The performance of lithium-ion batteries(LIBs)gradually declines over time,making it critical to predict the battery’s state of health(SOH)in real-time.This paper presents a model that incorporates health indicators ...The performance of lithium-ion batteries(LIBs)gradually declines over time,making it critical to predict the battery’s state of health(SOH)in real-time.This paper presents a model that incorporates health indicators and ensemble Gaussian process regression(EGPR)to predict the SOH of LIBs.Firstly,the degradation process of an LIB is analyzed through indirect health indicators(HIs)derived from voltage and temperature during discharge.Next,the parameters in the EGPR model are optimized using the gannet optimization algorithm(GOA),and the EGPR is employed to estimate the SOH of LIBs.Finally,the proposed model is tested under various experimental scenarios and compared with other machine learning models.The effectiveness of EGPR model is demonstrated using the National Aeronautics and Space Administration(NASA)LIB.The root mean square error(RMSE)is maintained within 0.20%,and the mean absolute error(MAE)is below 0.16%,illustrating the proposed approach’s excellent predictive accuracy and wide applicability.展开更多
The subset threshold auto regressive (SSTAR) model, which is capable of reproducing the limit cycle behavior of nonlinear time series, is introduced. The algorithm for fitting the sampled data with SSTAR model is pr...The subset threshold auto regressive (SSTAR) model, which is capable of reproducing the limit cycle behavior of nonlinear time series, is introduced. The algorithm for fitting the sampled data with SSTAR model is proposed and applied to model and forecast power load. Numerical example verifies that desirable accuracy of short term load forecasting can be achieved by using the SSTAR model.展开更多
Recently, wavelet neural networks have become a popular tool for non-linear functional approximation. Wavelet neural networks, which basis functions are orthonormal scalling functions, are more suitable in approximati...Recently, wavelet neural networks have become a popular tool for non-linear functional approximation. Wavelet neural networks, which basis functions are orthonormal scalling functions, are more suitable in approximating to function. Based on it, approximating to NLAR(p) with wavelet neural networks is studied.展开更多
A combination of the optimal subset regression (OSR) approach,the coupled general circulation model of the National Climate Center (NCC-CGCM) and precipitation observations from 160 stations over China is used to cons...A combination of the optimal subset regression (OSR) approach,the coupled general circulation model of the National Climate Center (NCC-CGCM) and precipitation observations from 160 stations over China is used to construct a statistical downscaling forecast model for precipitation in summer.Retroactive forecasts are performed to assess the skill of statistical downscaling during the period from 2003 to 2009.The results show a poor simulation for summer precipitation by the NCCCGCM for China,and the average spatial anomaly correlation coefficient (ACC) is 0.01 in the forecast period.The forecast skill can be improved by OSR statistical downscaling,and the OSR forecast performs better than the NCC-CGCM in most years except 2003.The spatial ACC is more than 0.2 in the years 2008 and 2009,which proves to be relatively skillful.Moreover,the statistical downscaling forecast performs relatively well for the main rain belt of the summer precipitation in some years,including 2005,2006,2008,and 2009.However,the forecast skill of statistical downscaling is restricted to some extent by the relatively low skill of the NCCCGCM.展开更多
Background： Increased ambient temperature has been implicated in increased physical aggression, which has important practical consequences. The present study investigates this established relationship between aggress...Background： Increased ambient temperature has been implicated in increased physical aggression, which has important practical consequences. The present study investigates this established relationship between aggressive behavior and ambient temperature in the highly aggressive context of professional football in the National Football League （NFL）. Methods： Using a publicly available dataset, authors conducted multiple hierarchical regression analyses on game-level data （2326 games）. Results： The analysis revealed that temperature positively predicted aggressive penalties in football, and that this relationship was significant for teams playing at home but not for visiting teams. Conclusion： These results indicate that even in the aggressive context of football, warmer weather contributes to increased violence. Further, the presence of the heat-aggression relationship for the home team suggests that the characteristics of interacting groups may influence whether heat would have an adverse effect on the outcome of those interactions.展开更多
Under the condition of the designated collection ratio and the interfused ratio of mullock, to ensure the least energy consumption, the parameters of collecting head （the feed speed, the axes height of collecting hea...Under the condition of the designated collection ratio and the interfused ratio of mullock, to ensure the least energy consumption, the parameters of collecting head （the feed speed, the axes height of collecting head, and the rotate speed） are chosen as the optimized parameters. According to the force on the cutting pick, the collecting size of the cobalt crust and bedrock and the optimized energy consumption of the collecting head, the optimized design model of collecting head is built. Taking two hundred groups seabed microtopography for grand in the range of depth displacement from 4.5 to 5.5 era, then making use of the improved simulated annealing genetic algorithm （SAGA）, the corresponding optimized result can be obtained. At the same time, in order to speed up the controlling of collecting head, the optimization results are analyzed using the regression analysis method, and the conclusion of the second parameter of the seabed microtopography is drawn.展开更多
This paper discusses the influence of the country-of-origin image, product knowledge and product involvement on consumer purchase decisions. Data were collected by a questionnaire from college students. Multiple regre...This paper discusses the influence of the country-of-origin image, product knowledge and product involvement on consumer purchase decisions. Data were collected by a questionnaire from college students. Multiple regression analysis of data from 379 respondents was used to test three hypotheses. The results show that the country-of-origin image, product knowledge and product involvement all have a significantly positive effect on consumer purchase decision. Further research should examine the different dimensions of involvement and product knowledge on consumer purchase decisions展开更多
基金supported by Fundamental Research Program of Shanxi Province(No.202203021211088)Shanxi Provincial Natural Science Foundation(No.202204021301049).
文摘The performance of lithium-ion batteries(LIBs)gradually declines over time,making it critical to predict the battery’s state of health(SOH)in real-time.This paper presents a model that incorporates health indicators and ensemble Gaussian process regression(EGPR)to predict the SOH of LIBs.Firstly,the degradation process of an LIB is analyzed through indirect health indicators(HIs)derived from voltage and temperature during discharge.Next,the parameters in the EGPR model are optimized using the gannet optimization algorithm(GOA),and the EGPR is employed to estimate the SOH of LIBs.Finally,the proposed model is tested under various experimental scenarios and compared with other machine learning models.The effectiveness of EGPR model is demonstrated using the National Aeronautics and Space Administration(NASA)LIB.The root mean square error(RMSE)is maintained within 0.20%,and the mean absolute error(MAE)is below 0.16%,illustrating the proposed approach’s excellent predictive accuracy and wide applicability.
文摘The subset threshold auto regressive (SSTAR) model, which is capable of reproducing the limit cycle behavior of nonlinear time series, is introduced. The algorithm for fitting the sampled data with SSTAR model is proposed and applied to model and forecast power load. Numerical example verifies that desirable accuracy of short term load forecasting can be achieved by using the SSTAR model.
文摘Recently, wavelet neural networks have become a popular tool for non-linear functional approximation. Wavelet neural networks, which basis functions are orthonormal scalling functions, are more suitable in approximating to function. Based on it, approximating to NLAR(p) with wavelet neural networks is studied.
基金supported by China Meteorological Administration R & D Special Fund for Public Welfare (Meteorology) (Grant Nos. GYHY200906018 and GYHY200906015)the National Natural Science Foundation of China (Grant No.41005051)the National Key Technologies R & D Program of China (Grant No. 2009BAC51B05)
文摘A combination of the optimal subset regression (OSR) approach,the coupled general circulation model of the National Climate Center (NCC-CGCM) and precipitation observations from 160 stations over China is used to construct a statistical downscaling forecast model for precipitation in summer.Retroactive forecasts are performed to assess the skill of statistical downscaling during the period from 2003 to 2009.The results show a poor simulation for summer precipitation by the NCCCGCM for China,and the average spatial anomaly correlation coefficient (ACC) is 0.01 in the forecast period.The forecast skill can be improved by OSR statistical downscaling,and the OSR forecast performs better than the NCC-CGCM in most years except 2003.The spatial ACC is more than 0.2 in the years 2008 and 2009,which proves to be relatively skillful.Moreover,the statistical downscaling forecast performs relatively well for the main rain belt of the summer precipitation in some years,including 2005,2006,2008,and 2009.However,the forecast skill of statistical downscaling is restricted to some extent by the relatively low skill of the NCCCGCM.
文摘Background： Increased ambient temperature has been implicated in increased physical aggression, which has important practical consequences. The present study investigates this established relationship between aggressive behavior and ambient temperature in the highly aggressive context of professional football in the National Football League （NFL）. Methods： Using a publicly available dataset, authors conducted multiple hierarchical regression analyses on game-level data （2326 games）. Results： The analysis revealed that temperature positively predicted aggressive penalties in football, and that this relationship was significant for teams playing at home but not for visiting teams. Conclusion： These results indicate that even in the aggressive context of football, warmer weather contributes to increased violence. Further, the presence of the heat-aggression relationship for the home team suggests that the characteristics of interacting groups may influence whether heat would have an adverse effect on the outcome of those interactions.
基金Project(50875265) supported by the National Natural Science Foundation of ChinaProject(20080440992) supported by the Postdoctoral Science Foundation of ChinaProject(2009SK3159) supported by the Technology Support Plan of Hunan Province,China
文摘Under the condition of the designated collection ratio and the interfused ratio of mullock, to ensure the least energy consumption, the parameters of collecting head （the feed speed, the axes height of collecting head, and the rotate speed） are chosen as the optimized parameters. According to the force on the cutting pick, the collecting size of the cobalt crust and bedrock and the optimized energy consumption of the collecting head, the optimized design model of collecting head is built. Taking two hundred groups seabed microtopography for grand in the range of depth displacement from 4.5 to 5.5 era, then making use of the improved simulated annealing genetic algorithm （SAGA）, the corresponding optimized result can be obtained. At the same time, in order to speed up the controlling of collecting head, the optimization results are analyzed using the regression analysis method, and the conclusion of the second parameter of the seabed microtopography is drawn.
文摘This paper discusses the influence of the country-of-origin image, product knowledge and product involvement on consumer purchase decisions. Data were collected by a questionnaire from college students. Multiple regression analysis of data from 379 respondents was used to test three hypotheses. The results show that the country-of-origin image, product knowledge and product involvement all have a significantly positive effect on consumer purchase decision. Further research should examine the different dimensions of involvement and product knowledge on consumer purchase decisions
