An algorithm of local prediction for chaotic sequences with variable frame length
Abstract According to the issues that the predict errors of chaotic sequences rapidly accumulated in multi-step forecasting which affects the predict accuracy, we proposed a new predict algorithm based on local modeling with variable frame length and interpolation points. The core idea is that, usin...
Ausführliche Beschreibung
Autor*in: |
Li, Jinlong [verfasserIn] |
---|
Format: |
E-Artikel |
---|---|
Sprache: |
Englisch |
Erschienen: |
2012 |
---|
Anmerkung: |
© Science Press, Institute of Electronics, CAS and Springer-Verlag Berlin Heidelberg 2012 |
---|
Übergeordnetes Werk: |
Enthalten in: Journal of electronics (China) - Beijing : Science Pr., 1984, 29(2012), 3-4 vom: Juli, Seite 345-352 |
---|---|
Übergeordnetes Werk: |
volume:29 ; year:2012 ; number:3-4 ; month:07 ; pages:345-352 |
Links: |
---|
DOI / URN: |
10.1007/s11767-012-0884-x |
---|
Katalog-ID: |
SPR022307729 |
---|
LEADER | 01000caa a22002652 4500 | ||
---|---|---|---|
001 | SPR022307729 | ||
003 | DE-627 | ||
005 | 20230330073725.0 | ||
007 | cr uuu---uuuuu | ||
008 | 201006s2012 xx |||||o 00| ||eng c | ||
024 | 7 | |a 10.1007/s11767-012-0884-x |2 doi | |
035 | |a (DE-627)SPR022307729 | ||
035 | |a (SPR)s11767-012-0884-x-e | ||
040 | |a DE-627 |b ger |c DE-627 |e rakwb | ||
041 | |a eng | ||
100 | 1 | |a Li, Jinlong |e verfasserin |4 aut | |
245 | 1 | 3 | |a An algorithm of local prediction for chaotic sequences with variable frame length |
264 | 1 | |c 2012 | |
336 | |a Text |b txt |2 rdacontent | ||
337 | |a Computermedien |b c |2 rdamedia | ||
338 | |a Online-Ressource |b cr |2 rdacarrier | ||
500 | |a © Science Press, Institute of Electronics, CAS and Springer-Verlag Berlin Heidelberg 2012 | ||
520 | |a Abstract According to the issues that the predict errors of chaotic sequences rapidly accumulated in multi-step forecasting which affects the predict accuracy, we proposed a new predict algorithm based on local modeling with variable frame length and interpolation points. The core idea is that, using interpolation method to increase the available sample data, then modeling the chaos dynamics system with least square algorithm which based on the Bernstein polynomial to realize the forecasting. We use the local modeling method, looking for the optimum frame length and interpolation points in every frame to improve the predict peformance. The experimental results show that the proposed algorithm can improve the predictive ability effectively, decreasing the accumulation of iterative errors in multi-step prediction. | ||
700 | 1 | |a Lin, Jiayu |4 aut | |
773 | 0 | 8 | |i Enthalten in |t Journal of electronics (China) |d Beijing : Science Pr., 1984 |g 29(2012), 3-4 vom: Juli, Seite 345-352 |w (DE-627)537443169 |w (DE-600)2376287-1 |x 1993-0615 |7 nnns |
773 | 1 | 8 | |g volume:29 |g year:2012 |g number:3-4 |g month:07 |g pages:345-352 |
856 | 4 | 0 | |u https://dx.doi.org/10.1007/s11767-012-0884-x |z lizenzpflichtig |3 Volltext |
912 | |a GBV_USEFLAG_A | ||
912 | |a SYSFLAG_A | ||
912 | |a GBV_SPRINGER | ||
912 | |a GBV_ILN_20 | ||
912 | |a GBV_ILN_31 | ||
912 | |a GBV_ILN_40 | ||
912 | |a GBV_ILN_60 | ||
912 | |a GBV_ILN_63 | ||
912 | |a GBV_ILN_65 | ||
912 | |a GBV_ILN_70 | ||
912 | |a GBV_ILN_73 | ||
912 | |a GBV_ILN_74 | ||
912 | |a GBV_ILN_90 | ||
912 | |a GBV_ILN_95 | ||
912 | |a GBV_ILN_110 | ||
912 | |a GBV_ILN_120 | ||
912 | |a GBV_ILN_150 | ||
912 | |a GBV_ILN_161 | ||
912 | |a GBV_ILN_213 | ||
912 | |a GBV_ILN_230 | ||
912 | |a GBV_ILN_285 | ||
912 | |a GBV_ILN_293 | ||
912 | |a GBV_ILN_370 | ||
912 | |a GBV_ILN_702 | ||
912 | |a GBV_ILN_2190 | ||
912 | |a GBV_ILN_4313 | ||
912 | |a GBV_ILN_4328 | ||
951 | |a AR | ||
952 | |d 29 |j 2012 |e 3-4 |c 07 |h 345-352 |
author_variant |
j l jl j l jl |
---|---|
matchkey_str |
article:19930615:2012----::nloiholclrdcinocatceunewt |
hierarchy_sort_str |
2012 |
publishDate |
2012 |
allfields |
10.1007/s11767-012-0884-x doi (DE-627)SPR022307729 (SPR)s11767-012-0884-x-e DE-627 ger DE-627 rakwb eng Li, Jinlong verfasserin aut An algorithm of local prediction for chaotic sequences with variable frame length 2012 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Science Press, Institute of Electronics, CAS and Springer-Verlag Berlin Heidelberg 2012 Abstract According to the issues that the predict errors of chaotic sequences rapidly accumulated in multi-step forecasting which affects the predict accuracy, we proposed a new predict algorithm based on local modeling with variable frame length and interpolation points. The core idea is that, using interpolation method to increase the available sample data, then modeling the chaos dynamics system with least square algorithm which based on the Bernstein polynomial to realize the forecasting. We use the local modeling method, looking for the optimum frame length and interpolation points in every frame to improve the predict peformance. The experimental results show that the proposed algorithm can improve the predictive ability effectively, decreasing the accumulation of iterative errors in multi-step prediction. Lin, Jiayu aut Enthalten in Journal of electronics (China) Beijing : Science Pr., 1984 29(2012), 3-4 vom: Juli, Seite 345-352 (DE-627)537443169 (DE-600)2376287-1 1993-0615 nnns volume:29 year:2012 number:3-4 month:07 pages:345-352 https://dx.doi.org/10.1007/s11767-012-0884-x lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_20 GBV_ILN_31 GBV_ILN_40 GBV_ILN_60 GBV_ILN_63 GBV_ILN_65 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_110 GBV_ILN_120 GBV_ILN_150 GBV_ILN_161 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_702 GBV_ILN_2190 GBV_ILN_4313 GBV_ILN_4328 AR 29 2012 3-4 07 345-352 |
spelling |
10.1007/s11767-012-0884-x doi (DE-627)SPR022307729 (SPR)s11767-012-0884-x-e DE-627 ger DE-627 rakwb eng Li, Jinlong verfasserin aut An algorithm of local prediction for chaotic sequences with variable frame length 2012 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Science Press, Institute of Electronics, CAS and Springer-Verlag Berlin Heidelberg 2012 Abstract According to the issues that the predict errors of chaotic sequences rapidly accumulated in multi-step forecasting which affects the predict accuracy, we proposed a new predict algorithm based on local modeling with variable frame length and interpolation points. The core idea is that, using interpolation method to increase the available sample data, then modeling the chaos dynamics system with least square algorithm which based on the Bernstein polynomial to realize the forecasting. We use the local modeling method, looking for the optimum frame length and interpolation points in every frame to improve the predict peformance. The experimental results show that the proposed algorithm can improve the predictive ability effectively, decreasing the accumulation of iterative errors in multi-step prediction. Lin, Jiayu aut Enthalten in Journal of electronics (China) Beijing : Science Pr., 1984 29(2012), 3-4 vom: Juli, Seite 345-352 (DE-627)537443169 (DE-600)2376287-1 1993-0615 nnns volume:29 year:2012 number:3-4 month:07 pages:345-352 https://dx.doi.org/10.1007/s11767-012-0884-x lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_20 GBV_ILN_31 GBV_ILN_40 GBV_ILN_60 GBV_ILN_63 GBV_ILN_65 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_110 GBV_ILN_120 GBV_ILN_150 GBV_ILN_161 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_702 GBV_ILN_2190 GBV_ILN_4313 GBV_ILN_4328 AR 29 2012 3-4 07 345-352 |
allfields_unstemmed |
10.1007/s11767-012-0884-x doi (DE-627)SPR022307729 (SPR)s11767-012-0884-x-e DE-627 ger DE-627 rakwb eng Li, Jinlong verfasserin aut An algorithm of local prediction for chaotic sequences with variable frame length 2012 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Science Press, Institute of Electronics, CAS and Springer-Verlag Berlin Heidelberg 2012 Abstract According to the issues that the predict errors of chaotic sequences rapidly accumulated in multi-step forecasting which affects the predict accuracy, we proposed a new predict algorithm based on local modeling with variable frame length and interpolation points. The core idea is that, using interpolation method to increase the available sample data, then modeling the chaos dynamics system with least square algorithm which based on the Bernstein polynomial to realize the forecasting. We use the local modeling method, looking for the optimum frame length and interpolation points in every frame to improve the predict peformance. The experimental results show that the proposed algorithm can improve the predictive ability effectively, decreasing the accumulation of iterative errors in multi-step prediction. Lin, Jiayu aut Enthalten in Journal of electronics (China) Beijing : Science Pr., 1984 29(2012), 3-4 vom: Juli, Seite 345-352 (DE-627)537443169 (DE-600)2376287-1 1993-0615 nnns volume:29 year:2012 number:3-4 month:07 pages:345-352 https://dx.doi.org/10.1007/s11767-012-0884-x lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_20 GBV_ILN_31 GBV_ILN_40 GBV_ILN_60 GBV_ILN_63 GBV_ILN_65 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_110 GBV_ILN_120 GBV_ILN_150 GBV_ILN_161 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_702 GBV_ILN_2190 GBV_ILN_4313 GBV_ILN_4328 AR 29 2012 3-4 07 345-352 |
allfieldsGer |
10.1007/s11767-012-0884-x doi (DE-627)SPR022307729 (SPR)s11767-012-0884-x-e DE-627 ger DE-627 rakwb eng Li, Jinlong verfasserin aut An algorithm of local prediction for chaotic sequences with variable frame length 2012 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Science Press, Institute of Electronics, CAS and Springer-Verlag Berlin Heidelberg 2012 Abstract According to the issues that the predict errors of chaotic sequences rapidly accumulated in multi-step forecasting which affects the predict accuracy, we proposed a new predict algorithm based on local modeling with variable frame length and interpolation points. The core idea is that, using interpolation method to increase the available sample data, then modeling the chaos dynamics system with least square algorithm which based on the Bernstein polynomial to realize the forecasting. We use the local modeling method, looking for the optimum frame length and interpolation points in every frame to improve the predict peformance. The experimental results show that the proposed algorithm can improve the predictive ability effectively, decreasing the accumulation of iterative errors in multi-step prediction. Lin, Jiayu aut Enthalten in Journal of electronics (China) Beijing : Science Pr., 1984 29(2012), 3-4 vom: Juli, Seite 345-352 (DE-627)537443169 (DE-600)2376287-1 1993-0615 nnns volume:29 year:2012 number:3-4 month:07 pages:345-352 https://dx.doi.org/10.1007/s11767-012-0884-x lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_20 GBV_ILN_31 GBV_ILN_40 GBV_ILN_60 GBV_ILN_63 GBV_ILN_65 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_110 GBV_ILN_120 GBV_ILN_150 GBV_ILN_161 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_702 GBV_ILN_2190 GBV_ILN_4313 GBV_ILN_4328 AR 29 2012 3-4 07 345-352 |
allfieldsSound |
10.1007/s11767-012-0884-x doi (DE-627)SPR022307729 (SPR)s11767-012-0884-x-e DE-627 ger DE-627 rakwb eng Li, Jinlong verfasserin aut An algorithm of local prediction for chaotic sequences with variable frame length 2012 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Science Press, Institute of Electronics, CAS and Springer-Verlag Berlin Heidelberg 2012 Abstract According to the issues that the predict errors of chaotic sequences rapidly accumulated in multi-step forecasting which affects the predict accuracy, we proposed a new predict algorithm based on local modeling with variable frame length and interpolation points. The core idea is that, using interpolation method to increase the available sample data, then modeling the chaos dynamics system with least square algorithm which based on the Bernstein polynomial to realize the forecasting. We use the local modeling method, looking for the optimum frame length and interpolation points in every frame to improve the predict peformance. The experimental results show that the proposed algorithm can improve the predictive ability effectively, decreasing the accumulation of iterative errors in multi-step prediction. Lin, Jiayu aut Enthalten in Journal of electronics (China) Beijing : Science Pr., 1984 29(2012), 3-4 vom: Juli, Seite 345-352 (DE-627)537443169 (DE-600)2376287-1 1993-0615 nnns volume:29 year:2012 number:3-4 month:07 pages:345-352 https://dx.doi.org/10.1007/s11767-012-0884-x lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_20 GBV_ILN_31 GBV_ILN_40 GBV_ILN_60 GBV_ILN_63 GBV_ILN_65 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_110 GBV_ILN_120 GBV_ILN_150 GBV_ILN_161 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_702 GBV_ILN_2190 GBV_ILN_4313 GBV_ILN_4328 AR 29 2012 3-4 07 345-352 |
language |
English |
source |
Enthalten in Journal of electronics (China) 29(2012), 3-4 vom: Juli, Seite 345-352 volume:29 year:2012 number:3-4 month:07 pages:345-352 |
sourceStr |
Enthalten in Journal of electronics (China) 29(2012), 3-4 vom: Juli, Seite 345-352 volume:29 year:2012 number:3-4 month:07 pages:345-352 |
format_phy_str_mv |
Article |
institution |
findex.gbv.de |
isfreeaccess_bool |
false |
container_title |
Journal of electronics (China) |
authorswithroles_txt_mv |
Li, Jinlong @@aut@@ Lin, Jiayu @@aut@@ |
publishDateDaySort_date |
2012-07-01T00:00:00Z |
hierarchy_top_id |
537443169 |
id |
SPR022307729 |
language_de |
englisch |
fullrecord |
<?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>01000caa a22002652 4500</leader><controlfield tag="001">SPR022307729</controlfield><controlfield tag="003">DE-627</controlfield><controlfield tag="005">20230330073725.0</controlfield><controlfield tag="007">cr uuu---uuuuu</controlfield><controlfield tag="008">201006s2012 xx |||||o 00| ||eng c</controlfield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.1007/s11767-012-0884-x</subfield><subfield code="2">doi</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627)SPR022307729</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(SPR)s11767-012-0884-x-e</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-627</subfield><subfield code="b">ger</subfield><subfield code="c">DE-627</subfield><subfield code="e">rakwb</subfield></datafield><datafield tag="041" ind1=" " ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Li, Jinlong</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="3"><subfield code="a">An algorithm of local prediction for chaotic sequences with variable frame length</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="c">2012</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">Text</subfield><subfield code="b">txt</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">Computermedien</subfield><subfield code="b">c</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">Online-Ressource</subfield><subfield code="b">cr</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="500" ind1=" " ind2=" "><subfield code="a">© Science Press, Institute of Electronics, CAS and Springer-Verlag Berlin Heidelberg 2012</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">Abstract According to the issues that the predict errors of chaotic sequences rapidly accumulated in multi-step forecasting which affects the predict accuracy, we proposed a new predict algorithm based on local modeling with variable frame length and interpolation points. The core idea is that, using interpolation method to increase the available sample data, then modeling the chaos dynamics system with least square algorithm which based on the Bernstein polynomial to realize the forecasting. We use the local modeling method, looking for the optimum frame length and interpolation points in every frame to improve the predict peformance. The experimental results show that the proposed algorithm can improve the predictive ability effectively, decreasing the accumulation of iterative errors in multi-step prediction.</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Lin, Jiayu</subfield><subfield code="4">aut</subfield></datafield><datafield tag="773" ind1="0" ind2="8"><subfield code="i">Enthalten in</subfield><subfield code="t">Journal of electronics (China)</subfield><subfield code="d">Beijing : Science Pr., 1984</subfield><subfield code="g">29(2012), 3-4 vom: Juli, Seite 345-352</subfield><subfield code="w">(DE-627)537443169</subfield><subfield code="w">(DE-600)2376287-1</subfield><subfield code="x">1993-0615</subfield><subfield code="7">nnns</subfield></datafield><datafield tag="773" ind1="1" ind2="8"><subfield code="g">volume:29</subfield><subfield code="g">year:2012</subfield><subfield code="g">number:3-4</subfield><subfield code="g">month:07</subfield><subfield code="g">pages:345-352</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="u">https://dx.doi.org/10.1007/s11767-012-0884-x</subfield><subfield code="z">lizenzpflichtig</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_USEFLAG_A</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SYSFLAG_A</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_SPRINGER</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_20</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_31</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_40</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_60</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_63</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_65</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_70</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_73</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_74</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_90</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_95</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_110</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_120</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_150</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_161</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_213</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_230</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_285</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_293</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_370</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_702</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2190</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4313</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4328</subfield></datafield><datafield tag="951" ind1=" " ind2=" "><subfield code="a">AR</subfield></datafield><datafield tag="952" ind1=" " ind2=" "><subfield code="d">29</subfield><subfield code="j">2012</subfield><subfield code="e">3-4</subfield><subfield code="c">07</subfield><subfield code="h">345-352</subfield></datafield></record></collection>
|
author |
Li, Jinlong |
spellingShingle |
Li, Jinlong An algorithm of local prediction for chaotic sequences with variable frame length |
authorStr |
Li, Jinlong |
ppnlink_with_tag_str_mv |
@@773@@(DE-627)537443169 |
format |
electronic Article |
delete_txt_mv |
keep |
author_role |
aut aut |
collection |
springer |
remote_str |
true |
illustrated |
Not Illustrated |
issn |
1993-0615 |
topic_title |
An algorithm of local prediction for chaotic sequences with variable frame length |
format_facet |
Elektronische Aufsätze Aufsätze Elektronische Ressource |
format_main_str_mv |
Text Zeitschrift/Artikel |
carriertype_str_mv |
cr |
hierarchy_parent_title |
Journal of electronics (China) |
hierarchy_parent_id |
537443169 |
hierarchy_top_title |
Journal of electronics (China) |
isfreeaccess_txt |
false |
familylinks_str_mv |
(DE-627)537443169 (DE-600)2376287-1 |
title |
An algorithm of local prediction for chaotic sequences with variable frame length |
ctrlnum |
(DE-627)SPR022307729 (SPR)s11767-012-0884-x-e |
title_full |
An algorithm of local prediction for chaotic sequences with variable frame length |
author_sort |
Li, Jinlong |
journal |
Journal of electronics (China) |
journalStr |
Journal of electronics (China) |
lang_code |
eng |
isOA_bool |
false |
recordtype |
marc |
publishDateSort |
2012 |
contenttype_str_mv |
txt |
container_start_page |
345 |
author_browse |
Li, Jinlong Lin, Jiayu |
container_volume |
29 |
format_se |
Elektronische Aufsätze |
author-letter |
Li, Jinlong |
doi_str_mv |
10.1007/s11767-012-0884-x |
title_sort |
algorithm of local prediction for chaotic sequences with variable frame length |
title_auth |
An algorithm of local prediction for chaotic sequences with variable frame length |
abstract |
Abstract According to the issues that the predict errors of chaotic sequences rapidly accumulated in multi-step forecasting which affects the predict accuracy, we proposed a new predict algorithm based on local modeling with variable frame length and interpolation points. The core idea is that, using interpolation method to increase the available sample data, then modeling the chaos dynamics system with least square algorithm which based on the Bernstein polynomial to realize the forecasting. We use the local modeling method, looking for the optimum frame length and interpolation points in every frame to improve the predict peformance. The experimental results show that the proposed algorithm can improve the predictive ability effectively, decreasing the accumulation of iterative errors in multi-step prediction. © Science Press, Institute of Electronics, CAS and Springer-Verlag Berlin Heidelberg 2012 |
abstractGer |
Abstract According to the issues that the predict errors of chaotic sequences rapidly accumulated in multi-step forecasting which affects the predict accuracy, we proposed a new predict algorithm based on local modeling with variable frame length and interpolation points. The core idea is that, using interpolation method to increase the available sample data, then modeling the chaos dynamics system with least square algorithm which based on the Bernstein polynomial to realize the forecasting. We use the local modeling method, looking for the optimum frame length and interpolation points in every frame to improve the predict peformance. The experimental results show that the proposed algorithm can improve the predictive ability effectively, decreasing the accumulation of iterative errors in multi-step prediction. © Science Press, Institute of Electronics, CAS and Springer-Verlag Berlin Heidelberg 2012 |
abstract_unstemmed |
Abstract According to the issues that the predict errors of chaotic sequences rapidly accumulated in multi-step forecasting which affects the predict accuracy, we proposed a new predict algorithm based on local modeling with variable frame length and interpolation points. The core idea is that, using interpolation method to increase the available sample data, then modeling the chaos dynamics system with least square algorithm which based on the Bernstein polynomial to realize the forecasting. We use the local modeling method, looking for the optimum frame length and interpolation points in every frame to improve the predict peformance. The experimental results show that the proposed algorithm can improve the predictive ability effectively, decreasing the accumulation of iterative errors in multi-step prediction. © Science Press, Institute of Electronics, CAS and Springer-Verlag Berlin Heidelberg 2012 |
collection_details |
GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_20 GBV_ILN_31 GBV_ILN_40 GBV_ILN_60 GBV_ILN_63 GBV_ILN_65 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_110 GBV_ILN_120 GBV_ILN_150 GBV_ILN_161 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_702 GBV_ILN_2190 GBV_ILN_4313 GBV_ILN_4328 |
container_issue |
3-4 |
title_short |
An algorithm of local prediction for chaotic sequences with variable frame length |
url |
https://dx.doi.org/10.1007/s11767-012-0884-x |
remote_bool |
true |
author2 |
Lin, Jiayu |
author2Str |
Lin, Jiayu |
ppnlink |
537443169 |
mediatype_str_mv |
c |
isOA_txt |
false |
hochschulschrift_bool |
false |
doi_str |
10.1007/s11767-012-0884-x |
up_date |
2024-07-04T02:37:26.558Z |
_version_ |
1803614312526249984 |
fullrecord_marcxml |
<?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>01000caa a22002652 4500</leader><controlfield tag="001">SPR022307729</controlfield><controlfield tag="003">DE-627</controlfield><controlfield tag="005">20230330073725.0</controlfield><controlfield tag="007">cr uuu---uuuuu</controlfield><controlfield tag="008">201006s2012 xx |||||o 00| ||eng c</controlfield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.1007/s11767-012-0884-x</subfield><subfield code="2">doi</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627)SPR022307729</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(SPR)s11767-012-0884-x-e</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-627</subfield><subfield code="b">ger</subfield><subfield code="c">DE-627</subfield><subfield code="e">rakwb</subfield></datafield><datafield tag="041" ind1=" " ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Li, Jinlong</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="3"><subfield code="a">An algorithm of local prediction for chaotic sequences with variable frame length</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="c">2012</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">Text</subfield><subfield code="b">txt</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">Computermedien</subfield><subfield code="b">c</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">Online-Ressource</subfield><subfield code="b">cr</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="500" ind1=" " ind2=" "><subfield code="a">© Science Press, Institute of Electronics, CAS and Springer-Verlag Berlin Heidelberg 2012</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">Abstract According to the issues that the predict errors of chaotic sequences rapidly accumulated in multi-step forecasting which affects the predict accuracy, we proposed a new predict algorithm based on local modeling with variable frame length and interpolation points. The core idea is that, using interpolation method to increase the available sample data, then modeling the chaos dynamics system with least square algorithm which based on the Bernstein polynomial to realize the forecasting. We use the local modeling method, looking for the optimum frame length and interpolation points in every frame to improve the predict peformance. The experimental results show that the proposed algorithm can improve the predictive ability effectively, decreasing the accumulation of iterative errors in multi-step prediction.</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Lin, Jiayu</subfield><subfield code="4">aut</subfield></datafield><datafield tag="773" ind1="0" ind2="8"><subfield code="i">Enthalten in</subfield><subfield code="t">Journal of electronics (China)</subfield><subfield code="d">Beijing : Science Pr., 1984</subfield><subfield code="g">29(2012), 3-4 vom: Juli, Seite 345-352</subfield><subfield code="w">(DE-627)537443169</subfield><subfield code="w">(DE-600)2376287-1</subfield><subfield code="x">1993-0615</subfield><subfield code="7">nnns</subfield></datafield><datafield tag="773" ind1="1" ind2="8"><subfield code="g">volume:29</subfield><subfield code="g">year:2012</subfield><subfield code="g">number:3-4</subfield><subfield code="g">month:07</subfield><subfield code="g">pages:345-352</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="u">https://dx.doi.org/10.1007/s11767-012-0884-x</subfield><subfield code="z">lizenzpflichtig</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_USEFLAG_A</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SYSFLAG_A</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_SPRINGER</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_20</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_31</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_40</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_60</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_63</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_65</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_70</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_73</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_74</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_90</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_95</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_110</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_120</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_150</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_161</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_213</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_230</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_285</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_293</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_370</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_702</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2190</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4313</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4328</subfield></datafield><datafield tag="951" ind1=" " ind2=" "><subfield code="a">AR</subfield></datafield><datafield tag="952" ind1=" " ind2=" "><subfield code="d">29</subfield><subfield code="j">2012</subfield><subfield code="e">3-4</subfield><subfield code="c">07</subfield><subfield code="h">345-352</subfield></datafield></record></collection>
|
score |
7.399131 |