literature.
590 $a School code: 0664.
650 4 $a Engineering, Electronics and Electrical. $3 626636
650 4 $a Engineering, Biomedical. $3 1017684
690 $a 0544
690 $a 0541
710 2 0 $a Oklahoma State University. $3 626630
773 0 $t Dissertation Abstracts International $g 63-06B.
790 1 0 $a Yen, Gary G., $e advisor
790 $a 0664
791 $a Ph.D.
792 $a 2002
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3057289