Based on the maximum entropy principle, a probability density function (PDF) is derived for the distribution of wave heights in a random wave field, without any more hypothesis. The present PDF, being a non-Rayleigh f...Based on the maximum entropy principle, a probability density function (PDF) is derived for the distribution of wave heights in a random wave field, without any more hypothesis. The present PDF, being a non-Rayleigh form, involves two parameters: the average wave height H— and the state parameter γ. The role of γ in the distribution of wave heights is examined. It is found that γ may be a certain measure of sea state. A least square method for determining γ from measured data is proposed. In virtue of the method, the values of γ are determined for three sea states from the data measured in the East China Sea. The present PDF is compared with the well known Rayleigh PDF of wave height and it is shown that it much better fits the data than the Rayleigh PDF. It is expected that the present PDF would fit some other wave variables, since its derivation is not restricted only to the wave height.展开更多
A new compound distribution model for extreme wave heights of typhoon-affected sea areas is proposed on the basis of the maximum-entropy principle. The new model is formed by nesting a discrete distribution in a conti...A new compound distribution model for extreme wave heights of typhoon-affected sea areas is proposed on the basis of the maximum-entropy principle. The new model is formed by nesting a discrete distribution in a continuous one, having eight parameters which can be determined in terms of observed data of typhoon occurrence-frequency and extreme wave heights by numerically solving two sets of equations derived in this paper. The model is examined by using it to predict the N-year return-period wave height at two hydrology stations in the Yellow Sea, and the predicted results are compared with those predicted by use of some other compound distribution models. Examinations and comparisons show that the model has some advantages for predicting the N-year return-period wave height in typhoon-affected sea areas.展开更多
A new method of treating maximum wave height as a random variable in reliability analysis of breakwater caissons isproposed. The maximum wave height is expressed as the significant wave height multiplied by the so-cal...A new method of treating maximum wave height as a random variable in reliability analysis of breakwater caissons isproposed. The maximum wave height is expressed as the significant wave height multiplied by the so-called wave height ratio.The proposed wave height ratio is a type of transfer function from the significant wave height to the maximum wave height.Under the condition of a breaking wave, the ratio is intrinsically nonlinear. Therefore, the probability density function for thevariable cannot be easily defined. In this study, however, it can be derived from the relationship between the maximum andsignificant waves in a nonbreaking environment. Some examples are shown to validate the derived probability density functionfor the wave ratio parameter. By introducing the wave height ratio into reliability analysis of caisson breakwater, the maximumwave height can be used as an independent and primary random variable, which means that the risk of caisson failure during itslifetime can be evaluated realistically.展开更多
Historically, Crescent City is one of the most vulnerable communities impacted by tsunamis along the west coast of the United States, largely attributed to its offshore geography. Trans-ocean tsunamis usually produce ...Historically, Crescent City is one of the most vulnerable communities impacted by tsunamis along the west coast of the United States, largely attributed to its offshore geography. Trans-ocean tsunamis usually produce large wave runup at Crescent Harbor resulting in catastrophic damages, property loss and human death. How to determine the return values of tsunami height using relatively short-term observation data is of great significance to assess the tsunami hazards and improve engineering design along the coast of Crescent City. In the present study, the extreme tsunami heights observed along the coast of Crescent City from 1938 to 2015 are fitted using six different probabilistic distributions, namely, the Gumbel distribution, the Weibull distribution, the maximum entropy distribution, the lognormal distribution, the generalized extreme value distribution and the generalized Pareto distribution. The maximum likelihood method is applied to estimate the parameters of all above distributions. Both Kolmogorov-Smirnov test and root mean square error method are utilized for goodness-of-fit test and the better fitting distribution is selected. Assuming that the occurrence frequency of tsunami in each year follows the Poisson distribution, the Poisson compound extreme value distribution can be used to fit the annual maximum tsunami amplitude, and then the point and interval estimations of return tsunami heights are calculated for structural design. The results show that the Poisson compound extreme value distribution fits tsunami heights very well and is suitable to determine the return tsunami heights for coastal disaster prevention.展开更多
A typhoon leading is an important natural disaster to many disasters to China. A giant wave caused by it has brought large threat for an offshore project. Based on the maximum entropy principle,one new model which has...A typhoon leading is an important natural disaster to many disasters to China. A giant wave caused by it has brought large threat for an offshore project. Based on the maximum entropy principle,one new model which has 4 undetermined parameters is constructed,which is called the discrete maximum entropy probabilistic model. In practical applications,the design wave height is considered as soon as possible in a typhoon affected sea areas,the result fits the observed data well. Further more this model does not have the priority compared with other distributions as Poisson distribution. The model provides a theoretical basis for the engineering design more reasonable when considering typhoon factors comprehensively.展开更多
Extreme waves may considerably impact crucial coastal and marine engineering structures. The First Scientific Assessment Report on Ocean and Climate Change of China and The Fourth Assessment Report on Climate Change o...Extreme waves may considerably impact crucial coastal and marine engineering structures. The First Scientific Assessment Report on Ocean and Climate Change of China and The Fourth Assessment Report on Climate Change of China were published in 2020 and 2022, respectively.However, no concrete results on the long-term trends in wave changes in China have been obtained. In this study, long-term trends in extreme wave elements over the past 55 years were investigated using wave data from five in situ observation sites(i.e., Lao Hu Tan, Cheng Shan Tou,Ri Zhao, Nan Ji, Wei Zhou) along the coast of China. The five stations showed different trends in wave height. Results show a general downward trend in wave heights at the LHT and CST stations, reaching-0.78 and-1.44 cm/a, respectively, in summer at middle and high latitudes. NJI stations at middle-to-low latitudes are influenced by the winter monsoon and summer tropical cyclones, showing a substantial increase in extreme wave heights(0.7 cm/a in winter and 2.68 cm/a in summer). The cumulative duration of H_(1/10) ≥ 3 m at NJI and RZH has grown since 1990.展开更多
Accurate acquisition of forest spatial competition and tree 3D structural phenotype parameters is crucial for exploring tree-environment interactions.However,due to the occlusion between tree crowns,current UAV-based ...Accurate acquisition of forest spatial competition and tree 3D structural phenotype parameters is crucial for exploring tree-environment interactions.However,due to the occlusion between tree crowns,current UAV-based and ground-based LiDAR struggles to capture complete crown information in dense stands,making parameter extraction challenging such as maximum crown width height(HMCW).This study proposes a canopy spatial relationship-based method for constructing forest spatial structure units and employs five ensemble learning techniques to train 11 machine learning model combinations.By coupling spatial competition with phenotype parameters,the study identifies the optimal fitting model for HMCW of Chinese fir.The results demonstrate that the constructed spatial structure units align closely with existing research while addressing issues of incorrectly selected or omitted neighboring trees.Among the 10,191 trained HMCW models,the Bagging model integrating XGBoost,Random Forest(RF),Support Vector Regression(SVR),Gradient Boosting(GB),and Ridge exhibited the best performance.Compared to the best single model(RF),the Bagging model achieved improved accuracy(R^(2)=0.8346,representing a 1.6%improvement;RMSE=1.4042,reduced by 6.66%;EVS=0.8389;MAE=0.9129;MAPE=0.0508;and MedAE=0.5076,with corresponding improvements of 1.63%,1.49%,0.1%,and 7.06%,respectively).This study provides a viable solution for modeling HMCW in all species with similar structural characteristics and offers a method for extracting other hard-to-measure parameters.The refined spatial structure units better link 3D structural phenotypes with environmental factors.This approach aids in canopy morphology simulation and forest management research.展开更多
文摘Based on the maximum entropy principle, a probability density function (PDF) is derived for the distribution of wave heights in a random wave field, without any more hypothesis. The present PDF, being a non-Rayleigh form, involves two parameters: the average wave height H— and the state parameter γ. The role of γ in the distribution of wave heights is examined. It is found that γ may be a certain measure of sea state. A least square method for determining γ from measured data is proposed. In virtue of the method, the values of γ are determined for three sea states from the data measured in the East China Sea. The present PDF is compared with the well known Rayleigh PDF of wave height and it is shown that it much better fits the data than the Rayleigh PDF. It is expected that the present PDF would fit some other wave variables, since its derivation is not restricted only to the wave height.
基金supported by the Open Fund of the Key Laboratory of Research on Marine Hazards Forecasting (Grant No.LOMF1101)the Shanghai Typhoon Research Fund (Grant No. 2009ST05)the National Natural Science Foundation of China(Grant No. 40776006)
文摘A new compound distribution model for extreme wave heights of typhoon-affected sea areas is proposed on the basis of the maximum-entropy principle. The new model is formed by nesting a discrete distribution in a continuous one, having eight parameters which can be determined in terms of observed data of typhoon occurrence-frequency and extreme wave heights by numerically solving two sets of equations derived in this paper. The model is examined by using it to predict the N-year return-period wave height at two hydrology stations in the Yellow Sea, and the predicted results are compared with those predicted by use of some other compound distribution models. Examinations and comparisons show that the model has some advantages for predicting the N-year return-period wave height in typhoon-affected sea areas.
基金supported by the Korea Institute of Energy Technology Evaluation and Planning(KETEP)grant funded by the Korea Government Ministry of Knowledge Economy(Grant No.20123030020110)
文摘A new method of treating maximum wave height as a random variable in reliability analysis of breakwater caissons isproposed. The maximum wave height is expressed as the significant wave height multiplied by the so-called wave height ratio.The proposed wave height ratio is a type of transfer function from the significant wave height to the maximum wave height.Under the condition of a breaking wave, the ratio is intrinsically nonlinear. Therefore, the probability density function for thevariable cannot be easily defined. In this study, however, it can be derived from the relationship between the maximum andsignificant waves in a nonbreaking environment. Some examples are shown to validate the derived probability density functionfor the wave ratio parameter. By introducing the wave height ratio into reliability analysis of caisson breakwater, the maximumwave height can be used as an independent and primary random variable, which means that the risk of caisson failure during itslifetime can be evaluated realistically.
基金supported by the National Natural Science Foundation of China (51279186, 51479183, 51509227)the National Key Research and Development Program (2016YFC0802301)+1 种基金the National Program on Key Basic Research Project (2011CB013704)the Shandong Province Natural Science Foundation, China (ZR2014EEQ030)
文摘Historically, Crescent City is one of the most vulnerable communities impacted by tsunamis along the west coast of the United States, largely attributed to its offshore geography. Trans-ocean tsunamis usually produce large wave runup at Crescent Harbor resulting in catastrophic damages, property loss and human death. How to determine the return values of tsunami height using relatively short-term observation data is of great significance to assess the tsunami hazards and improve engineering design along the coast of Crescent City. In the present study, the extreme tsunami heights observed along the coast of Crescent City from 1938 to 2015 are fitted using six different probabilistic distributions, namely, the Gumbel distribution, the Weibull distribution, the maximum entropy distribution, the lognormal distribution, the generalized extreme value distribution and the generalized Pareto distribution. The maximum likelihood method is applied to estimate the parameters of all above distributions. Both Kolmogorov-Smirnov test and root mean square error method are utilized for goodness-of-fit test and the better fitting distribution is selected. Assuming that the occurrence frequency of tsunami in each year follows the Poisson distribution, the Poisson compound extreme value distribution can be used to fit the annual maximum tsunami amplitude, and then the point and interval estimations of return tsunami heights are calculated for structural design. The results show that the Poisson compound extreme value distribution fits tsunami heights very well and is suitable to determine the return tsunami heights for coastal disaster prevention.
基金Open Fund of the Key Laboratory of Research on Marine Hazards Forecasting under contract No. LOMF1101the National Natural Science Foundation of China under contract No. 40776006Shanghai Typhoon Research Fund under contract No. 2009ST05
文摘A typhoon leading is an important natural disaster to many disasters to China. A giant wave caused by it has brought large threat for an offshore project. Based on the maximum entropy principle,one new model which has 4 undetermined parameters is constructed,which is called the discrete maximum entropy probabilistic model. In practical applications,the design wave height is considered as soon as possible in a typhoon affected sea areas,the result fits the observed data well. Further more this model does not have the priority compared with other distributions as Poisson distribution. The model provides a theoretical basis for the engineering design more reasonable when considering typhoon factors comprehensively.
基金Supported by the National Natural Science Foundation of China (No. 52271271)National Key Research and Development Program of China (No. 2022YFE0104500)Major Science and Technology Projects of the Ministry of Water Resources (No. SKS-2022025)。
文摘Extreme waves may considerably impact crucial coastal and marine engineering structures. The First Scientific Assessment Report on Ocean and Climate Change of China and The Fourth Assessment Report on Climate Change of China were published in 2020 and 2022, respectively.However, no concrete results on the long-term trends in wave changes in China have been obtained. In this study, long-term trends in extreme wave elements over the past 55 years were investigated using wave data from five in situ observation sites(i.e., Lao Hu Tan, Cheng Shan Tou,Ri Zhao, Nan Ji, Wei Zhou) along the coast of China. The five stations showed different trends in wave height. Results show a general downward trend in wave heights at the LHT and CST stations, reaching-0.78 and-1.44 cm/a, respectively, in summer at middle and high latitudes. NJI stations at middle-to-low latitudes are influenced by the winter monsoon and summer tropical cyclones, showing a substantial increase in extreme wave heights(0.7 cm/a in winter and 2.68 cm/a in summer). The cumulative duration of H_(1/10) ≥ 3 m at NJI and RZH has grown since 1990.
基金funded by Fundamental Research Funds of CAF(CAFYBB2023PA003)Science and Technology Innovation 2030-Major Projects(2023ZD0406103)National Natural Science Foundation of China(32271877).
文摘Accurate acquisition of forest spatial competition and tree 3D structural phenotype parameters is crucial for exploring tree-environment interactions.However,due to the occlusion between tree crowns,current UAV-based and ground-based LiDAR struggles to capture complete crown information in dense stands,making parameter extraction challenging such as maximum crown width height(HMCW).This study proposes a canopy spatial relationship-based method for constructing forest spatial structure units and employs five ensemble learning techniques to train 11 machine learning model combinations.By coupling spatial competition with phenotype parameters,the study identifies the optimal fitting model for HMCW of Chinese fir.The results demonstrate that the constructed spatial structure units align closely with existing research while addressing issues of incorrectly selected or omitted neighboring trees.Among the 10,191 trained HMCW models,the Bagging model integrating XGBoost,Random Forest(RF),Support Vector Regression(SVR),Gradient Boosting(GB),and Ridge exhibited the best performance.Compared to the best single model(RF),the Bagging model achieved improved accuracy(R^(2)=0.8346,representing a 1.6%improvement;RMSE=1.4042,reduced by 6.66%;EVS=0.8389;MAE=0.9129;MAPE=0.0508;and MedAE=0.5076,with corresponding improvements of 1.63%,1.49%,0.1%,and 7.06%,respectively).This study provides a viable solution for modeling HMCW in all species with similar structural characteristics and offers a method for extracting other hard-to-measure parameters.The refined spatial structure units better link 3D structural phenotypes with environmental factors.This approach aids in canopy morphology simulation and forest management research.
