This paper present a simulation study of an evolutionary algorithms, Particle Swarm Optimization PSO algorithm to optimize likelihood function of ARMA（1, 1） model, where maximizing likelihood function is equivalent ...This paper present a simulation study of an evolutionary algorithms, Particle Swarm Optimization PSO algorithm to optimize likelihood function of ARMA（1, 1） model, where maximizing likelihood function is equivalent to maximizing its logarithm, so the objective function ＇obj.fun＇ is maximizing log-likelihood function. Monte Carlo method adapted for implementing and designing the experiments of this simulation. This study including a comparison among three versions of PSO algorithm “Constriction coefficient CCPSO, Inertia weight IWPSO, and Fully Informed FIPSO”, the experiments designed by setting different values of model parameters al, bs sample size n, moreover the parameters of PSO algorithms. MSE used as test statistic to measure the efficiency PSO to estimate model. The results show the ability of PSO to estimate ARMA＇ s parameters, and the minimum values of MSE getting for COPSO.展开更多
Atmospheric models are physical equations based on the ideal gas law. Applied to the atmosphere, this law yields equations for water, vapor (gas), ice, air, humidity, dryness, fire, and heat, thus defining the model o...Atmospheric models are physical equations based on the ideal gas law. Applied to the atmosphere, this law yields equations for water, vapor (gas), ice, air, humidity, dryness, fire, and heat, thus defining the model of key atmospheric parameters. The distribution of these parameters across the entire planet Earth is the origin of the formation of the climatic cycle, which is a normal climatic variation. To do this, the Earth is divided into eight (8) parts according to the number of key parameters to be defined in a physical representation of the model. Following this distribution, numerical models calculate the constants for the formation of water, vapor, ice, dryness, thermal energy (fire), heat, air, and humidity. These models vary in complexity depending on the indirect trigonometric direction and simplicity in the sum of neighboring models. Note that the constants obtained from the equations yield 275.156˚K (2.006˚C) for water, 273.1596˚K (0.00963˚C) for vapor, 273.1633˚K (0.0133˚C) for ice, 0.00365 in/s for atmospheric dryness, 1.996 in<sup>2</sup>/s for humidity, 2.993 in<sup>2</sup>/s for air, 1 J for thermal energy of fire, and 0.9963 J for heat. In summary, this study aims to define the main parameters and natural phenomena contributing to the modification of planetary climate. .展开更多
In grey system theory,the studies in the field of grey prediction model are focused on real number sequences,rather than grey number ones.Hereby,a prediction model based on interval grey number sequences is proposed.B...In grey system theory,the studies in the field of grey prediction model are focused on real number sequences,rather than grey number ones.Hereby,a prediction model based on interval grey number sequences is proposed.By mining the geometric features of interval grey number sequences on a two-dimensional surface,all the interval grey numbers are converted into real numbers by means of certain algorithm,and then the prediction model is established based on those real number sequences.The entire process avoids the algebraic operations of grey number,and the prediction problem of interval grey number is usefully solved.Ultimately,through an example＇s program simulation,the validity and practicability of this novel model are verified.展开更多
To create a new prediction model, the unbiased GM （1,1） model is optimized by the five-point slide method in this paper. Then, based on the occurrence areas of dce blast in Enshi District during 1995 -2004, the new ...To create a new prediction model, the unbiased GM （1,1） model is optimized by the five-point slide method in this paper. Then, based on the occurrence areas of dce blast in Enshi District during 1995 -2004, the new model and unbiased GM （1, 1 ） model are applied to predict the occurrence areas of rice blast during 2005 -2010. Predicting outcomes show that the prediction accuracy of five-point unbiased sliding optimized GM （1, 1 ） model is higher than the unbiased GM （1,1） model. Finally, combined with the prediction results, the author provides some suggestion for Enshi District in the prevention and control of rice blast in 2010.展开更多
Extensive iron deposition has been observed in the midbrain substantia nigra （SN） of Parkinson＇s disease （PD） patients, but the mechanisms of iron deposition in the SN remain poorly understood. The present study ...Extensive iron deposition has been observed in the midbrain substantia nigra （SN） of Parkinson＇s disease （PD） patients, but the mechanisms of iron deposition in the SN remain poorly understood. The present study investigated the relationship between dopaminergic neuronal damage, iron content changes, and divalent metal transporter 1 （DMT1） in the midbrain SN of PD rats to explore the relationship between time of iron deposition and DMT1 expression. Frozen midbrain SN sections from model rats were stained with Perls＇ iron. Results showed massive loss of tyrosine hydroxylase （TH）-positive cells in the SN and increased DMT1 expression in model group rats. No obvious iron deposition was observed in the SN during early stages after damage, but significant iron deposition was detected at 8 weeks post-injury. Results demonstrate that the loss of TH-positive cells in the SN appeared simultaneously with increased DMT1 expression. Extensive iron deposition occurred at 8 weeks post injury, which could be regarded as an early time window of iron deposition.展开更多
目的研究以专科护士为主导的“1+1+X”协同管理模式对稳定型心绞痛患者病情、自我管理能力的影响。方法方便选取2021年3月—2023年3月聊城市第二人民医院心血管内科收治的86例稳定型心绞痛患者为研究对象,根据不同护理方法分为常规组和...目的研究以专科护士为主导的“1+1+X”协同管理模式对稳定型心绞痛患者病情、自我管理能力的影响。方法方便选取2021年3月—2023年3月聊城市第二人民医院心血管内科收治的86例稳定型心绞痛患者为研究对象,根据不同护理方法分为常规组和协同管理组,各43例。常规组采用常规护理,协同管理组采用以专科护士为主导的“1+1+X”协同管理模式护理,两组均持续护理1个月。观察对比两组患者护理前后生活质量[健康调查简表(MOS Item Short Form Health Survey,SF-36)]、焦虑抑郁心理状况、自我管理能力[冠心病自我管理行为量表(Coronary Artery Disease Self-management Scale,CSMS)]。结果护理后,协同管理组SF-36量表评分高于常规组,差异有统计学意义(P<0.05);协同管理组焦虑自评量表(38.18±3.52)分、抑郁自评量表(39.21±3.24)分均优于常规组的(43.23±3.61)分、(45.03±3.69)分,差异有统计学意义(t=6.568、7.772,P均<0.05);协同管理组CSMS评分高于常规组,差异有统计学意义(P均<0.05)。结论以专科护士为主导的“1+1+X”协同管理模式应用于稳定型心绞痛患者护理可有效提升生活质量,改善不良心理状态,提高自我管理能力。展开更多
By studying the spectral properties of the underlying operator corresponding to the M/G/1 queueing model with optional second service we obtain that the time-dependent solution of the model strongly converges to its s...By studying the spectral properties of the underlying operator corresponding to the M/G/1 queueing model with optional second service we obtain that the time-dependent solution of the model strongly converges to its steady-state solution. We also show that the time-dependent queueing size at the departure point converges to the corresponding steady-state queueing size at the departure point.展开更多
This paper expresses the efficient outputs of decisionmaking unit（DMU） as the sum of ＂average outputs＂ forecasted by a GM（1,N） model and ＂increased outputs＂ which reflect the difficulty to realize efficient ou...This paper expresses the efficient outputs of decisionmaking unit（DMU） as the sum of ＂average outputs＂ forecasted by a GM（1,N） model and ＂increased outputs＂ which reflect the difficulty to realize efficient outputs.The increased outputs are solved by linear programming using data envelopment analysis efficiency theories,wherein a new sample is introduced whose inputs are equal to the budget in the issue No.n ＋ 1 and outputs are forecasted by the GM（1,N） model.The shortcoming in the existing methods that the forecasted efficient outputs may be less than the possible actual outputs according to developing trends of input-output rate in the periods of pre-n is overcome.The new prediction method provides decision-makers with more decisionmaking information,and the initial conditions are easy to be given.展开更多
文摘This paper present a simulation study of an evolutionary algorithms, Particle Swarm Optimization PSO algorithm to optimize likelihood function of ARMA（1, 1） model, where maximizing likelihood function is equivalent to maximizing its logarithm, so the objective function ＇obj.fun＇ is maximizing log-likelihood function. Monte Carlo method adapted for implementing and designing the experiments of this simulation. This study including a comparison among three versions of PSO algorithm “Constriction coefficient CCPSO, Inertia weight IWPSO, and Fully Informed FIPSO”, the experiments designed by setting different values of model parameters al, bs sample size n, moreover the parameters of PSO algorithms. MSE used as test statistic to measure the efficiency PSO to estimate model. The results show the ability of PSO to estimate ARMA＇ s parameters, and the minimum values of MSE getting for COPSO.
文摘Atmospheric models are physical equations based on the ideal gas law. Applied to the atmosphere, this law yields equations for water, vapor (gas), ice, air, humidity, dryness, fire, and heat, thus defining the model of key atmospheric parameters. The distribution of these parameters across the entire planet Earth is the origin of the formation of the climatic cycle, which is a normal climatic variation. To do this, the Earth is divided into eight (8) parts according to the number of key parameters to be defined in a physical representation of the model. Following this distribution, numerical models calculate the constants for the formation of water, vapor, ice, dryness, thermal energy (fire), heat, air, and humidity. These models vary in complexity depending on the indirect trigonometric direction and simplicity in the sum of neighboring models. Note that the constants obtained from the equations yield 275.156˚K (2.006˚C) for water, 273.1596˚K (0.00963˚C) for vapor, 273.1633˚K (0.0133˚C) for ice, 0.00365 in/s for atmospheric dryness, 1.996 in<sup>2</sup>/s for humidity, 2.993 in<sup>2</sup>/s for air, 1 J for thermal energy of fire, and 0.9963 J for heat. In summary, this study aims to define the main parameters and natural phenomena contributing to the modification of planetary climate. .
基金supported by the National Natural Science Foundation of China(7084001290924022)the Ph.D.Thesis Innovation and Excellent Foundation of Nanjing University of Aeronautics and Astronautics(2010)
文摘In grey system theory,the studies in the field of grey prediction model are focused on real number sequences,rather than grey number ones.Hereby,a prediction model based on interval grey number sequences is proposed.By mining the geometric features of interval grey number sequences on a two-dimensional surface,all the interval grey numbers are converted into real numbers by means of certain algorithm,and then the prediction model is established based on those real number sequences.The entire process avoids the algebraic operations of grey number,and the prediction problem of interval grey number is usefully solved.Ultimately,through an example＇s program simulation,the validity and practicability of this novel model are verified.
基金Supported by Science Research Project of Department of Education of Hubei Province (B20092901)~~
文摘To create a new prediction model, the unbiased GM （1,1） model is optimized by the five-point slide method in this paper. Then, based on the occurrence areas of dce blast in Enshi District during 1995 -2004, the new model and unbiased GM （1, 1 ） model are applied to predict the occurrence areas of rice blast during 2005 -2010. Predicting outcomes show that the prediction accuracy of five-point unbiased sliding optimized GM （1, 1 ） model is higher than the unbiased GM （1,1） model. Finally, combined with the prediction results, the author provides some suggestion for Enshi District in the prevention and control of rice blast in 2010.
基金the Scientific Research Common Program of Beijing Municipal Commission of Education,No.KM200610025008
文摘Extensive iron deposition has been observed in the midbrain substantia nigra （SN） of Parkinson＇s disease （PD） patients, but the mechanisms of iron deposition in the SN remain poorly understood. The present study investigated the relationship between dopaminergic neuronal damage, iron content changes, and divalent metal transporter 1 （DMT1） in the midbrain SN of PD rats to explore the relationship between time of iron deposition and DMT1 expression. Frozen midbrain SN sections from model rats were stained with Perls＇ iron. Results showed massive loss of tyrosine hydroxylase （TH）-positive cells in the SN and increased DMT1 expression in model group rats. No obvious iron deposition was observed in the SN during early stages after damage, but significant iron deposition was detected at 8 weeks post-injury. Results demonstrate that the loss of TH-positive cells in the SN appeared simultaneously with increased DMT1 expression. Extensive iron deposition occurred at 8 weeks post injury, which could be regarded as an early time window of iron deposition.
文摘目的研究以专科护士为主导的“1+1+X”协同管理模式对稳定型心绞痛患者病情、自我管理能力的影响。方法方便选取2021年3月—2023年3月聊城市第二人民医院心血管内科收治的86例稳定型心绞痛患者为研究对象,根据不同护理方法分为常规组和协同管理组,各43例。常规组采用常规护理,协同管理组采用以专科护士为主导的“1+1+X”协同管理模式护理,两组均持续护理1个月。观察对比两组患者护理前后生活质量[健康调查简表(MOS Item Short Form Health Survey,SF-36)]、焦虑抑郁心理状况、自我管理能力[冠心病自我管理行为量表(Coronary Artery Disease Self-management Scale,CSMS)]。结果护理后,协同管理组SF-36量表评分高于常规组,差异有统计学意义(P<0.05);协同管理组焦虑自评量表(38.18±3.52)分、抑郁自评量表(39.21±3.24)分均优于常规组的(43.23±3.61)分、(45.03±3.69)分,差异有统计学意义(t=6.568、7.772,P均<0.05);协同管理组CSMS评分高于常规组,差异有统计学意义(P均<0.05)。结论以专科护士为主导的“1+1+X”协同管理模式应用于稳定型心绞痛患者护理可有效提升生活质量,改善不良心理状态,提高自我管理能力。
基金supported by the National Natural Science Foundation of China(11371303)Natural Science Foundation of Xinjiang(2012211A023)Science Foundation of Xinjiang University(XY110101)
文摘By studying the spectral properties of the underlying operator corresponding to the M/G/1 queueing model with optional second service we obtain that the time-dependent solution of the model strongly converges to its steady-state solution. We also show that the time-dependent queueing size at the departure point converges to the corresponding steady-state queueing size at the departure point.
基金supported by the Research Start Funds for Introducing High-level Talents of North China University of Water Resources and Electric Power
文摘This paper expresses the efficient outputs of decisionmaking unit（DMU） as the sum of ＂average outputs＂ forecasted by a GM（1,N） model and ＂increased outputs＂ which reflect the difficulty to realize efficient outputs.The increased outputs are solved by linear programming using data envelopment analysis efficiency theories,wherein a new sample is introduced whose inputs are equal to the budget in the issue No.n ＋ 1 and outputs are forecasted by the GM（1,N） model.The shortcoming in the existing methods that the forecasted efficient outputs may be less than the possible actual outputs according to developing trends of input-output rate in the periods of pre-n is overcome.The new prediction method provides decision-makers with more decisionmaking information,and the initial conditions are easy to be given.
