Kernel broad learning cauchy conjugate gradient algorithm for online chaotic time series prediction
Accurate prediction of nonlinear systems in non-Gaussian noise environments has long been a significant challenge in the fields of statistical data analysis and time series modeling. To address this issue, this paper proposes an improved Cauchy Conjugate Gradient algorithm based on a kernel broad le...
Gespeichert in:
| Veröffentlicht in: | Neurocomputing (Amsterdam) Jg. 639; S. 130234 |
|---|---|
| Hauptverfasser: | , |
| Format: | Journal Article |
| Sprache: | Englisch |
| Veröffentlicht: |
Elsevier B.V
28.07.2025
|
| Schlagworte: | |
| ISSN: | 0925-2312 |
| Online-Zugang: | Volltext |
| Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
| Abstract | Accurate prediction of nonlinear systems in non-Gaussian noise environments has long been a significant challenge in the fields of statistical data analysis and time series modeling. To address this issue, this paper proposes an improved Cauchy Conjugate Gradient algorithm based on a kernel broad learning feature extraction strategy (Kernel Broad Learning Cauchy Conjugate Gradient, KBLCCG). This algorithm integrates kernel mapping with broad learning systems, forming a dual feature extraction mechanism that effectively captures the complex nonlinear structures of chaotic time series while preserving their inherent dynamic chaotic characteristics. The KBLCCG algorithm utilizes its robust feature extraction capabilities through the dual extraction mechanism of kernel mapping and broad learning systems, effectively capturing the intricate nonlinear structures present in time series data. The kernel broad learning strategy mitigates the phenomenon of kernel matrix size expansion during the iterative process, thereby reducing the computational burden and enhancing the algorithm's robustness. The Cauchy Conjugate Gradient method is employed to optimize the reduced-dimensional feature data, efficiently addressing the nonlinear prediction problem of the target sequence. Empirical analysis using simulation data and actual financial data (including the Lorenz system, Shanghai Composite Index, and CSI 300 Index) validates the performance of this method. Experimental results indicate that KBLCCG significantly outperforms existing adaptive filtering algorithms in terms of prediction accuracy, particularly demonstrating stronger generalization capabilities when dealing with complex chaotic systems. Compared to traditional methods, the kernel broad learning strategy markedly enhances the feature capturing and modeling effectiveness of chaotic time series, further validating the method's efficacy and robustness in nonlinear time series prediction. The KBLCCG algorithm not only exhibits superior predictive capabilities in complex non-Gaussian noise environments but also provides an innovative solution for handling the nonlinear and chaotic characteristics of time series prediction. |
|---|---|
| AbstractList | Accurate prediction of nonlinear systems in non-Gaussian noise environments has long been a significant challenge in the fields of statistical data analysis and time series modeling. To address this issue, this paper proposes an improved Cauchy Conjugate Gradient algorithm based on a kernel broad learning feature extraction strategy (Kernel Broad Learning Cauchy Conjugate Gradient, KBLCCG). This algorithm integrates kernel mapping with broad learning systems, forming a dual feature extraction mechanism that effectively captures the complex nonlinear structures of chaotic time series while preserving their inherent dynamic chaotic characteristics. The KBLCCG algorithm utilizes its robust feature extraction capabilities through the dual extraction mechanism of kernel mapping and broad learning systems, effectively capturing the intricate nonlinear structures present in time series data. The kernel broad learning strategy mitigates the phenomenon of kernel matrix size expansion during the iterative process, thereby reducing the computational burden and enhancing the algorithm's robustness. The Cauchy Conjugate Gradient method is employed to optimize the reduced-dimensional feature data, efficiently addressing the nonlinear prediction problem of the target sequence. Empirical analysis using simulation data and actual financial data (including the Lorenz system, Shanghai Composite Index, and CSI 300 Index) validates the performance of this method. Experimental results indicate that KBLCCG significantly outperforms existing adaptive filtering algorithms in terms of prediction accuracy, particularly demonstrating stronger generalization capabilities when dealing with complex chaotic systems. Compared to traditional methods, the kernel broad learning strategy markedly enhances the feature capturing and modeling effectiveness of chaotic time series, further validating the method's efficacy and robustness in nonlinear time series prediction. The KBLCCG algorithm not only exhibits superior predictive capabilities in complex non-Gaussian noise environments but also provides an innovative solution for handling the nonlinear and chaotic characteristics of time series prediction. |
| ArticleNumber | 130234 |
| Author | Su, Liyun Wang, Xiaoyi |
| Author_xml | – sequence: 1 givenname: Liyun surname: Su fullname: Su, Liyun email: cloudhopping@163.com, suliyun@cqut.edu.cn – sequence: 2 givenname: Xiaoyi surname: Wang fullname: Wang, Xiaoyi email: wxy@stu.cqut.edu.cn |
| BookMark | eNqFkLtOwzAYhT0UibbwBgx-gQRfmqRhQEIVN1GJBWbL-fM7dZTale0i9e1JFSYGmM70HZ3zLcjMeYeE3HCWc8bL2z53eAS_zwUTRc4lE3I1I3NWiyITkotLsoixZ4xXXNRzAm8YHA60CV63dEAdnHUdBX2E3YmCd_2x0wlpF3Rr0SWqh84Hm3Z7anyg3g3WIYWd9skCTXaPNGKwGOkhYGshWe-uyIXRQ8Trn1ySz6fHj81Ltn1_ft08bDOQbJ0yjRKNaECbRq5B1FVZGN2uRMWZrBBNJWtTYimaxoiaNUXbouS1KKUxBWBVySVZTb0QfIwBjToEu9fhpDhTZzmqV5McdZajJjkjdvcLA5v0eXgK2g7_wfcTjOOxL4tBRRg9wfg9ICTVevt3wTdq34nh |
| CitedBy_id | crossref_primary_10_1016_j_eswa_2025_128844 |
| Cites_doi | 10.1088/1009-1963/9/6/002 10.1049/iet-spr.2011.0324 10.1109/TSP.2021.3065173 10.3390/en12010161 10.1145/355984.355989 10.1109/TSP.2015.2437835 10.1007/s00034-016-0379-3 10.1109/TSP.2010.2096420 10.1109/TCSVT.2020.2989659 10.1109/ISCAS.1989.100705 10.1109/TSP.2017.2768024 10.1090/S0002-9947-1950-0051437-7 10.1016/j.mcm.2009.11.016 10.1109/LSP.2020.3048841 10.1109/LSP.2021.3081381 10.1080/03610920903537277 10.1109/TSP.2017.2698364 10.1109/TNNLS.2020.3004253 10.1016/j.physa.2017.02.072 10.1109/TPAMI.2017.2777841 10.1109/TSP.2007.896065 10.1016/j.asoc.2024.111516 10.3390/sym11101323 10.1109/TASSP.1987.1165167 10.1016/j.chaos.2022.112519 10.1016/j.asoc.2010.10.015 10.1016/j.asoc.2022.109831 10.1109/TNNLS.2011.2178446 10.1109/TSP.2018.2853109 10.1175/1520-0469(1963)020<0130:DNF>2.0.CO;2 10.1109/LSP.2019.2907480 |
| ContentType | Journal Article |
| Copyright | 2025 Elsevier B.V. |
| Copyright_xml | – notice: 2025 Elsevier B.V. |
| DBID | AAYXX CITATION |
| DOI | 10.1016/j.neucom.2025.130234 |
| DatabaseName | CrossRef |
| DatabaseTitle | CrossRef |
| DatabaseTitleList | |
| DeliveryMethod | fulltext_linktorsrc |
| Discipline | Computer Science |
| ExternalDocumentID | 10_1016_j_neucom_2025_130234 S0925231225009063 |
| GroupedDBID | --- --K --M .DC .~1 0R~ 123 1B1 1~. 1~5 4.4 457 4G. 53G 5VS 7-5 71M 8P~ 9JM 9JN AABNK AAEDT AAEDW AAIKJ AAKOC AALRI AAOAW AAQFI AATTM AAXKI AAXLA AAXUO AAYFN AAYWO ABBOA ABCQJ ABFNM ABJNI ABMAC ACDAQ ACGFS ACRLP ACVFH ACZNC ADBBV ADCNI ADEZE AEBSH AEIPS AEKER AENEX AEUPX AFJKZ AFPUW AFTJW AFXIZ AGCQF AGHFR AGUBO AGWIK AGYEJ AHHHB AHZHX AIALX AIEXJ AIGII AIIUN AIKHN AITUG AKBMS AKRWK AKYEP ALMA_UNASSIGNED_HOLDINGS AMRAJ ANKPU AOUOD APXCP AXJTR BKOJK BLXMC CS3 DU5 EBS EFJIC EFKBS EO8 EO9 EP2 EP3 F5P FDB FIRID FNPLU FYGXN G-Q GBLVA GBOLZ IHE J1W KOM LG9 M41 MO0 MOBAO N9A O-L O9- OAUVE OZT P-8 P-9 P2P PC. Q38 ROL RPZ SDF SDG SDP SES SEW SPC SPCBC SSN SSV SSZ T5K ZMT ~G- 29N 9DU AAQXK AAYXX ABWVN ABXDB ACLOT ACNNM ACRPL ADJOM ADMUD ADNMO AGQPQ ASPBG AVWKF AZFZN CITATION EFLBG EJD FEDTE FGOYB HLZ HVGLF HZ~ R2- SBC WUQ XPP ~HD |
| ID | FETCH-LOGICAL-c308t-ae3ef2bcafb38c29765fad4271037eef739f6e62bbf290b5dde319263ff5ce773 |
| ISICitedReferencesCount | 2 |
| ISICitedReferencesURI | http://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=Summon&SrcAuth=ProQuest&DestLinkType=CitingArticles&DestApp=WOS_CPL&KeyUT=001480846100001&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D |
| ISSN | 0925-2312 |
| IngestDate | Sat Nov 29 06:52:57 EST 2025 Tue Nov 18 22:33:07 EST 2025 Sat Aug 23 17:11:34 EDT 2025 |
| IsPeerReviewed | true |
| IsScholarly | true |
| Keywords | Cauchy cost function Kernel broad learning Conjugate gradient algorithm |
| Language | English |
| LinkModel | OpenURL |
| MergedId | FETCHMERGED-LOGICAL-c308t-ae3ef2bcafb38c29765fad4271037eef739f6e62bbf290b5dde319263ff5ce773 |
| ParticipantIDs | crossref_primary_10_1016_j_neucom_2025_130234 crossref_citationtrail_10_1016_j_neucom_2025_130234 elsevier_sciencedirect_doi_10_1016_j_neucom_2025_130234 |
| PublicationCentury | 2000 |
| PublicationDate | 2025-07-28 |
| PublicationDateYYYYMMDD | 2025-07-28 |
| PublicationDate_xml | – month: 07 year: 2025 text: 2025-07-28 day: 28 |
| PublicationDecade | 2020 |
| PublicationTitle | Neurocomputing (Amsterdam) |
| PublicationYear | 2025 |
| Publisher | Elsevier B.V |
| Publisher_xml | – name: Elsevier B.V |
| References | Zhang, Yang, Wang (bib31) 2021; 69 Han, Li, Feng (bib35) 2020; 32 Zhao, Han, Xu (bib4) 2022; 10 Lorenz (bib42) 1963; 20 Takens (bib32) 2006 Su, Ling (bib3) 2020; 2020 Xiong, Su, Wang (bib5) 2024; 157 Sayed (bib16) 2003 Mathews, Cho (bib20) 1987; 35 Zhang, Song, Li (bib2) 2019; 12 Le-Tian, Shi-Yuan, Ming-Lin, Gang-Yi (bib43) 2022; 71 Paige, Saunders (bib41) 1982; 8 Príncipe (bib24) 2010 Eweda (bib17) 2017; 65 Huang, Wang, Xiong (bib40) 2019; 11 Takizawa, Yukawa (bib12) 2015; 63 Khashei, Bijari (bib9) 2011; 11 Liu, Pokharel, Principe (bib37) 2007; 55 Bouboulis, Theodoridis (bib14) 2010; 59 Su, Xiong, Yang (bib6) 2023; 132 Xiong, Wang (bib39) 2019; 26 Liu, Principe, Haykin (bib15) 2011 Xing, Chen, Wang, Du, Cao (bib22) 2020; 31 Chen, Liu (bib34) 2017 Hestenes, Stiefel (bib38) 1952 Zhang, Lin, Shang (bib1) 2017; 477 Chen, Zhao, Zhu, Príncipe (bib13) 2011; 23 Mathews, Cho (bib26) 1987; 35 Lu, Zhao (bib19) 2017; 36 G.K. Boray and M.D. Srinath, Conjugate gradient techniques for adaptive filtering, 1989 IEEE International Symposium on Circuits and Systems (ISCAS), Portland, OR, USA, 1989, pp. 1752-1757 vol.3. Toque, Terraza (bib8) 2011; 40 Wang, de Lamare (bib30) 2012; 6 Jia-Shu, Xian-Ci (bib10) 2000; 9 Guan, Liu, Zhang, Tao, Davis (bib25) 2017; 41 Qi, Shen, Wang, Wang (bib36) 2021; 28 Zhang, Wang, Chen (bib29) 2018; 66 Ding, Han, Chen (bib7) 2010; 51 Aronszajn (bib11) 1950; 68 Zhang, Yang, Wang, Wang (bib23) 2021; 69 Mengüç, Acır (bib18) 2017; 66 Luenberger, Ye (bib27) 1984 Cao, Cai, Hua (bib33) 2022; 163 Lai, Xu (bib21) 2021; 28 Xiong (10.1016/j.neucom.2025.130234_bib39) 2019; 26 Zhao (10.1016/j.neucom.2025.130234_bib4) 2022; 10 Khashei (10.1016/j.neucom.2025.130234_bib9) 2011; 11 Le-Tian (10.1016/j.neucom.2025.130234_bib43) 2022; 71 Aronszajn (10.1016/j.neucom.2025.130234_bib11) 1950; 68 Zhang (10.1016/j.neucom.2025.130234_bib29) 2018; 66 Ding (10.1016/j.neucom.2025.130234_bib7) 2010; 51 Liu (10.1016/j.neucom.2025.130234_bib15) 2011 Lorenz (10.1016/j.neucom.2025.130234_bib42) 1963; 20 Xiong (10.1016/j.neucom.2025.130234_bib5) 2024; 157 Jia-Shu (10.1016/j.neucom.2025.130234_bib10) 2000; 9 Hestenes (10.1016/j.neucom.2025.130234_bib38) 1952 Zhang (10.1016/j.neucom.2025.130234_bib1) 2017; 477 Takizawa (10.1016/j.neucom.2025.130234_bib12) 2015; 63 Cao (10.1016/j.neucom.2025.130234_bib33) 2022; 163 Bouboulis (10.1016/j.neucom.2025.130234_bib14) 2010; 59 Xing (10.1016/j.neucom.2025.130234_bib22) 2020; 31 Mathews (10.1016/j.neucom.2025.130234_bib26) 1987; 35 Lai (10.1016/j.neucom.2025.130234_bib21) 2021; 28 Paige (10.1016/j.neucom.2025.130234_bib41) 1982; 8 Su (10.1016/j.neucom.2025.130234_bib3) 2020; 2020 Takens (10.1016/j.neucom.2025.130234_bib32) 2006 Chen (10.1016/j.neucom.2025.130234_bib34) 2017 Su (10.1016/j.neucom.2025.130234_bib6) 2023; 132 Lu (10.1016/j.neucom.2025.130234_bib19) 2017; 36 Sayed (10.1016/j.neucom.2025.130234_bib16) 2003 Wang (10.1016/j.neucom.2025.130234_bib30) 2012; 6 Zhang (10.1016/j.neucom.2025.130234_bib2) 2019; 12 Han (10.1016/j.neucom.2025.130234_bib35) 2020; 32 Príncipe (10.1016/j.neucom.2025.130234_bib24) 2010 Luenberger (10.1016/j.neucom.2025.130234_bib27) 1984 Qi (10.1016/j.neucom.2025.130234_bib36) 2021; 28 Eweda (10.1016/j.neucom.2025.130234_bib17) 2017; 65 Guan (10.1016/j.neucom.2025.130234_bib25) 2017; 41 Zhang (10.1016/j.neucom.2025.130234_bib23) 2021; 69 Mengüç (10.1016/j.neucom.2025.130234_bib18) 2017; 66 10.1016/j.neucom.2025.130234_bib28 Chen (10.1016/j.neucom.2025.130234_bib13) 2011; 23 Toque (10.1016/j.neucom.2025.130234_bib8) 2011; 40 Liu (10.1016/j.neucom.2025.130234_bib37) 2007; 55 Mathews (10.1016/j.neucom.2025.130234_bib20) 1987; 35 Huang (10.1016/j.neucom.2025.130234_bib40) 2019; 11 Zhang (10.1016/j.neucom.2025.130234_bib31) 2021; 69 |
| References_xml | – volume: 11 start-page: 2664 year: 2011 end-page: 2675 ident: bib9 article-title: A novel hybridization of artificial neural networks and ARIMA models for time series forecasting publication-title: Appl. soft Comput. – volume: 28 start-page: 165 year: 2021 end-page: 169 ident: bib21 article-title: Robust kernel correlation based bi-channel signal detection with correlated non-Gaussian noise publication-title: IEEE Signal Process. Lett. – volume: 31 start-page: 533 year: 2020 end-page: 545 ident: bib22 article-title: Robust high-order manifold constrained low rank representation for subspace clustering publication-title: IEEE Trans. Circuits Syst. Video Technol. – volume: 8 start-page: 43 year: 1982 end-page: 71 ident: bib41 article-title: LSQR: An algorithm for sparse linear equations and sparse least squares publication-title: ACM Trans. Math. Softw. (TOMS) – volume: 66 start-page: 438 year: 2017 end-page: 448 ident: bib18 article-title: An augmented complex-valued least-mean kurtosis algorithm for the filtering of noncircular signals publication-title: IEEE Trans. Signal Process. – year: 1984 ident: bib27 article-title: Linear and Nonlinear Programming – volume: 11 start-page: 1323 year: 2019 ident: bib40 article-title: The Cauchy conjugate gradient algorithm with random Fourier features publication-title: Symmetry – volume: 69 start-page: 1859 year: 2021 end-page: 1873 ident: bib31 article-title: General Cauchy conjugate gradient algorithms based on multiple random Fourier features publication-title: IEEE Trans. Signal Process. – volume: 32 start-page: 2320 year: 2020 end-page: 2329 ident: bib35 article-title: Maximum information exploitation using broad learning system for large-scale chaotic time-series prediction publication-title: IEEE Trans. Neural Netw. Learn. Syst. – volume: 132 year: 2023 ident: bib6 article-title: Multi-Attn BLS: Multi-head attention mechanism with broad learning system for chaotic time series prediction publication-title: Appl. Soft Comput. – year: 2011 ident: bib15 article-title: Kernel Adaptive Filtering: A Comprehensive Introduction – volume: 20 start-page: 130 year: 1963 end-page: 141 ident: bib42 article-title: Deterministic nonperiodic flow publication-title: J. Atmos. Sci. – volume: 2020 start-page: 1 year: 2020 end-page: 14 ident: bib3 article-title: Estimating weak pulse signal in chaotic background with Jordan neural network publication-title: Complexity – volume: 35 start-page: 450 year: 1987 end-page: 454 ident: bib26 article-title: Improved convergence analysis of stochastic gradient adaptive filters using the sign algorithm publication-title: IEEE Trans. Acoust. Speech Signal Process. – volume: 66 start-page: 4377 year: 2018 end-page: 4387 ident: bib29 article-title: The kernel conjugate gradient algorithms publication-title: IEEE Trans. Signal Process. – volume: 163 year: 2022 ident: bib33 article-title: n-Dimensional Chaotic Map with application in secure communication publication-title: Chaos, Solitons Fractals – volume: 51 start-page: 527 year: 2010 end-page: 536 ident: bib7 article-title: Time series AR modeling with missing observations based on the polynomial transformation publication-title: Math. Comput. Model. – volume: 63 start-page: 4257 year: 2015 end-page: 4269 ident: bib12 article-title: Adaptive nonlinear estimation based on parallel projection along affine subspaces in reproducing kernel Hilbert space publication-title: IEEE Trans. Signal Process. – volume: 10 year: 2022 ident: bib4 article-title: Traffic flow prediction model based on the combination of improved gated recurrent unit and graph convolutional network publication-title: Front. Bioeng. Biotechnol. – volume: 41 start-page: 246 year: 2017 end-page: 259 ident: bib25 article-title: Truncated Cauchy non-negative matrix factorization publication-title: IEEE Trans. Pattern Anal. Mach. Intell. – volume: 9 start-page: 408 year: 2000 ident: bib10 article-title: Fast evolving multi-layer perceptrons for noisy chaotic time series modeling and predictions publication-title: Chin. Phys. – volume: 23 start-page: 22 year: 2011 end-page: 32 ident: bib13 article-title: Quantized kernel least mean square algorithm publication-title: IEEE Trans. Neural Netw. Learn. Syst. – volume: 28 start-page: 1011 year: 2021 end-page: 1015 ident: bib36 article-title: Robust Cauchy kernel conjugate gradient algorithm for non-Gaussian noises publication-title: IEEE Signal Process. Lett. – volume: 69 start-page: 1859 year: 2021 end-page: 1873 ident: bib23 article-title: General cauchy conjugate gradient algorithms based on multiple random Fourier features publication-title: IEEE Trans. Signal Process. – volume: 36 start-page: 1586 year: 2017 end-page: 1603 ident: bib19 article-title: Improved filtered-x least mean kurtosis algorithm for active noise control publication-title: Circuits, Syst. Signal Process. – start-page: 409 year: 1952 end-page: 436 ident: bib38 article-title: Methods of conjugate gradients for solving linear systems publication-title: Wash., DC: NBS – volume: 68 start-page: 337 year: 1950 end-page: 404 ident: bib11 article-title: Theory of reproducing kernels publication-title: Trans. Am. Math. Soc. – start-page: 366 year: 2006 end-page: 381 ident: bib32 article-title: Detecting strange attractors in turbulence publication-title: Dynamical Systems and Turbulence, Warwick 1980: proceedings of a symposium held at the University of Warwick 1979/80 – volume: 6 start-page: 789 year: 2012 end-page: 797 ident: bib30 article-title: Set-membership constrained conjugate gradient adaptive algorithm for beamforming publication-title: IET Signal Process. – volume: 40 start-page: 1533 year: 2011 end-page: 1544 ident: bib8 article-title: Time series factorial models with uncertainty measures: Applications to ARMA processes and financial data publication-title: Commun. Stat. - Theory Methods – volume: 59 start-page: 964 year: 2010 end-page: 978 ident: bib14 article-title: Extension of Wirtinger’s calculus to reproducing kernel Hilbert spaces and the complex kernel LMS publication-title: IEEE Trans. Signal Process. – volume: 55 start-page: 5286 year: 2007 end-page: 5298 ident: bib37 article-title: Correntropy: properties and applications in non-Gaussian signal processing publication-title: IEEE Trans. Signal Process. – volume: 35 start-page: 450 year: 1987 end-page: 454 ident: bib20 article-title: Improved convergence analysis of stochastic gradient adaptive filters using the sign algorithm publication-title: IEEE Trans. Acoust. Speech Signal Process. – year: 2003 ident: bib16 article-title: Fundamentals of Adaptive Filtering – volume: 477 start-page: 161 year: 2017 end-page: 173 ident: bib1 article-title: Multidimensional k-nearest neighbor model based on EEMD for financial time series forecasting publication-title: Phys. A: Stat. Mech. Appl. – volume: 157 year: 2024 ident: bib5 article-title: Dynamic adaptive graph convolutional transformer with broad learning system for multi-dimensional chaotic time series prediction publication-title: Appl. Soft Comput. – volume: 65 start-page: 3948 year: 2017 end-page: 3959 ident: bib17 article-title: Stabilization of high-order stochastic gradient adaptive filtering algorithms publication-title: IEEE Trans. Signal Process. – year: 2010 ident: bib24 article-title: Information Theoretic Learning: Renyis Entropy and Kernel Perspectives – volume: 71 year: 2022 ident: bib43 article-title: Prediction of chaotic time series based on Nyström Cauchy kernel conjugate gradient algorithm publication-title: Acta Phys. Sin. – reference: G.K. Boray and M.D. Srinath, Conjugate gradient techniques for adaptive filtering, 1989 IEEE International Symposium on Circuits and Systems (ISCAS), Portland, OR, USA, 1989, pp. 1752-1757 vol.3. – volume: 26 start-page: 740 year: 2019 end-page: 744 ident: bib39 article-title: The online random Fourier features conjugate gradient algorithm publication-title: IEEE Signal Process. Lett. – start-page: 1271 year: 2017 end-page: 1276 ident: bib34 article-title: Broad learning system: a new learning paradigm and system without going deep publication-title: 2017 32nd youth academic annual conference of Chinese association of automation (YAC) – volume: 12 start-page: 161 year: 2019 ident: bib2 article-title: Research on gas concentration prediction models based on LSTM multidimensional time series publication-title: Energies – volume: 9 start-page: 408 issue: 6 year: 2000 ident: 10.1016/j.neucom.2025.130234_bib10 article-title: Fast evolving multi-layer perceptrons for noisy chaotic time series modeling and predictions publication-title: Chin. Phys. doi: 10.1088/1009-1963/9/6/002 – volume: 6 start-page: 789 issue: 8 year: 2012 ident: 10.1016/j.neucom.2025.130234_bib30 article-title: Set-membership constrained conjugate gradient adaptive algorithm for beamforming publication-title: IET Signal Process. doi: 10.1049/iet-spr.2011.0324 – volume: 69 start-page: 1859 year: 2021 ident: 10.1016/j.neucom.2025.130234_bib31 article-title: General Cauchy conjugate gradient algorithms based on multiple random Fourier features publication-title: IEEE Trans. Signal Process. doi: 10.1109/TSP.2021.3065173 – volume: 12 start-page: 161 issue: 1 year: 2019 ident: 10.1016/j.neucom.2025.130234_bib2 article-title: Research on gas concentration prediction models based on LSTM multidimensional time series publication-title: Energies doi: 10.3390/en12010161 – volume: 8 start-page: 43 issue: 1 year: 1982 ident: 10.1016/j.neucom.2025.130234_bib41 article-title: LSQR: An algorithm for sparse linear equations and sparse least squares publication-title: ACM Trans. Math. Softw. (TOMS) doi: 10.1145/355984.355989 – volume: 63 start-page: 4257 issue: 16 year: 2015 ident: 10.1016/j.neucom.2025.130234_bib12 article-title: Adaptive nonlinear estimation based on parallel projection along affine subspaces in reproducing kernel Hilbert space publication-title: IEEE Trans. Signal Process. doi: 10.1109/TSP.2015.2437835 – volume: 36 start-page: 1586 year: 2017 ident: 10.1016/j.neucom.2025.130234_bib19 article-title: Improved filtered-x least mean kurtosis algorithm for active noise control publication-title: Circuits, Syst. Signal Process. doi: 10.1007/s00034-016-0379-3 – year: 2010 ident: 10.1016/j.neucom.2025.130234_bib24 – volume: 59 start-page: 964 issue: 3 year: 2010 ident: 10.1016/j.neucom.2025.130234_bib14 article-title: Extension of Wirtinger’s calculus to reproducing kernel Hilbert spaces and the complex kernel LMS publication-title: IEEE Trans. Signal Process. doi: 10.1109/TSP.2010.2096420 – year: 2003 ident: 10.1016/j.neucom.2025.130234_bib16 – volume: 31 start-page: 533 issue: 2 year: 2020 ident: 10.1016/j.neucom.2025.130234_bib22 article-title: Robust high-order manifold constrained low rank representation for subspace clustering publication-title: IEEE Trans. Circuits Syst. Video Technol. doi: 10.1109/TCSVT.2020.2989659 – ident: 10.1016/j.neucom.2025.130234_bib28 doi: 10.1109/ISCAS.1989.100705 – volume: 66 start-page: 438 issue: 2 year: 2017 ident: 10.1016/j.neucom.2025.130234_bib18 article-title: An augmented complex-valued least-mean kurtosis algorithm for the filtering of noncircular signals publication-title: IEEE Trans. Signal Process. doi: 10.1109/TSP.2017.2768024 – volume: 68 start-page: 337 issue: 3 year: 1950 ident: 10.1016/j.neucom.2025.130234_bib11 article-title: Theory of reproducing kernels publication-title: Trans. Am. Math. Soc. doi: 10.1090/S0002-9947-1950-0051437-7 – volume: 51 start-page: 527 issue: 5-6 year: 2010 ident: 10.1016/j.neucom.2025.130234_bib7 article-title: Time series AR modeling with missing observations based on the polynomial transformation publication-title: Math. Comput. Model. doi: 10.1016/j.mcm.2009.11.016 – volume: 28 start-page: 165 year: 2021 ident: 10.1016/j.neucom.2025.130234_bib21 article-title: Robust kernel correlation based bi-channel signal detection with correlated non-Gaussian noise publication-title: IEEE Signal Process. Lett. doi: 10.1109/LSP.2020.3048841 – volume: 28 start-page: 1011 year: 2021 ident: 10.1016/j.neucom.2025.130234_bib36 article-title: Robust Cauchy kernel conjugate gradient algorithm for non-Gaussian noises publication-title: IEEE Signal Process. Lett. doi: 10.1109/LSP.2021.3081381 – volume: 40 start-page: 1533 issue: 9 year: 2011 ident: 10.1016/j.neucom.2025.130234_bib8 article-title: Time series factorial models with uncertainty measures: Applications to ARMA processes and financial data publication-title: Commun. Stat. - Theory Methods doi: 10.1080/03610920903537277 – volume: 10 year: 2022 ident: 10.1016/j.neucom.2025.130234_bib4 article-title: Traffic flow prediction model based on the combination of improved gated recurrent unit and graph convolutional network publication-title: Front. Bioeng. Biotechnol. – volume: 65 start-page: 3948 issue: 15 year: 2017 ident: 10.1016/j.neucom.2025.130234_bib17 article-title: Stabilization of high-order stochastic gradient adaptive filtering algorithms publication-title: IEEE Trans. Signal Process. doi: 10.1109/TSP.2017.2698364 – year: 2011 ident: 10.1016/j.neucom.2025.130234_bib15 – volume: 32 start-page: 2320 issue: 6 year: 2020 ident: 10.1016/j.neucom.2025.130234_bib35 article-title: Maximum information exploitation using broad learning system for large-scale chaotic time-series prediction publication-title: IEEE Trans. Neural Netw. Learn. Syst. doi: 10.1109/TNNLS.2020.3004253 – volume: 477 start-page: 161 year: 2017 ident: 10.1016/j.neucom.2025.130234_bib1 article-title: Multidimensional k-nearest neighbor model based on EEMD for financial time series forecasting publication-title: Phys. A: Stat. Mech. Appl. doi: 10.1016/j.physa.2017.02.072 – volume: 41 start-page: 246 issue: 1 year: 2017 ident: 10.1016/j.neucom.2025.130234_bib25 article-title: Truncated Cauchy non-negative matrix factorization publication-title: IEEE Trans. Pattern Anal. Mach. Intell. doi: 10.1109/TPAMI.2017.2777841 – volume: 55 start-page: 5286 issue: 11 year: 2007 ident: 10.1016/j.neucom.2025.130234_bib37 article-title: Correntropy: properties and applications in non-Gaussian signal processing publication-title: IEEE Trans. Signal Process. doi: 10.1109/TSP.2007.896065 – volume: 2020 start-page: 1 year: 2020 ident: 10.1016/j.neucom.2025.130234_bib3 article-title: Estimating weak pulse signal in chaotic background with Jordan neural network publication-title: Complexity – volume: 157 year: 2024 ident: 10.1016/j.neucom.2025.130234_bib5 article-title: Dynamic adaptive graph convolutional transformer with broad learning system for multi-dimensional chaotic time series prediction publication-title: Appl. Soft Comput. doi: 10.1016/j.asoc.2024.111516 – volume: 11 start-page: 1323 issue: 10 year: 2019 ident: 10.1016/j.neucom.2025.130234_bib40 article-title: The Cauchy conjugate gradient algorithm with random Fourier features publication-title: Symmetry doi: 10.3390/sym11101323 – volume: 35 start-page: 450 issue: 4 year: 1987 ident: 10.1016/j.neucom.2025.130234_bib26 article-title: Improved convergence analysis of stochastic gradient adaptive filters using the sign algorithm publication-title: IEEE Trans. Acoust. Speech Signal Process. doi: 10.1109/TASSP.1987.1165167 – volume: 163 year: 2022 ident: 10.1016/j.neucom.2025.130234_bib33 article-title: n-Dimensional Chaotic Map with application in secure communication publication-title: Chaos, Solitons Fractals doi: 10.1016/j.chaos.2022.112519 – volume: 35 start-page: 450 issue: 4 year: 1987 ident: 10.1016/j.neucom.2025.130234_bib20 article-title: Improved convergence analysis of stochastic gradient adaptive filters using the sign algorithm publication-title: IEEE Trans. Acoust. Speech Signal Process. doi: 10.1109/TASSP.1987.1165167 – volume: 71 issue: 10 year: 2022 ident: 10.1016/j.neucom.2025.130234_bib43 article-title: Prediction of chaotic time series based on Nyström Cauchy kernel conjugate gradient algorithm publication-title: Acta Phys. Sin. – volume: 11 start-page: 2664 issue: 2 year: 2011 ident: 10.1016/j.neucom.2025.130234_bib9 article-title: A novel hybridization of artificial neural networks and ARIMA models for time series forecasting publication-title: Appl. soft Comput. doi: 10.1016/j.asoc.2010.10.015 – year: 1984 ident: 10.1016/j.neucom.2025.130234_bib27 – volume: 132 year: 2023 ident: 10.1016/j.neucom.2025.130234_bib6 article-title: Multi-Attn BLS: Multi-head attention mechanism with broad learning system for chaotic time series prediction publication-title: Appl. Soft Comput. doi: 10.1016/j.asoc.2022.109831 – volume: 23 start-page: 22 issue: 1 year: 2011 ident: 10.1016/j.neucom.2025.130234_bib13 article-title: Quantized kernel least mean square algorithm publication-title: IEEE Trans. Neural Netw. Learn. Syst. doi: 10.1109/TNNLS.2011.2178446 – start-page: 1271 year: 2017 ident: 10.1016/j.neucom.2025.130234_bib34 article-title: Broad learning system: a new learning paradigm and system without going deep – volume: 66 start-page: 4377 issue: 16 year: 2018 ident: 10.1016/j.neucom.2025.130234_bib29 article-title: The kernel conjugate gradient algorithms publication-title: IEEE Trans. Signal Process. doi: 10.1109/TSP.2018.2853109 – volume: 69 start-page: 1859 year: 2021 ident: 10.1016/j.neucom.2025.130234_bib23 article-title: General cauchy conjugate gradient algorithms based on multiple random Fourier features publication-title: IEEE Trans. Signal Process. doi: 10.1109/TSP.2021.3065173 – volume: 20 start-page: 130 issue: 2 year: 1963 ident: 10.1016/j.neucom.2025.130234_bib42 article-title: Deterministic nonperiodic flow publication-title: J. Atmos. Sci. doi: 10.1175/1520-0469(1963)020<0130:DNF>2.0.CO;2 – start-page: 409 year: 1952 ident: 10.1016/j.neucom.2025.130234_bib38 article-title: Methods of conjugate gradients for solving linear systems publication-title: Wash., DC: NBS – start-page: 366 year: 2006 ident: 10.1016/j.neucom.2025.130234_bib32 article-title: Detecting strange attractors in turbulence – volume: 26 start-page: 740 year: 2019 ident: 10.1016/j.neucom.2025.130234_bib39 article-title: The online random Fourier features conjugate gradient algorithm publication-title: IEEE Signal Process. Lett. doi: 10.1109/LSP.2019.2907480 |
| SSID | ssj0017129 |
| Score | 2.4599924 |
| Snippet | Accurate prediction of nonlinear systems in non-Gaussian noise environments has long been a significant challenge in the fields of statistical data analysis... |
| SourceID | crossref elsevier |
| SourceType | Enrichment Source Index Database Publisher |
| StartPage | 130234 |
| SubjectTerms | Cauchy cost function Conjugate gradient algorithm Kernel broad learning |
| Title | Kernel broad learning cauchy conjugate gradient algorithm for online chaotic time series prediction |
| URI | https://dx.doi.org/10.1016/j.neucom.2025.130234 |
| Volume | 639 |
| WOSCitedRecordID | wos001480846100001&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D |
| hasFullText | 1 |
| inHoldings | 1 |
| isFullTextHit | |
| isPrint | |
| journalDatabaseRights | – providerCode: PRVESC databaseName: Elsevier SD Freedom Collection Journals 2021 issn: 0925-2312 databaseCode: AIEXJ dateStart: 19950101 customDbUrl: isFulltext: true dateEnd: 99991231 titleUrlDefault: https://www.sciencedirect.com omitProxy: false ssIdentifier: ssj0017129 providerName: Elsevier |
| link | http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwtZ3ba9swFIfF1u5hL1t3Y93Wooe9BY9EtiX7MYyOXaAM2rG8GUk5Sh1auzjxaP77nWPJbkvGLoW9mGAs2ehTjk9-ORfG3uZWTxKXGvx-TyBKwCRRnloT5RlkxoFWSvlmE-r4OJvN8q-hS9-qayegqiq7usov_ytqPIewKXX2H3APk-IJ_IzQ8YjY8fhX4L9AU8H5yDS1nvdNIRYjq1t7tqEg82VLytlo0XTBXqT4LuqmXJ9ddBGHvnIG5QPXVMqVWs-P6LFhReUE5qUdQC77uk8tvgO73hBBdZheUPGFOe20QWU4ab0AsGmHzfg9KNWzUteb8qb6IFKSNUM2dyeJbaXFeG0RL0TH8ZaZlb5o0ZbJ9urB8l0FLcXv0E2oRbUIGuftYtgnNDXNjJ7bOEf36j7bFSrN0Z7tTj8dzT4P_yCpifB1FsOj9GmTXWzf9r1-7ZbccDVO99ij8BuBTz3bJ-weVE_Z477_Bg_m-BmzHjXvUPMeNfeo-YCa96j5gJojau5R84CaE2ruUfNr1M_Ztw9Hp-8_RqFpRmTjcbaONMTghLHamTizAr3N1Ol5IhQlhAI4FedOghTGOJGPTYqvN7TCQsbOpRaUil-wnaqu4CXjUtoEcAyafZFI9AVTkCloIZUQWhq9z-J-zQobKspTY5Pzog8dXBZ-pQta6cKv9D6LhlGXvqLKH65XPY4ieIXe2ytwB_125Ks7j3zNHl5v9jdsZ920cMAe2B_rctUchq32E64tjMw |
| linkProvider | Elsevier |
| openUrl | ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.genre=article&rft.atitle=Kernel+broad+learning+cauchy+conjugate+gradient+algorithm+for+online+chaotic+time+series+prediction&rft.jtitle=Neurocomputing+%28Amsterdam%29&rft.au=Su%2C+Liyun&rft.au=Wang%2C+Xiaoyi&rft.date=2025-07-28&rft.pub=Elsevier+B.V&rft.issn=0925-2312&rft.volume=639&rft_id=info:doi/10.1016%2Fj.neucom.2025.130234&rft.externalDocID=S0925231225009063 |
| thumbnail_l | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=0925-2312&client=summon |
| thumbnail_m | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=0925-2312&client=summon |
| thumbnail_s | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=0925-2312&client=summon |