This paper focuses on the analytical and numerical asymptotical stability of neutral reaction-diffusion equations with piecewise continuous arguments.First,for the analytical solutions of the equations,we derive their...This paper focuses on the analytical and numerical asymptotical stability of neutral reaction-diffusion equations with piecewise continuous arguments.First,for the analytical solutions of the equations,we derive their expressions and asymptotical stability criteria.Second,for the semi-discrete and one-parameter fully-discrete finite element methods solving the above equations,we work out the sufficient conditions for assuring that the finite element solutions are asymptotically stable.Finally,with a typical example with numerical experiments,we illustrate the applicability of the obtained theoretical results.展开更多
Accurate prediction of shipmotion is very important for ensuringmarine safety,weapon control,and aircraft carrier landing,etc.Ship motion is a complex time-varying nonlinear process which is affected by many factors.T...Accurate prediction of shipmotion is very important for ensuringmarine safety,weapon control,and aircraft carrier landing,etc.Ship motion is a complex time-varying nonlinear process which is affected by many factors.Time series analysis method and many machine learning methods such as neural networks,support vector machines regression(SVR)have been widely used in ship motion predictions.However,these single models have certain limitations,so this paper adopts amulti-model prediction method.First,ensemble empirical mode decomposition(EEMD)is used to remove noise in ship motion data.Then the randomforest(RF)prediction model optimized by genetic algorithm(GA),back propagation neural network(BPNN)prediction model and SVR prediction model are respectively established,and the final prediction results are obtained by results of three models.And the weights coefficients are determined by the correlation coefficients,reducing the risk of prediction and improving the reliability.The experimental results show that the proposed combined model EEMD-GARF-BPNN-SVR is superior to the single predictive model and more reliable.The mean absolute percentage error(MAPE)of the proposed model is 0.84%,but the results of the single models are greater than 1%.展开更多
Accurate carbon price forecasting is essential to provide the guidance for production and investment.Current research is mainly dependent on plenty of historical samples of carbon prices,which is impractical for the n...Accurate carbon price forecasting is essential to provide the guidance for production and investment.Current research is mainly dependent on plenty of historical samples of carbon prices,which is impractical for the newly launched carbon market due to its short history.Based on the idea of transfer learning,this paper proposes a novel price forecasting model,which utilizes the correlation between the new and mature markets.The model is firstly pretrained on large data of mature market by gated recurrent unit algorithm,and then fine-tuned by the target market samples.An integral framework,including complexity decomposition method for data pre-processing,sample entropy for feature selection,and support vector regression for result post-processing,is provided.In the empirical analysis of new Chinese market,the root mean square error,mean absolute error,mean absolute percentage error,and determination coefficient of the model are 0.529,0.476,0.717%and 0.501 respectively,proving its validity.展开更多
Objective:To investigate the clinical efficacy of acupuncture combined with emotional intervention in patients with post-stroke depression(PSD).Methods:A total of 100 patients with PSD who met the inclusion criteria w...Objective:To investigate the clinical efficacy of acupuncture combined with emotional intervention in patients with post-stroke depression(PSD).Methods:A total of 100 patients with PSD who met the inclusion criteria were randomly divided into an experimental group(50 cases)and a control group(50 cases)using the random number table method,and the enrollment was in order of admission time.The control group used conventional treatment of oral antidepressant Deanxit tablets(0.5 mg flupenthixol+10 mg melitracen)with the dose appropriately adjusted according to the patient’s medication effect,and modern rehabilitation treatment given selectively according to the patient’s condition.The experimental group had similar treatment as the control group with the addition of traditional Chinese medicine(TCM)acupuncture combined with emotional intervention.The application effects of both groups before and after treatment were verified using the Hamilton Depression Rating Scale(Ham-D),National Institutes of Health Stroke Scale(NIHSS),and Activities of Daily Living(ADL),serotonin levels were measured,and statistical analyses were carried out.Results:The total effective rate of patients in the experimental group was significantly higher than that in the control group,and the Ham-D score,NIHSS score,ADL score,and serotonin level after treatment were significantly higher than those in the control group,and the difference between the two groups was statistically significant(P<0.05).Conclusion:For patients with PSD,adding TCM acupuncture with emotional intervention on top of conventional treatment significantly improve the clinical efficacy and better improve the daily life ability of patients.展开更多
文摘This paper focuses on the analytical and numerical asymptotical stability of neutral reaction-diffusion equations with piecewise continuous arguments.First,for the analytical solutions of the equations,we derive their expressions and asymptotical stability criteria.Second,for the semi-discrete and one-parameter fully-discrete finite element methods solving the above equations,we work out the sufficient conditions for assuring that the finite element solutions are asymptotically stable.Finally,with a typical example with numerical experiments,we illustrate the applicability of the obtained theoretical results.
文摘Accurate prediction of shipmotion is very important for ensuringmarine safety,weapon control,and aircraft carrier landing,etc.Ship motion is a complex time-varying nonlinear process which is affected by many factors.Time series analysis method and many machine learning methods such as neural networks,support vector machines regression(SVR)have been widely used in ship motion predictions.However,these single models have certain limitations,so this paper adopts amulti-model prediction method.First,ensemble empirical mode decomposition(EEMD)is used to remove noise in ship motion data.Then the randomforest(RF)prediction model optimized by genetic algorithm(GA),back propagation neural network(BPNN)prediction model and SVR prediction model are respectively established,and the final prediction results are obtained by results of three models.And the weights coefficients are determined by the correlation coefficients,reducing the risk of prediction and improving the reliability.The experimental results show that the proposed combined model EEMD-GARF-BPNN-SVR is superior to the single predictive model and more reliable.The mean absolute percentage error(MAPE)of the proposed model is 0.84%,but the results of the single models are greater than 1%.
文摘Accurate carbon price forecasting is essential to provide the guidance for production and investment.Current research is mainly dependent on plenty of historical samples of carbon prices,which is impractical for the newly launched carbon market due to its short history.Based on the idea of transfer learning,this paper proposes a novel price forecasting model,which utilizes the correlation between the new and mature markets.The model is firstly pretrained on large data of mature market by gated recurrent unit algorithm,and then fine-tuned by the target market samples.An integral framework,including complexity decomposition method for data pre-processing,sample entropy for feature selection,and support vector regression for result post-processing,is provided.In the empirical analysis of new Chinese market,the root mean square error,mean absolute error,mean absolute percentage error,and determination coefficient of the model are 0.529,0.476,0.717%and 0.501 respectively,proving its validity.
基金The Shandong Traditional Chinese Medicine Science and Technology Development Program 2020Q132。
文摘Objective:To investigate the clinical efficacy of acupuncture combined with emotional intervention in patients with post-stroke depression(PSD).Methods:A total of 100 patients with PSD who met the inclusion criteria were randomly divided into an experimental group(50 cases)and a control group(50 cases)using the random number table method,and the enrollment was in order of admission time.The control group used conventional treatment of oral antidepressant Deanxit tablets(0.5 mg flupenthixol+10 mg melitracen)with the dose appropriately adjusted according to the patient’s medication effect,and modern rehabilitation treatment given selectively according to the patient’s condition.The experimental group had similar treatment as the control group with the addition of traditional Chinese medicine(TCM)acupuncture combined with emotional intervention.The application effects of both groups before and after treatment were verified using the Hamilton Depression Rating Scale(Ham-D),National Institutes of Health Stroke Scale(NIHSS),and Activities of Daily Living(ADL),serotonin levels were measured,and statistical analyses were carried out.Results:The total effective rate of patients in the experimental group was significantly higher than that in the control group,and the Ham-D score,NIHSS score,ADL score,and serotonin level after treatment were significantly higher than those in the control group,and the difference between the two groups was statistically significant(P<0.05).Conclusion:For patients with PSD,adding TCM acupuncture with emotional intervention on top of conventional treatment significantly improve the clinical efficacy and better improve the daily life ability of patients.
