Fuzzy cognitive maps for applied sciences and engineering : From fundamentals to extensions and learning algorithms /
Fuzzy Cognitive Maps (FCM) constitute cognitive models in the form of fuzzy directed graphs consisting of two basic elements: the nodes, which basically correspond to "concepts" bearing different states of activation depending on the knowledge they represent, and the "edges" deno...
Saved in:
| Corporate Author: | |
|---|---|
| Other Authors: | |
| Format: | eBook |
| Language: | English |
| Published: |
Berlin, Heidelberg
Springer Berlin Heidelberg
2014.
|
| Series: | Intelligent Systems Reference Library
54 |
| Subjects: | |
| Online Access: | Click here to view the full text content |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| LEADER | 02976nam a2200385 i 4500 | ||
|---|---|---|---|
| 001 | vtls000123192 | ||
| 003 | MY-ArUMP | ||
| 005 | 20210731153038.0 | ||
| 006 | m fo d | ||
| 007 | cr nn 008mamaa | ||
| 008 | 150126s2014 gw f 00| 0 eng d | ||
| 020 | |a 9783642397394 | ||
| 039 | 9 | |a 201511191438 |b SMI |c 201501260957 |d NY |y 201501162007 |z NY | |
| 040 | |a MYPMP |b eng |c MYPMP |e rda | ||
| 245 | 0 | 0 | |a Fuzzy cognitive maps for applied sciences and engineering : |b From fundamentals to extensions and learning algorithms / |c edited by Elpiniki I. Papageorgiou. |
| 264 | 1 | |a Berlin, Heidelberg |b Springer Berlin Heidelberg |c 2014. | |
| 300 | |a 1 online resource (XXVII, 395 pages) 147 illustration, 2 illustration in colour. | ||
| 336 | |a text |b txt |2 rdacontent | ||
| 337 | |a computer |b c |2 rdamedia | ||
| 338 | |a online resource |b cr |2 rdacarrier | ||
| 347 | |a text file |b PDF |2 rda | ||
| 490 | 1 | |a Intelligent Systems Reference Library |x 1868-4394 |v 54 | |
| 520 | |a Fuzzy Cognitive Maps (FCM) constitute cognitive models in the form of fuzzy directed graphs consisting of two basic elements: the nodes, which basically correspond to "concepts" bearing different states of activation depending on the knowledge they represent, and the "edges" denoting the causal effects that each source node exercises on the receiving concept expressed through weights. Weights take values in the interval [-1,1], which denotes the positive, negative or neutral causal relationship between two concepts. An FCM can be typically obtained through linguistic terms, inherent to fuzzy systems, but with a structure similar to the neural networks, which facilitates data processing, and has capabilities for training and adaptation. During the last 10 years, an exponential growth of published papers in FCMs was followed showing great impact potential. Different FCM structures and learning schemes have been developed, while numerous studies report their use in many contexts with highly successful modeling results. The aim of this book is to fill the existing gap in the literature concerning fundamentals, models, extensions and learning algorithms for FCMs in knowledge engineering. It comprehensively covers the state-of-the-art FCM modeling and learning methods, with algorithms, codes and software tools, and provides a set of applications that demonstrate their various usages in applied sciences and engineering. | ||
| 650 | 0 | |a Engineering. | |
| 650 | 0 | |a Artificial intelligence. | |
| 700 | 1 | |a Papageorgiou, Elpiniki I. | |
| 710 | 2 | |a SpringerLink (Online service) | |
| 773 | 0 | |t Springer eBooks | |
| 776 | 0 | 8 | |i Printed edition |z 9783642397387 |
| 830 | 0 | |a Intelligent Systems Reference Library |x 1868-4394 |v 54 | |
| 856 | 4 | 0 | |u http://dx.doi.org/10.1007/978-3-642-39739-4 |y Click here to view the full text content |
| 942 | |2 lcc |c BK-EBOOK | ||
| 949 | |a VIRTUAITEM |d 10011 |x 9 | ||
| 999 | |c 62585 |d 62585 | ||
| 952 | |0 0 |1 0 |2 lcc |4 0 |7 0 |9 55164 |a FSGM |b FSGM |d 2021-07-31 |l 0 |r 2021-07-31 |w 2021-07-31 |y BK-EBOOK | ||