{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,2]],"date-time":"2026-05-02T01:34:12Z","timestamp":1777685652611,"version":"3.51.4"},"reference-count":14,"publisher":"SAGE Publications","issue":"4","license":[{"start":{"date-parts":[[2019,11,1]],"date-time":"2019-11-01T00:00:00Z","timestamp":1572566400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/journals.sagepub.com\/page\/policies\/text-and-data-mining-license"}],"content-domain":{"domain":["journals.sagepub.com"],"crossmark-restriction":true},"short-container-title":["International Journal of Hybrid Intelligent Systems"],"published-print":{"date-parts":[[2019,11]]},"abstract":"\n The purpose of this research is to develop and adapt a complex of hybrid mathematical and instrumental methods of analysis and risk management through the prediction of natural time series with memory. The paper poses the problem of developing a constructive method for predictive analysis of time series within the current trend of using so-called \u201cgraphical tests\u201d in the process of time series modeling using nonlinear dynamics methods. The main purpose of using graphical tests is to identify both stable and unstable quasiperiodic cycles (quasi-cycles). Modern computer technologies which allow to study in detail complex phenomena and processes were used as a toolkit for the implementation of nonlinear dynamics methods. Authors propose to use for the predictive analysis of time series a modified\n \n \n \n R<\/mml:mi>\n \/<\/mml:mo>\n S<\/mml:mi>\n <\/mml:mrow>\n <\/mml:math>\n <\/jats:inline-formula>\n -analysis algorithm, as well as phase analysis methods for constructing phase portraits in order to identify cycles of the studied time series and confirm the forecast. This approach differs from classical forecasting methods by implementing trends accounting and appears to the authors as a new tool for identifying the cyclical components of the considered time series. Using the proposed hybrid complex, the decision maker has more detailed information that cannot be obtained using classical statistics methods. In this paper, authors analyzed the time series of Kuban mountain river runoffs, revealed the impossibility of using the classical Hurst method for their predictive analysis and also proved the consistency of using the proposed hybrid toolkit to identify the cyclic components of the time series and predict it. The study acquires particular relevance in the light of the absence of any effective methods for predicting natural-economic time series, despite the proven need to study them and their risk-extreme levels. The work was supported by Russian Foundation for Basic Research (Grant No 17-06-00354 A).\n <\/jats:p>","DOI":"10.3233\/his-190272","type":"journal-article","created":{"date-parts":[[2019,5,24]],"date-time":"2019-05-24T10:51:06Z","timestamp":1558695066000},"page":"221-241","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":2,"title":["Methods of nonlinear dynamics as a hybrid tool for predictive analysis and research of risk-extreme levels"],"prefix":"10.1177","volume":"15","author":[{"given":"Elena","family":"Popova","sequence":"first","affiliation":[{"name":", Krasnodar,"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Lu\u00eds","family":"de Sousa Costa","sequence":"additional","affiliation":[{"name":"CIMO \u2013 Centro de Investiga\u00e7\u00e3o de Montanha","place":["Portugal"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Alfira","family":"Kumratova","sequence":"additional","affiliation":[{"name":", Krasnodar,"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Daria","family":"Zamotajlova","sequence":"additional","affiliation":[{"name":", Krasnodar,"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"179","published-online":{"date-parts":[[2019,11]]},"reference":[{"key":"e_1_3_1_2_2","unstructured":"BudykoM.I. Changing of the climate Gidrometeoizdat Leningrad 1974 p. 280."},{"key":"e_1_3_1_3_2","unstructured":"The results of the commission Issue 24 July 27 2002. Available online: http:\/\/www\/admkrai.krasnodar.ru (accessed on 12.02.2019)."},{"key":"e_1_3_1_4_2","first-page":"5","article-title":"Using tools of cellular automaton for the formation of predictable fuzzy values of yield on the basis of a time series, News of universities, North Caucasus region","volume":"4","author":"Perepelitsa V.A.","year":"2003","unstructured":"PerepelitsaV.A. KasaevaM.D. TebuyevaF.B. and TemirovaL.G., Using tools of cellular automaton for the formation of predictable fuzzy values of yield on the basis of a time series, News of universities, North Caucasus region, Natural Sciences 4 (2003), 5\u201311.","journal-title":"Natural Sciences"},{"key":"e_1_3_1_5_2","unstructured":"PerepelitsaV.A. and PopovaE.V. Mathematical models and methods for assessing the risks of economic social and agricultural processes Rostov-on-Don University Rostov-on-Don 2002 p. 202."},{"key":"e_1_3_1_6_2","unstructured":"PetersE. Chaos and order in the capital markets: a new analytical view of cycles prices and market volatility Wiley New Jersey 2000 p. 288."},{"key":"e_1_3_1_7_2","unstructured":"PetersE. Fractal analysis of financial markets: application of the theory of chaos in investment and the economy Internet-Trading Moscow 2004 p. 304."},{"key":"e_1_3_1_8_2","unstructured":"SiegelE. Practical business statistics Williams Moscow 2004 p. 1056."},{"key":"e_1_3_1_9_2","unstructured":"FederE. Fractals Mir Moscow 1991 p. 260."},{"key":"e_1_3_1_10_2","first-page":"73","article-title":"The use of nonlinear dynamics methods for the predictive analysis of the runoffs volumes of mountain rivers","volume":"1","author":"Yangishieva A.M.","year":"2005","unstructured":"YangishievaA.M. PerepelitsaV.A. PopovaE.V. and SalpagarovA.D., The use of nonlinear dynamics methods for the predictive analysis of the runoffs volumes of mountain rivers, Ecological Bulletin of Scientific Centers of the Black Sea Economic Cooperation 1 (2005), 73\u201384.","journal-title":"Ecological Bulletin of Scientific Centers of the Black Sea Economic Cooperation"},{"key":"e_1_3_1_11_2","unstructured":"HoldenK. PeelD.A. and ThompsonJ.L. Economic forecasting: introduction Press Syndicate of the University of Cambridge Cambridge United Kingdom 1990 p. 231."},{"key":"e_1_3_1_12_2","unstructured":"Natural Disasters in the World. Statistical Trend on Natural Disasters. National Land Agency Japan IDNDR Promotion Office 1994."},{"key":"e_1_3_1_13_2","doi-asserted-by":"publisher","DOI":"10.1103\/PhysRevLett.45.712"},{"key":"e_1_3_1_14_2","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-14347-3_4"},{"key":"e_1_3_1_15_2","doi-asserted-by":"publisher","DOI":"10.3233\/HIS-170243"}],"container-title":["International Journal of Hybrid Intelligent Systems"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/journals.sagepub.com\/doi\/pdf\/10.3233\/HIS-190272","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/journals.sagepub.com\/doi\/full-xml\/10.3233\/HIS-190272","content-type":"application\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/journals.sagepub.com\/doi\/pdf\/10.3233\/HIS-190272","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,4,29]],"date-time":"2026-04-29T08:52:46Z","timestamp":1777452766000},"score":1,"resource":{"primary":{"URL":"https:\/\/journals.sagepub.com\/doi\/10.3233\/HIS-190272"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,11]]},"references-count":14,"journal-issue":{"issue":"4","published-print":{"date-parts":[[2019,11]]}},"alternative-id":["10.3233\/HIS-190272"],"URL":"https:\/\/doi.org\/10.3233\/his-190272","relation":{},"ISSN":["1448-5869","1875-8819"],"issn-type":[{"value":"1448-5869","type":"print"},{"value":"1875-8819","type":"electronic"}],"subject":[],"published":{"date-parts":[[2019,11]]}}}