{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T02:05:19Z","timestamp":1760148319513,"version":"build-2065373602"},"reference-count":25,"publisher":"MDPI AG","issue":"4","license":[{"start":{"date-parts":[[2023,4,19]],"date-time":"2023-04-19T00:00:00Z","timestamp":1681862400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Science and Technology Project of Hebei Education Department","award":["ZD2021088","HBMESO2315","21373302D"],"award-info":[{"award-number":["ZD2021088","HBMESO2315","21373302D"]}]},{"name":"Marine Ecological Restoration and Smart Ocean Engineering Research Center of Hebei Province","award":["ZD2021088","HBMESO2315","21373302D"],"award-info":[{"award-number":["ZD2021088","HBMESO2315","21373302D"]}]},{"name":"Intelligent Early Warning Prediction and Demonstration Application of Pollutants from Land to Sea","award":["ZD2021088","HBMESO2315","21373302D"],"award-info":[{"award-number":["ZD2021088","HBMESO2315","21373302D"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Entropy"],"abstract":"<jats:p>In recent years, with the frequency of marine disasters, water quality has become an important environmental problem for researchers, and much effort has been put into the prediction of marine water quality. The temporal and spatial correlation of marine water quality parameters directly determines whether the marine time-series data prediction task can be completed efficiently. However, existing research has only focused on the correlation analysis of marine data in a certain area and has ignored the temporal and spatial characteristics of marine data in complex and changeable marine environments. Therefore, we constructed a spatio-temporal dynamic analysis model of marine water quality based on a cross-recurrence plot (CRP) and cross-recurrence quantitative analysis (CRQA). The time-series data of marine water quality were first mapped to high-dimensional space through phase space reconstruction, and then the dynamic relationship among various factors affecting water quality was visually displayed through CRP. Finally, their correlation was quantitatively explained by CRQA. The experimental results showed that our scheme demonstrated well the dynamic correlation of various factors affecting water quality in different locations, providing important data support for the spatio-temporal prediction of marine water quality.<\/jats:p>","DOI":"10.3390\/e25040689","type":"journal-article","created":{"date-parts":[[2023,4,20]],"date-time":"2023-04-20T03:25:11Z","timestamp":1681961111000},"page":"689","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Spatio-Temporal Analysis of Marine Water Quality Data Based on Cross-Recurrence Plot (CRP) and Cross-Recurrence Quantitative Analysis (CRQA)"],"prefix":"10.3390","volume":"25","author":[{"given":"Zhigang","family":"Li","sequence":"first","affiliation":[{"name":"College of Artificial Intelligence, North China University of Science and Technology, Bohai Road, Tangshan 063210, China"},{"name":"Hebei Key Laboratory of Industrial Perception, Tangshan 063210, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ting","family":"Sun","sequence":"additional","affiliation":[{"name":"College of Artificial Intelligence, North China University of Science and Technology, Bohai Road, Tangshan 063210, China"},{"name":"Hebei Key Laboratory of Industrial Perception, Tangshan 063210, China"},{"name":"Marine Ecological Restoration and Smart Ocean Engineering Research Center of Hebei Province, Qinhuangdao 066000, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yu","family":"Wang","sequence":"additional","affiliation":[{"name":"College of Artificial Intelligence, North China University of Science and Technology, Bohai Road, Tangshan 063210, China"},{"name":"Hebei Key Laboratory of Industrial Perception, Tangshan 063210, China"},{"name":"Marine Ecological Restoration and Smart Ocean Engineering Research Center of Hebei Province, Qinhuangdao 066000, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yujie","family":"Liu","sequence":"additional","affiliation":[{"name":"College of Artificial Intelligence, North China University of Science and Technology, Bohai Road, Tangshan 063210, China"},{"name":"Hebei Key Laboratory of Industrial Perception, Tangshan 063210, China"},{"name":"Marine Ecological Restoration and Smart Ocean Engineering Research Center of Hebei Province, Qinhuangdao 066000, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5101-5953","authenticated-orcid":false,"given":"Xiaochuan","family":"Sun","sequence":"additional","affiliation":[{"name":"College of Artificial Intelligence, North China University of Science and Technology, Bohai Road, Tangshan 063210, China"},{"name":"Hebei Key Laboratory of Industrial Perception, Tangshan 063210, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2023,4,19]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"48318","DOI":"10.1109\/ACCESS.2022.3172274","article-title":"Waternet: A network for monitoring and assessing water quality for drinking and irrigation purposes","volume":"10","author":"Ajayi","year":"2022","journal-title":"IEEE Access"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"732","DOI":"10.1007\/s11227-018-2297-6","article-title":"A parallel FP-growth algorithm on World Ocean Atlas data with multi-core CPU","volume":"75","author":"Jiang","year":"2019","journal-title":"J. Supercomput."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"691","DOI":"10.1016\/j.jhazmat.2019.02.067","article-title":"Distribution of plastic polymer types in the marine environment; A meta-analysis","volume":"369","author":"Zadjelovic","year":"2019","journal-title":"J. Hazard. Mater."},{"key":"ref_4","first-page":"1","article-title":"Computing and plotting correlograms by Python and R libraries for correlation analysis of the environmental data in marine geomorphology","volume":"3","author":"Lemenkova","year":"2019","journal-title":"Jeomorfol. Ara\u015ft. Derg."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"365","DOI":"10.1016\/j.jenvman.2017.03.024","article-title":"A novel water quality data analysis framework based on time-series data mining","volume":"196","author":"Deng","year":"2017","journal-title":"J. Environ. Manag."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"1773","DOI":"10.1109\/TDEI.2017.006407","article-title":"Identification and localization of partial discharge in transformer insulation adopting cross recurrence plot analysis of acoustic signals detected using fiber bragg gratings","volume":"24","author":"Kanakambaran","year":"2017","journal-title":"IEEE Trans. Dielectr. Electr. Insul."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"189","DOI":"10.1152\/japplphysiol.00364.2019","article-title":"Dynamical interaction between heart rate and blood pressure of end-stage renal disease patients evaluated by cross recurrence plot diagonal analysis","volume":"128","author":"Infante","year":"2020","journal-title":"J. Appl. Physiol."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"93","DOI":"10.1016\/j.corsci.2017.05.012","article-title":"Recurrence plot-based dynamic analysis on electrochemical noise of the evolutive corrosion process","volume":"124","author":"Liu","year":"2017","journal-title":"Corros. Sci."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"185121","DOI":"10.1109\/ACCESS.2019.2960764","article-title":"Machine learning based dynamic correlation on marine environmental data using cross-recurrence strategy","volume":"7","author":"Li","year":"2019","journal-title":"IEEE Access"},{"key":"ref_10","first-page":"1466","article-title":"Phase space reconstruction driven spatio-temporal feature learning for dynamic facial expression recognition","volume":"13","author":"Shuai","year":"2020","journal-title":"IEEE Trans. Affect. Comput."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"5666","DOI":"10.1109\/JIOT.2020.2980617","article-title":"Recurrence behavior statistics of blast furnace gas sensor data in industrial internet of things","volume":"7","author":"Li","year":"2020","journal-title":"IEEE Internet Things J."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"163172","DOI":"10.1109\/ACCESS.2019.2952365","article-title":"Phase space reconstruction-based conceptor network for time series prediction","volume":"7","author":"Xu","year":"2019","journal-title":"IEEE Access"},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"13","DOI":"10.1016\/j.apenergy.2018.04.075","article-title":"Short term load forecasting based on phase space reconstruction algorithm and bi-square kernel regression model","volume":"224","author":"Fan","year":"2018","journal-title":"Appl. Energy"},{"key":"ref_14","doi-asserted-by":"crossref","unstructured":"Coco, M.I., M\u00f8nster, D., and Leonardi, G. (arXiv, 2020). Unidimensional and multidimensional methods for recurrence quantification analysis with CRQA, arXiv.","DOI":"10.32614\/RJ-2021-062"},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"4920","DOI":"10.1002\/joc.7106","article-title":"Dynamic analysis of meteorological time series in Hong Kong: A nonlinear perspective","volume":"41","author":"Yan","year":"2021","journal-title":"Int. J. Climatol."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"23","DOI":"10.1016\/j.chaos.2017.01.005","article-title":"Nonlinearity and chaos in wireless network traffic","volume":"96","author":"Mukherjee","year":"2017","journal-title":"Chaos Solitons Fractals"},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"6308","DOI":"10.1109\/TIE.2021.3095819","article-title":"Recurrence plots based method for detecting series arc faults in photovoltaic systems","volume":"69","author":"Amiri","year":"2021","journal-title":"IEEE Trans. Ind. Electron."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"361","DOI":"10.1016\/j.jsv.2015.03.046","article-title":"Selection of optimal threshold to construct recurrence plot for structural operational vibration measurements","volume":"349","author":"Yang","year":"2015","journal-title":"J. Sound Vib."},{"key":"ref_19","doi-asserted-by":"crossref","unstructured":"Mart\u00edn-Gonz\u00e1lez, S., Navarro-Mesa, J.L., Juli\u00e1-Serd\u00e1, G., Ram\u00edrez-\u00c1vila, G.M., and Ravelo-Garc\u00eda, A.G. (2018). Improving the understanding of sleep apnea characterization using recurrence quantification analysis by defining overall acceptable values for the dimensionality of the system, the delay, and the distance threshold. PLoS ONE, 13.","DOI":"10.1371\/journal.pone.0194462"},{"key":"ref_20","first-page":"100593","article-title":"A remote sensing approach to ascertain spatial and temporal variations of seawater quality parameters in the coastal area of bay of Bengal, Bangladesh","volume":"23","author":"Ashikur","year":"2021","journal-title":"Remote. Sens. Appl. Soc. Environ."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"6835","DOI":"10.1080\/03067319.2020.1817428","article-title":"Biofloc technology: Water quality (ph, temperature, do, cod, bod) in a flood & drain aquaponic system","volume":"102","author":"Deswati","year":"2022","journal-title":"Int. J. Environ. Anal. Chem."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"123962","DOI":"10.1016\/j.jhydrol.2019.123962","article-title":"Multi-step ahead modelling of river water quality parameters using ensemble artificial intelligence-based approach","volume":"577","author":"Elkiran","year":"2019","journal-title":"J. Hydrol."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"6377","DOI":"10.1007\/s13762-018-2049-4","article-title":"Prediction of water quality parameters using evolutionary computing-based formulations","volume":"16","author":"Najafzadeh","year":"2019","journal-title":"Int. J. Environ. Sci. Technol."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"131586","DOI":"10.1016\/j.chemosphere.2021.131586","article-title":"Using simple and easy water quality parameters to predict trihalomethane occurrence in tap water","volume":"286","author":"Xu","year":"2022","journal-title":"Chemosphere"},{"key":"ref_25","doi-asserted-by":"crossref","unstructured":"Susanti, N.D., Sagita, D., Apriyanto, I.F., Anggara, C.E.W., Darmajana, D.A., and Rahayuningtyas, A. (2021, January 4\u20135). Design and implementation of water quality monitoring system (temperature, ph, tds) in aquaculture using iot at low cost. Proceedings of the 6th International Conference of Food, Agriculture, and Natural Resource (IC-FANRES 2021), Tangerang, Indonesia.","DOI":"10.2991\/absr.k.220101.002"}],"container-title":["Entropy"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1099-4300\/25\/4\/689\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T19:19:06Z","timestamp":1760123946000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1099-4300\/25\/4\/689"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,4,19]]},"references-count":25,"journal-issue":{"issue":"4","published-online":{"date-parts":[[2023,4]]}},"alternative-id":["e25040689"],"URL":"https:\/\/doi.org\/10.3390\/e25040689","relation":{},"ISSN":["1099-4300"],"issn-type":[{"type":"electronic","value":"1099-4300"}],"subject":[],"published":{"date-parts":[[2023,4,19]]}}}