{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2023,12,15]],"date-time":"2023-12-15T00:45:37Z","timestamp":1702601137755},"reference-count":0,"publisher":"IOS Press","isbn-type":[{"value":"9781643684703","type":"print"},{"value":"9781643684710","type":"electronic"}],"license":[{"start":{"date-parts":[[2023,12,12]],"date-time":"2023-12-12T00:00:00Z","timestamp":1702339200000},"content-version":"unspecified","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2023,12,12]]},"abstract":"<jats:p>Network analysis methods of time series provide a new analytical framework on describing complex behaviors using sample data. Reproducibility is one of the important principles in scientific research. This work focuses on the algorithm review and reproduction of time series network. We paid special attention to the applicability and data characteristics of the five typical algorithms: visibility graph, phase space reconstruction, fluctuation mode, symbolic representation and coarsened multidimensional time series. It provides a reference and inspiration for future analysis of time series with various characteristics. Although two pioneer methods are widely applicable, while the directed weighted network established by coarsening thoughts contains more information about time series. In addition, coarseness process makes these approaches perform better for massive data analysis. It should be noted that: the process of data coarsening needs to ensure that the data characteristics of the original time series are inherited.<\/jats:p>","DOI":"10.3233\/faia231024","type":"book-chapter","created":{"date-parts":[[2023,12,14]],"date-time":"2023-12-14T15:06:15Z","timestamp":1702566375000},"source":"Crossref","is-referenced-by-count":0,"title":["Algorithms of Time Series Network: Approaches Reproduction and Networks Topology"],"prefix":"10.3233","author":[{"given":"Li-Na","family":"Wang","sequence":"first","affiliation":[{"name":"Science College, Inner Mongolia University of Technology, Hohhot, 010051, China"},{"name":"Inner Mongolian Key Laboratory of Statistical Analysis Theory for Life Data and Neural Network Modeling, Hohhot, 010051, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yuan-Yuan","family":"Cheng","sequence":"additional","affiliation":[{"name":"Science College, Inner Mongolia University of Technology, Hohhot, 010051, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Gui-Min","family":"Tan","sequence":"additional","affiliation":[{"name":"Science College, Inner Mongolia University of Technology, Hohhot, 010051, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"7437","container-title":["Frontiers in Artificial Intelligence and Applications","Fuzzy Systems and Data Mining IX"],"original-title":[],"link":[{"URL":"https:\/\/ebooks.iospress.nl\/pdf\/doi\/10.3233\/FAIA231024","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,12,14]],"date-time":"2023-12-14T15:06:16Z","timestamp":1702566376000},"score":1,"resource":{"primary":{"URL":"https:\/\/ebooks.iospress.nl\/doi\/10.3233\/FAIA231024"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,12,12]]},"ISBN":["9781643684703","9781643684710"],"references-count":0,"URL":"https:\/\/doi.org\/10.3233\/faia231024","relation":{},"ISSN":["0922-6389","1879-8314"],"issn-type":[{"value":"0922-6389","type":"print"},{"value":"1879-8314","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,12,12]]}}}