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Examine the Reliability of Econometrics Software: An Empirical Comparison of Time Series Modelling
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作者 Wickramasinghage M. A. Wickramasinghe Parana P. A. W. Athukorala +1 位作者 Siththara G. J. Senarathne Yapa P. R. D. Yapa 《Open Journal of Statistics》 2023年第1期25-45,共21页
Researchers must understand that naively relying on the reliability of statistical software packages may result in suboptimal, biased, or erroneous results, which affects applied economic theory and the conclusions an... Researchers must understand that naively relying on the reliability of statistical software packages may result in suboptimal, biased, or erroneous results, which affects applied economic theory and the conclusions and policy recommendations drawn from it. To create confidence in a result, several software packages should be applied to the same estimation problem. This study examines the results of three software packages (EViews, R, and Stata) in the analysis of time-series econometric data. The time-series data analysis which presents the determinants of macroeconomic growth of Sri Lanka from 1978 to 2020 has been used. The study focuses on testing for stationarity, cointegration, and significant relationships among the variables. The Augmented Dickey-Fuller and Phillips Perron tests were employed in this study to test for stationarity, while the Johansen cointegration test was utilized to test for cointegration. The study employs the vector error correction model to assess the short-run and long-term dynamics of the variables in an attempt to determine the relationship between them. Finally, the Granger Causality test is employed in order to examine the linear causation between the concerned variables. The study revealed that the results produced by three software packages for the same dataset and the same lag order vary significantly. This implies that time series econometrics results are sensitive to the software that is used by the researchers while providing different policy implications even for the same dataset. The present study highlights the necessity of further analysis to investigate the impact of software packages in time series analysis of economic scenarios. 展开更多
关键词 ECONOMETRICS Macroeconomic Determinants Software Packages Time Series modelling
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Reconstructing historical forest fire risk in the non-satellite era using the improved forest fire danger index and long short-term memory deep learning-a case study in Sichuan Province,southwestern China
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作者 Yuwen Peng Huiyi Su +1 位作者 Min Sun Mingshi Li 《Forest Ecosystems》 SCIE CSCD 2024年第1期87-99,共13页
Historical forest fire risk databases are vital for evaluating the effectiveness of past forest management approaches,enhancing forest fire warnings and emergency response capabilities,and accurately budgeting potenti... Historical forest fire risk databases are vital for evaluating the effectiveness of past forest management approaches,enhancing forest fire warnings and emergency response capabilities,and accurately budgeting potential carbon emissions resulting from fires.However,due to the unavailability of spatial information technology,such databases are extremely difficult to build reliably and completely in the non-satellite era.This study presented an improved forest fire risk reconstruction framework that integrates a deep learning-based time series prediction model and spatial interpolation to address the challenge in Sichuan Province,southwestern China.First,the forest fire danger index(FFDI)was improved by supplementing slope and aspect information.We compared the performances of three time series models,namely,the autoregressive integrated moving average(ARIMA),Prophet and long short-term memory(LSTM)in predicting the modified forest fire danger index(MFFDI).The bestperforming model was used to retrace the MFFDI of individual stations from 1941 to 1970.Following this,the Anusplin spatial interpolation method was used to map the distributions of the MFFDI at five-year intervals,which were then subjected to weighted overlay with the distance-to-river layer to generate forest fire risk maps for reconstructing the forest fire danger database.The results revealed LSTM as the most accurate in fitting and predicting the historical MFFDI,with a fitting determination coefficient(R^2)of 0.709,mean square error(MSE)of0.047,and validation R^2 and MSE of 0.508 and 0.11,respectively.Independent validation of the predicted forest fire risk maps indicated that 5 out of 7 historical forest fire events were located in forest fire-prone areas,which is higher than the results determined from the original FFDI(2 out of 7).This proves the effectiveness of the improved MFFDI and indicates a high level of reliability of the historical forest fire risk reconstruction method proposed in this study. 展开更多
关键词 Forest fire risk reconstruction MFFDI Time series models LSTM ARIMA PROPHET Anusplin
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Motion and Special Relativity in Complex Spaces
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作者 Jerzy K. Filus 《Journal of Applied Mathematics and Physics》 2024年第1期330-361,共32页
A natural extension of the Lorentz transformation to its complex version was constructed together with a parallel extension of the Minkowski M<sup>4</sup> model for special relativity (SR) to complex C<... A natural extension of the Lorentz transformation to its complex version was constructed together with a parallel extension of the Minkowski M<sup>4</sup> model for special relativity (SR) to complex C<sup>4</sup> space-time. As the [signed] absolute values of complex coordinates of the underlying motion’s characterization in C<sup>4</sup> one obtains a Newtonian-like type of motion whereas as the real parts of the complex motion’s description and of the complex Lorentz transformation, all the SR theory as modeled by M<sup>4</sup> real space-time can be recovered. This means all the SR theory is preserved in the real subspace M<sup>4</sup> of the space-time C<sup>4</sup> while becoming simpler and clearer in the new complex model’s framework. Since velocities in the complex model can be determined geometrically, with no primary use of time, time turns out to be definable within the equivalent theory of the reduced complex C<sup>4</sup> model to the C<sup>3</sup> “para-space” model. That procedure allows us to separate time from the (para)space and consider all the SR theory as a theory of C<sup>3</sup> alone. On the other hand, the complex time defined within the C<sup>3</sup> theory is interpreted and modeled by the single separate C<sup>1</sup> complex plane. The possibility for application of the C<sup>3</sup> model to quantum mechanics is suggested. As such, the model C<sup>3</sup> seems to have unifying abilities for application to different physical theories. 展开更多
关键词 Special Relativity Complex Space and Time models and Dramatic SR Simplification Complex Time and Space Separation Complex Time Interpretation
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Fault Prediction Based on Dynamic Model and Grey Time Series Model in Chemical Processes 被引量:13
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作者 田文德 胡明刚 李传坤 《Chinese Journal of Chemical Engineering》 SCIE EI CAS CSCD 2014年第6期643-650,共8页
This paper combines grey model with time series model and then dynamic model for rapid and in-depth fault prediction in chemical processes. Two combination methods are proposed. In one method, historical data is intro... This paper combines grey model with time series model and then dynamic model for rapid and in-depth fault prediction in chemical processes. Two combination methods are proposed. In one method, historical data is introduced into the grey time series model to predict future trend of measurement values in chemical process. These predicted measurements are then used in the dynamic model to retrieve the change of fault parameters by model based diagnosis algorithm. In another method, historical data is introduced directly into the dynamic model to retrieve historical fault parameters by model based diagnosis algorithm. These parameters are then predicted by the grey time series model. The two methods are applied to a gravity tank example. The case study demonstrates that the first method is more accurate for fault prediction. 展开更多
关键词 fault prediction dynamic model grey model time series model
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Traffic condition estimation with pre-selection space time model 被引量:5
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作者 DONG Hong-hui SUN Xiao-liang +2 位作者 JIA Li-min LI Hai-jian QIN Yong 《Journal of Central South University》 SCIE EI CAS 2012年第1期206-212,共7页
A pre-selection space time model was proposed to estimate the traffic condition at poor-data-detector,especially non-detector locations.The space time model is better to integrate the spatial and temporal information ... A pre-selection space time model was proposed to estimate the traffic condition at poor-data-detector,especially non-detector locations.The space time model is better to integrate the spatial and temporal information comprehensibly.Firstly,the influencing factors of the "cause nodes" were studied,and then the pre-selection "cause nodes" procedure which utilizes the Pearson correlation coefficient to evaluate the relevancy of the traffic data was introduced.Finally,only the most relevant data were collected to compose the space time model.The experimental results with the actual data demonstrate that the model performs better than other three models. 展开更多
关键词 traffic condition ESTIMATION space time model pre-selection
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Comparison of performance of statistical models in forecasting monthly streamflow of Kizil River,China 被引量:8
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作者 Shalamu ABUDU Chun-liang CUI +1 位作者 James Phillip KING Kaiser ABUDUKADEER 《Water Science and Engineering》 EI CAS 2010年第3期269-281,共13页
This paper presents the application of autoregressive integrated moving average (ARIMA), seasonal ARIMA (SARIMA), and Jordan-Elman artificial neural networks (ANN) models in forecasting the monthly streamflow of... This paper presents the application of autoregressive integrated moving average (ARIMA), seasonal ARIMA (SARIMA), and Jordan-Elman artificial neural networks (ANN) models in forecasting the monthly streamflow of the Kizil River in Xinjiang, China. Two different types of monthly streamflow data (original and deseasonalized data) were used to develop time series and Jordan-Elman ANN models using previous flow conditions as predictors. The one-month-ahead forecasting performances of all models for the testing period (1998-2005) were compared using the average monthly flow data from the Kalabeili gaging station on the Kizil River. The Jordan-Elman ANN models, using previous flow conditions as inputs, resulted in no significant improvement over time series models in one-month-ahead forecasting. The results suggest that the simple time series models (ARIMA and SARIMA) can be used in one-month-ahead streamflow forecasting at the study site with a simple and explicit model structure and a model performance similar to the Jordan-Elman ANN models. 展开更多
关键词 time series model Jordan-Elman artificial neural networks model monthly streamflow forecasting
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A continuum traffic flow model with the consideration of coupling effect for two-lane freeways 被引量:3
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作者 D.-H. Sun G.-H. Peng +1 位作者 L.-P. Fu H.-P. He 《Acta Mechanica Sinica》 SCIE EI CAS CSCD 2011年第2期228-236,共9页
A new higher-order continuum model is proposed by considering the coupling and lane changing effects of the vehicles on two adjacent lanes. A stability analysis of the proposed model provides the conditions that ensur... A new higher-order continuum model is proposed by considering the coupling and lane changing effects of the vehicles on two adjacent lanes. A stability analysis of the proposed model provides the conditions that ensure its linear stability. Issues related to lane changing, shock waves and rarefaction waves, local clustering and phase transition are also investigated with numerical experiments. The simulation results show that the proposed model is capable of providing explanations to some particular traffic phenomena commonly observable in real traffic flows. 展开更多
关键词 Two-lane traffic Two delay time scales model Numerical simulation Coupling effect Phase transition
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Time Series Models for Short Term Prediction of the Incidence of Japanese Encephalitis in Xianyang City, P R China 被引量:3
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作者 张荣强 李凤英 +5 位作者 刘军礼 刘美宁 罗文瑞 马婷 马波 张志刚 《Chinese Medical Sciences Journal》 CAS CSCD 2017年第3期152-160,共9页
Objective To construct a model of Seasonal Autoregressive Integrated Moving Average (SARIMA) for forecasting the epidemic of Japanese encephalitis (JE) in Xianyang, Shaanxi, China, and provide valuable reference ... Objective To construct a model of Seasonal Autoregressive Integrated Moving Average (SARIMA) for forecasting the epidemic of Japanese encephalitis (JE) in Xianyang, Shaanxi, China, and provide valuable reference information for JE control and prevention. Methods Theoretically epidemiologic study was employed in the research process. Monthly incidence data on JE for the period from Jan 2005 to Sep 2014 were obtained from a passive surveillance system at the Center for Diseases Prevention and Control in Xianyang, Shaanxi province. An optimal SARIMA model was developed for JE incidence from 2005 to 2013 with the Box and Jenkins approach. This SARIMA model could predict JE incidence for the year 2014 and 2015. Results SARIMA (1, 1, 1) (2, 1, 1)12 was considered to be the best model with the lowest Bayesian information criterion, Akaike information criterion, Mean Absolute Error values, the highest R2, and a lower Mean Absolute Percent Error. SARIMA (1, 1, 1) (2, 1, 1)12 was stationary and accurate for predicting JE incidence in Xianyang. The predicted incidence, around 0.3/100 000 from June to August in 2014 with low errors, was higher compared with the actual incidence. Therefore, SARIMA (1, 1, 1) (2, 1, 1)12 appeared to be reliable and accurate and could be applied to incidence prediction. Conclusions The proposed prediction model could provide clues to early identification of the JE incidence that is increased abnormally (≥0.4/100 000). According to the predicted results in 2014, the JE incidence in Xianyang will decline slightly and reach its peak from June to August.The authors wish to thank the staff from the CDCs from 13 counties of Xianyang, Shaanxi province, China, for their contribution to Japanese encephalitis cases reporting. 展开更多
关键词 Japanese encephalitis time series models INCIDENCE PREDICTION
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GLOBAL EXISTENCE AND ASYMPTOTIC BEHAVIOR FOR AN 1-D COMPRESSIBLE ENERGY TRANSPORT MODEL 被引量:4
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作者 黎勇 《Acta Mathematica Scientia》 SCIE CSCD 2009年第5期1295-1308,共14页
In this article, the global existence and the large time behavior of smooth solutions to the initial boundary value problem for a degenerate compressible energy transport model are established.
关键词 degenerate parabolic system hyperbolic-parabolic energy transport model large time behavior
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Modeling of time dependent subsidence for coal and ore deposits 被引量:4
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作者 Ryszard Hejmanowski 《International Journal of Coal Science & Technology》 EI 2015年第4期287-292,共6页
Coal and ore underground mining generates subsidence and deformation of the land surface. Those defor- mations may cause damage to buildings and infrastructures. The environmental impact of subsidence will not be acce... Coal and ore underground mining generates subsidence and deformation of the land surface. Those defor- mations may cause damage to buildings and infrastructures. The environmental impact of subsidence will not be accepted in the future by the society in many countries. Especially acceptance of the ground deformations decreases every year there, where the mining regions are densely urbanized, the The only solution is to limit the subsidence or its impact on the infrastructure. The first is not rentable for the mining industry, the second depends on the precise subsidence prediction and good preventing management involved in the mining areas. The precision of the subsidence prediction depends strictly on the mathematical model of the deformation phenomenon and on the uncertainty of the input data. The subsidence prediction in the geological conditions of the raw materials used to be made on the basis of numerical modeling or the stochastic models. A modified solution of the stochastic model by Knothe will be presented in the paper. The author focuses on the precise description of the deposit shape and on the time dependent displacements of the rock mass. A two parameters' time function has been introduced in the algorithm. 展开更多
关键词 Subsidence prediction Influence function modeling in time
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Time function of surface subsidence based on Harris model in mined-out area 被引量:7
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作者 Liu Xinrong Wang Junbao +2 位作者 Guo Jianqiang Yuan Hong Li Peng 《International Journal of Mining Science and Technology》 SCIE EI 2013年第2期251-254,共4页
The surface subsidence is a common environmental hazard in mined-out area. Based on careful analysis of the regularity of surface subsidence in mined-out area, we proposed a new time function based on Harris curve mod... The surface subsidence is a common environmental hazard in mined-out area. Based on careful analysis of the regularity of surface subsidence in mined-out area, we proposed a new time function based on Harris curve model in consideration of the shortage of current surface subsidence time functions. By analyzing the characteristics of the new time function, we found that it could meet the dynamic process, the velocity change process and the acceleration change process during surface subsidence. Then its rationality had been verified through project cases. The results show that the proposed time function model can give a good reflection of the regularity of surface subsidence in mined-out area and can accurately predict surface subsidence. And the prediction data of the model are a little greater than measured data on condition of proper measured data quantity, which is safety in the engineering. This model provides a new method for the analysis of surface subsidence in mined-out area and reference for future prediction, and it is valuable to engineering application. 展开更多
关键词 Mined-out area Surface subsidence Time function Harris model Prediction
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Space station short-term mission planning using ontology modelling and time iteration 被引量:5
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作者 Huijiao Bu Jin Zhang Yazhong Luo 《Journal of Systems Engineering and Electronics》 SCIE EI CSCD 2016年第2期407-421,共15页
This paper studies the problem of the space station short-term mission planning, which aims to allocate the executing time of missions effectively, schedule the corresponding resources reasonably and arrange the time ... This paper studies the problem of the space station short-term mission planning, which aims to allocate the executing time of missions effectively, schedule the corresponding resources reasonably and arrange the time of the astronauts properly. A domain model is developed by using the ontology theory to describe the concepts, constraints and relations of the planning domain formally, abstractly and normatively. A method based on time iteration is adopted to solve the short-term planning problem. Meanwhile, the resolving strategies are proposed to resolve different kinds of conflicts induced by the constraints of power, heat, resource, astronaut and relationship. The proposed approach is evaluated in a test case with fifteen missions, thirteen resources and three astronauts. The results show that the developed domain ontology model is reasonable, and the time iteration method using the proposed resolving strategies can successfully obtain the plan satisfying all considered constraints. 展开更多
关键词 space station mission planning ontology modelling time iteration
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A class of asymptotic solution for the time delay wind field model of an ocean 被引量:1
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作者 周先春 石兰芳 莫嘉琪 《Chinese Physics B》 SCIE EI CAS CSCD 2014年第4期83-90,共8页
A time delay model of a two-layer barotropic ocean with Rayleigh dissipation is built. Using the improved perturba- tion method, an analytic asymptotic solution of a better approximate degree is obtained in the mid-la... A time delay model of a two-layer barotropic ocean with Rayleigh dissipation is built. Using the improved perturba- tion method, an analytic asymptotic solution of a better approximate degree is obtained in the mid-latitude wind field, and the physical meaning of the corresponding solution is also discussed. 展开更多
关键词 two-layers barotropic time delay model asymptotic method
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A Hybrid Neural Network and Box-Jenkins Models for Time Series Forecasting 被引量:1
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作者 Mohammad Hadwan Basheer M.Al-Maqaleh +2 位作者 Fuad N.Al-Badani Rehan Ullah Khan Mohammed A.Al-Hagery 《Computers, Materials & Continua》 SCIE EI 2022年第3期4829-4845,共17页
Time series forecasting plays a significant role in numerous applications,including but not limited to,industrial planning,water consumption,medical domains,exchange rates and consumer price index.The main problem is ... Time series forecasting plays a significant role in numerous applications,including but not limited to,industrial planning,water consumption,medical domains,exchange rates and consumer price index.The main problem is insufficient forecasting accuracy.The present study proposes a hybrid forecastingmethods to address this need.The proposed method includes three models.The first model is based on the autoregressive integrated moving average(ARIMA)statistical model;the second model is a back propagation neural network(BPNN)with adaptive slope and momentum parameters;and the thirdmodel is a hybridization between ARIMA and BPNN(ARIMA/BPNN)and artificial neural networks and ARIMA(ARIMA/ANN)to gain the benefits of linear and nonlinearmodeling.The forecasting models proposed in this study are used to predict the indices of the consumer price index(CPI),and predict the expected number of cancer patients in the Ibb Province in Yemen.Statistical standard measures used to evaluate the proposed method include(i)mean square error,(ii)mean absolute error,(iii)root mean square error,and(iv)mean absolute percentage error.Based on the computational results,the improvement rate of forecasting the CPI dataset was 5%,71%,and 4%for ARIMA/BPNN model,ARIMA/ANN model,and BPNN model respectively;while the result for cancer patients’dataset was 7%,200%,and 19%for ARIMA/BPNNmodel,ARIMA/ANN model,and BPNNmodel respectively.Therefore,it is obvious that the proposed method reduced the randomness degree,and the alterations affected the time series with data non-linearity.The ARIMA/ANN model outperformed each of its components when it was applied separately in terms of increasing the accuracy of forecasting and decreasing the overall errors of forecasting. 展开更多
关键词 Hybrid model forecasting non-linear data time series models cancer patients neural networks box-jenkins consumer price index
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A Numerical Algorithm Based on Quadratic Finite Element for Two-Dimensional Nonlinear Time Fractional Thermal Diffusion Model 被引量:3
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作者 Yanlong Zhang Baoli Yin +2 位作者 Yue Cao Yang Liu Hong Li 《Computer Modeling in Engineering & Sciences》 SCIE EI 2020年第3期1081-1098,共18页
In this article,a high-order scheme,which is formulated by combining the quadratic finite element method in space with a second-order time discrete scheme,is developed for looking for the numerical solution of a two-d... In this article,a high-order scheme,which is formulated by combining the quadratic finite element method in space with a second-order time discrete scheme,is developed for looking for the numerical solution of a two-dimensional nonlinear time fractional thermal diffusion model.The time Caputo fractional derivative is approximated by using the L2-1formula,the first-order derivative and nonlinear term are discretized by some second-order approximation formulas,and the quadratic finite element is used to approximate the spatial direction.The error accuracy O(h3+t2)is obtained,which is verified by the numerical results. 展开更多
关键词 Quadratic finite element two-dimensional nonlinear time fractional thermal diffusion model L2-1formula.
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Time lag characteristics of sap flow in seed-maize and their implications for modeling transpiration in an arid region of Northwest China 被引量:5
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作者 BO Xiaodong DU Taisheng +1 位作者 DING Risheng Louise COMAS 《Journal of Arid Land》 SCIE CSCD 2017年第4期515-529,共15页
Plant capacity for water storage leads to time lags between basal stem sap flow and transpiration in various woody plants. Internal water storage depends on the sizes of woody plants. However, the changes and its infl... Plant capacity for water storage leads to time lags between basal stem sap flow and transpiration in various woody plants. Internal water storage depends on the sizes of woody plants. However, the changes and its influencing factors in time lags of basal stem flow during the development of herbaceous plants including crops remain unclear. A field experiment was conducted in an arid region of Northwest China to examine the time lag characteristics of sap flow in seed-maize and to calibrate the transpiration modeling. Cross-correlation analysis was used to estimate the time lags between stem sap flow and meteorological driving factors including solar radiation(R_s) and vapor pressure deficit of the air(VPD_(air)). Results indicate that the changes in seed-maize stem sap flow consistently lagged behind the changes in R_s and preceded the changes in VPD_(air) both on hourly and daily scales, suggesting that light-mediated stomatal closures drove sap flow responses. The time lag in the maize's sap flow differed significantly during different growth stages and the difference was potentially due to developmental changes in capacitance tissue and/or xylem during ontogenesis. The time lags between stem sap flow and R_s in both female plants and male plants corresponded to plant use of stored water and were independent of total plant water use. Time lags of sap flow were always longer in male plants than in female plants. Theoretically, dry soil may decrease the speed by which sap flow adjusts ahead of shifts in VPD_(air) in comparison with wet soil and also increase the speed by which sap flow adjusts to R_s. However, sap flow lags that were associated with R_s before irrigation and after irrigation in female plants did not shift. Time series analysis method provided better results for simulating seed-maize sap flow with advantages of allowing for fewer variables to be included. This approach would be helpful in improving the accuracy of estimation for canopy transpiration and conductance using meteorological measurements. 展开更多
关键词 seed-maize sap flow capacitance transfer function model time lag stored water use
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A time fractional model to represent rainfall process 被引量:1
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作者 Jacques GOLDER Maminirina JOELSON +1 位作者 Marie-Christine NEEL Liliana DI PIETRO 《Water Science and Engineering》 EI CAS CSCD 2014年第1期32-40,共9页
This paper deals with a stochastic representation of the rainfall process. The analysis of a rainfall time series shows that cumulative representation of a rainfall time series can be modeled as a non-Gaussian random ... This paper deals with a stochastic representation of the rainfall process. The analysis of a rainfall time series shows that cumulative representation of a rainfall time series can be modeled as a non-Gaussian random walk with a log-normal jump distribution and a time-waiting distribution following a tempered a-stable probability law. Based on the random walk model, a fractional Fokker-Planck equation (FFPE) with tempered a-stable waiting times was obtained. Through the comparison of observed data and simulated results from the random walk model and FFPE model with tempered a-stable waiting times, it can be concluded that the behavior of the rainfall process is globally reproduced, and the FFPE model with tempered a-stable waiting times is more efficient in reproducing the observed behavior. 展开更多
关键词 rainfall process heavy-tailed probability distribution tempered a-stable probability law log-normal law Hurst exponent continuous time random walk model fractional Fokker-Planck equation
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Dynamics of the HBV model with diffusion and time delay 被引量:2
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作者 QIAO mei-hong,QI huan(Department of Control Science and Engineering,Huazhong University of Science and Technology,Wuhan 430074) 《医用生物力学》 EI CAS CSCD 2009年第S1期117-118,共2页
Chronic hepatitis B infection is a major health problem,with approximately 350 million virus carriers worldwide.In Africa,about 30%-60% of children and 60%-100% of adults have
关键词 HBV TIME Dynamics of the HBV model with diffusion and time delay
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Multi-factor high-order intuitionistic fuzzy timeseries forecasting model 被引量:1
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作者 Ya'nan Wang Yingjie Lei +1 位作者 Yang Lei Xiaoshi Fan 《Journal of Systems Engineering and Electronics》 SCIE EI CSCD 2016年第5期1054-1062,共9页
Fuzzy sets theory cannot describe the neutrality degreeof data, which has largely limited the objectivity of fuzzy time seriesin uncertain data forecasting. With this regard, a multi-factor highorderintuitionistic fuz... Fuzzy sets theory cannot describe the neutrality degreeof data, which has largely limited the objectivity of fuzzy time seriesin uncertain data forecasting. With this regard, a multi-factor highorderintuitionistic fuzzy time series forecasting model is built. Inthe new model, a fuzzy clustering algorithm is used to get unequalintervals, and a more objective technique for ascertaining membershipand non-membership functions of the intuitionistic fuzzy setis proposed. On these bases, forecast rules based on multidimensionalintuitionistic fuzzy modus ponens inference are established.Finally, contrast experiments on the daily mean temperature ofBeijing are carried out, which show that the novel model has aclear advantage of improving the forecast accuracy. 展开更多
关键词 multi-factor high-order intuitionistic fuzzy time series forecasting model intuitionistic fuzzy inference.
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RECONFIGURABLE PRODUCTION LINE MODELING AND SCHEDULING USING PETRI NETS AND GENETIC ALGORITHM 被引量:8
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作者 XIE Nan LI Aiping 《Chinese Journal of Mechanical Engineering》 SCIE EI CAS CSCD 2006年第3期362-367,共6页
In response to the production capacity and functionality variations, a genetic algorithm (GA) embedded with deterministic timed Petri nets(DTPN) for reconfigurable production line(RPL) is proposed to solve its s... In response to the production capacity and functionality variations, a genetic algorithm (GA) embedded with deterministic timed Petri nets(DTPN) for reconfigurable production line(RPL) is proposed to solve its scheduling problem. The basic DTPN modules are presented to model the corresponding variable structures in RPL, and then the scheduling model of the whole RPL is constructed. And in the scheduling algorithm, firing sequences of the Petri nets model are used as chromosomes, thus the selection, crossover, and mutation operator do not deal with the elements in the problem space, but the elements of Petri nets model. Accordingly, all the algorithms for GA operations embedded with Petri nets model are proposed. Moreover, the new weighted single-objective optimization based on reconfiguration cost and E/T is used. The results of a DC motor RPL scheduling suggest that the presented DTPN-GA scheduling algorithm has a significant impact on RPL scheduling, and provide obvious improvements over the conventional scheduling method in practice that meets duedate, minimizes reconfiguration cost, and enhances cost effectivity. 展开更多
关键词 Reconfigurable production line Deterministic timed Petri nets (DTPN) modeling Scheduling Genetic algorithm(GA)
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