語系:
繁體中文
English
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
New hybrid intelligent systems for d...
~
Melin, Patricia.
FindBook
Google Book
Amazon
博客來
New hybrid intelligent systems for diagnosis and risk evaluation of arterial hypertension
紀錄類型:
書目-電子資源 : Monograph/item
正題名/作者:
New hybrid intelligent systems for diagnosis and risk evaluation of arterial hypertension/ by Patricia Melin, German Prado-Arechiga.
作者:
Melin, Patricia.
其他作者:
Prado-Arechiga, German.
出版者:
Cham :Springer International Publishing : : 2018.,
面頁冊數:
viii, 88 p. :ill., digital ;24 cm.
內容註:
From the Content: Introduction -- Fuzzy Logic for Arterial Hypertension Classification -- Design of a Neuro Design of a Neuro Design of Arterial Hypertension.
Contained By:
Springer eBooks
標題:
Hypertension - Diagnosis. -
電子資源:
http://dx.doi.org/10.1007/978-3-319-61149-5
ISBN:
9783319611495
New hybrid intelligent systems for diagnosis and risk evaluation of arterial hypertension
Melin, Patricia.
New hybrid intelligent systems for diagnosis and risk evaluation of arterial hypertension
[electronic resource] /by Patricia Melin, German Prado-Arechiga. - Cham :Springer International Publishing :2018. - viii, 88 p. :ill., digital ;24 cm. - SpringerBriefs in applied sciences and technology,2191-530X. - SpringerBriefs in applied sciences and technology..
From the Content: Introduction -- Fuzzy Logic for Arterial Hypertension Classification -- Design of a Neuro Design of a Neuro Design of Arterial Hypertension.
In this book, a new approach for diagnosis and risk evaluation of ar-terial hypertension is introduced. The new approach was implement-ed as a hybrid intelligent system combining modular neural net-works and fuzzy systems. The different responses of the hybrid system are combined using fuzzy logic. Finally, two genetic algo-rithms are used to perform the optimization of the modular neural networks parameters and fuzzy inference system parameters. The experimental results obtained using the proposed method on real pa-tient data show that when the optimization is used, the results can be better than without optimization. This book is intended to be a refer-ence for scientists and physicians interested in applying soft compu-ting techniques, such as neural networks, fuzzy logic and genetic algorithms, in medical diagnosis, but also in general to classification and pattern recognition and similar problems.
ISBN: 9783319611495
Standard No.: 10.1007/978-3-319-61149-5doiSubjects--Topical Terms:
2017252
Hypertension
--Diagnosis.
LC Class. No.: RC685.H8
Dewey Class. No.: 616.132075
New hybrid intelligent systems for diagnosis and risk evaluation of arterial hypertension
LDR
:02134nmm a2200325 a 4500
001
2130687
003
DE-He213
005
20170704113649.0
006
m d
007
cr nn 008maaau
008
181005s2018 gw s 0 eng d
020
$a
9783319611495
$q
(electronic bk.)
020
$a
9783319611488
$q
(paper)
024
7
$a
10.1007/978-3-319-61149-5
$2
doi
035
$a
978-3-319-61149-5
040
$a
GP
$c
GP
041
0
$a
eng
050
4
$a
RC685.H8
072
7
$a
UYQ
$2
bicssc
072
7
$a
COM004000
$2
bisacsh
082
0 4
$a
616.132075
$2
23
090
$a
RC685.H8
$b
M522 2018
100
1
$a
Melin, Patricia.
$3
855558
245
1 0
$a
New hybrid intelligent systems for diagnosis and risk evaluation of arterial hypertension
$h
[electronic resource] /
$c
by Patricia Melin, German Prado-Arechiga.
260
$a
Cham :
$b
Springer International Publishing :
$b
Imprint: Springer,
$c
2018.
300
$a
viii, 88 p. :
$b
ill., digital ;
$c
24 cm.
490
1
$a
SpringerBriefs in applied sciences and technology,
$x
2191-530X
505
0
$a
From the Content: Introduction -- Fuzzy Logic for Arterial Hypertension Classification -- Design of a Neuro Design of a Neuro Design of Arterial Hypertension.
520
$a
In this book, a new approach for diagnosis and risk evaluation of ar-terial hypertension is introduced. The new approach was implement-ed as a hybrid intelligent system combining modular neural net-works and fuzzy systems. The different responses of the hybrid system are combined using fuzzy logic. Finally, two genetic algo-rithms are used to perform the optimization of the modular neural networks parameters and fuzzy inference system parameters. The experimental results obtained using the proposed method on real pa-tient data show that when the optimization is used, the results can be better than without optimization. This book is intended to be a refer-ence for scientists and physicians interested in applying soft compu-ting techniques, such as neural networks, fuzzy logic and genetic algorithms, in medical diagnosis, but also in general to classification and pattern recognition and similar problems.
650
0
$a
Hypertension
$x
Diagnosis.
$3
2017252
650
0
$a
Hypertension
$x
Risk assessment.
$3
3295513
650
0
$a
Neural networks (Computer science)
$3
532070
650
0
$a
Soft computing.
$3
563033
650
0
$a
Fuzzy logic.
$3
532071
650
1 4
$a
Engineering.
$3
586835
650
2 4
$a
Computational Intelligence.
$3
1001631
650
2 4
$a
Biomedical Engineering.
$3
720279
650
2 4
$a
Health Informatics.
$3
892928
700
1
$a
Prado-Arechiga, German.
$3
3295512
710
2
$a
SpringerLink (Online service)
$3
836513
773
0
$t
Springer eBooks
830
0
$a
SpringerBriefs in applied sciences and technology.
$3
1565541
856
4 0
$u
http://dx.doi.org/10.1007/978-3-319-61149-5
950
$a
Engineering (Springer-11647)
筆 0 讀者評論
館藏地:
全部
電子資源
出版年:
卷號:
館藏
1 筆 • 頁數 1 •
1
條碼號
典藏地名稱
館藏流通類別
資料類型
索書號
使用類型
借閱狀態
預約狀態
備註欄
附件
W9339422
電子資源
11.線上閱覽_V
電子書
EB RC685.H8
一般使用(Normal)
在架
0
1 筆 • 頁數 1 •
1
多媒體
評論
新增評論
分享你的心得
Export
取書館
處理中
...
變更密碼
登入