Sea-water-level(SWL)prediction significantly impacts human lives and maritime activities in coastal regions,particularly at offshore locations with shallow water levels.Long-term SWL forecasts,which are conventionally...Sea-water-level(SWL)prediction significantly impacts human lives and maritime activities in coastal regions,particularly at offshore locations with shallow water levels.Long-term SWL forecasts,which are conventionally obtained via harmonic analysis,become ineffective when nonperiodic meteorological events predominate.Artificial intelligence combined with other data-processing methods can effectively forecast highly nonlinear and nonstationary inflow patterns by recognizing historical relationships between input and output.These techniques are considerably useful in time-series data predictions.This paper reports the development of a hybrid model to realize accurate multihour SWL forecasting by combining an adaptive neuro-fuzzy inference system(ANFIS)with wavelet decomposition while using sea-level anomaly(SLA)and wind-shear-velocity components as inputs.Numerous wavelet-ANFIS(WANFIS)models have been tested using different inputs to assess their applicability as alternatives to the artificial neural network(ANN),wavelet ANN(WANN),and ANFIS models.Different error definitions have been used to evaluate results,which indicate that integrated wavelet-decomposition and ANFIS models improve the accuracy of SWL prediction and that the inputs of SLA and wind-shear velocity exhibit superior prediction capability compared to conventional SWL-only models.展开更多
In the last 10 years(2012-2021),five hypoxic events have been observed in summer in the central Bohai Sea(CBS).Frequent and persistent hypoxia will have an impact on the ecosystem of the CBS.In this paper,historical s...In the last 10 years(2012-2021),five hypoxic events have been observed in summer in the central Bohai Sea(CBS).Frequent and persistent hypoxia will have an impact on the ecosystem of the CBS.In this paper,historical sea temperature(ST),salinity(SAL),density(Den),and dissolved oxygen(DO)concentration data from three stations in the CBS are analyzed via the linear regression method,and the correlations between the stratification factors(ST,SAL,and Den)and DO concentration are determined.The thresholds of the stratification factors at the three stations in June in the year in which hypoxia occurred were determined and applied to survey data from 29 stations in late May to early June in 2022 in the CBS;this assessment found that the data from 19 stations indicated that hypoxia was about to occur.In August,the survey data showed that 14 out of the 29 stations indicated hypoxic conditions,of which 12 were from the predicted 19 stations,meaning that the estimation accuracy reached 63%.The same approach was applied to data from June 2023.The data for August from a bottom-type online monitoring system in the CBS verified the occurrence of hypoxic events around Sta.M2.The results show that the strength of the seawater stratification plays a leading role in hypoxic events in the summer in the CBS,and the thresholds of the stratification factors can be used to predict the occurrence of hypoxic events.展开更多
基金The National Key R&D Program of China under contract No.2016YFC1402609。
文摘Sea-water-level(SWL)prediction significantly impacts human lives and maritime activities in coastal regions,particularly at offshore locations with shallow water levels.Long-term SWL forecasts,which are conventionally obtained via harmonic analysis,become ineffective when nonperiodic meteorological events predominate.Artificial intelligence combined with other data-processing methods can effectively forecast highly nonlinear and nonstationary inflow patterns by recognizing historical relationships between input and output.These techniques are considerably useful in time-series data predictions.This paper reports the development of a hybrid model to realize accurate multihour SWL forecasting by combining an adaptive neuro-fuzzy inference system(ANFIS)with wavelet decomposition while using sea-level anomaly(SLA)and wind-shear-velocity components as inputs.Numerous wavelet-ANFIS(WANFIS)models have been tested using different inputs to assess their applicability as alternatives to the artificial neural network(ANN),wavelet ANN(WANN),and ANFIS models.Different error definitions have been used to evaluate results,which indicate that integrated wavelet-decomposition and ANFIS models improve the accuracy of SWL prediction and that the inputs of SLA and wind-shear velocity exhibit superior prediction capability compared to conventional SWL-only models.
基金The National Natural Science Foundation of China under contract Nos U2106211 and 42076197supported by the Data Center of Yantai Insti-tute of Coastal Zone Research,Chinese Academy of Sciences,China.Some of the data and samples were collected utilizing R/V Lanhai101 during open research cruise NORC2023-01supported by the NSFC Shiptime Sharing Project under contrac No.42249901.
文摘In the last 10 years(2012-2021),five hypoxic events have been observed in summer in the central Bohai Sea(CBS).Frequent and persistent hypoxia will have an impact on the ecosystem of the CBS.In this paper,historical sea temperature(ST),salinity(SAL),density(Den),and dissolved oxygen(DO)concentration data from three stations in the CBS are analyzed via the linear regression method,and the correlations between the stratification factors(ST,SAL,and Den)and DO concentration are determined.The thresholds of the stratification factors at the three stations in June in the year in which hypoxia occurred were determined and applied to survey data from 29 stations in late May to early June in 2022 in the CBS;this assessment found that the data from 19 stations indicated that hypoxia was about to occur.In August,the survey data showed that 14 out of the 29 stations indicated hypoxic conditions,of which 12 were from the predicted 19 stations,meaning that the estimation accuracy reached 63%.The same approach was applied to data from June 2023.The data for August from a bottom-type online monitoring system in the CBS verified the occurrence of hypoxic events around Sta.M2.The results show that the strength of the seawater stratification plays a leading role in hypoxic events in the summer in the CBS,and the thresholds of the stratification factors can be used to predict the occurrence of hypoxic events.
