Function fitting for modeling seasonal normalized difference vegetation index time series and early forecasting of soybean yield

Forecasting crop yields based on remote sensing data is one of the most important tasks in agriculture.Soybean is the main crop in the Russian Far East.It is desirable to forecast soybean yield as early as possible while maintaining high accuracy.This study aimed to investigate seasonal time series of the normalized difference vegetation index(NDVI) to achieve early forecasting of soybean yield.This research used data from the Moderate Resolution Image Spectroradiometer(MODIS),an arable-land mask obtained from the VEGA-Science web service,and soybean yield data for 2008-2017 for the Jewish Autonomous Region(JAR) districts.Four approximating functions were fitted to model the NDVI time series:Gaussian,double logistic(DL),and quadratic and cubic polynomials.In the period from calendar weeks 22-42(end of May to mid-October),averaged over two districts,the model using the DL function showed the highest accuracy(mean absolute percentage error-4.0%,root mean square error(RMSE)-0.029,P <0.01).The yield forecast accuracy of prediction in the period of weeks 25-30 in JAR municipalities using the parameters of the Gaussian function was higher(P <0.05) than that using the other functions.The mean forecast error for the Gaussian function was 14.9% in week 25(RMSE was0.21 t ha) and 5.1%-12.9% in weeks 26-30(RMSE varied from 0.06 to 0.15 t ha) according to the2013-2017 data.In weeks 31-32,the error was 5.0%-5.4%(RMSE was 0.07 t ha) using the Gaussian parameters and 7.4%-7.7%(RMSE was 0.09-0.11 t ha) for the DL function.When the method was applied to municipal districts of other soy-producing regions of the Russian Far East.RMSE was0.14-0.32 t hain weeks 25-26 and did not exceed 0.20 t hain subsequent weeks.

Effectiveness of high intensity interval training on cardiorespiratory fitness and endothelial function in type 2 diabetes:A systematic review

BACKGROUND Type 2 diabetes mellitus(T2DM)is a chronic metabolic syndrome characterized by insulin resistance and hyperglycemia that may lead to endothelial dysfunction,reduced functional capacity and exercise intolerance.Regular aerobic exercise has been promoted as the most beneficial non-pharmacological treatment of cardiovascular diseases.High intensity interval training(HIIT)seems to be superior than moderate-intensity continuous training(MICT)in cardiovascular diseases by improving brachial artery flow-mediated dilation(FMD)and cardiorespiratory fitness to a greater extent.However,the beneficial effects of HIIT in patients with T2DM still remain under investigation and number of studies is limited.AIM To evaluate the effectiveness of high intensity interval training on cardiorespiratory fitness and endothelial function in patients with T2DM.METHODS We performed a search on PubMed,PEDro and CINAHL databases,selecting papers published between December 2012 and December 2022 and identified published randomized controlled trials(RCTs)in the English language that included community or outpatient exercise training programs in patients with T2DM.RCTs were assessed for methodological rigor and risk of bias via the Physiotherapy Evidence Database(PEDro).The primary outcome was peak VO_(2 ) and the secondary outcome was endothelial function assessed either by FMD or other indices of microcirculation.RESULTS Twelve studies were included in our systematic review.The 12 RCTs resulted in 661 participants in total.HIIT was performed in 310 patients(46.8%),MICT to 271 and the rest 80 belonged to the control group.Peak VO_(2 ) increased in 10 out of 12 studies after HIIT.Ten studies compared HIIT with other exercise regimens(MICT or strength endurance)and 4 of them demonstrated additional beneficial effects of HIIT over MICT or other exercise regimens.Moreover,4 studies explored the effects of HIIT on endothelial function and FMD in T2DM patients.In 2 of them,HIIT further improved endothelial function compared to MICT and/or the control group while in the rest 2 studies no differences between HIIT and MICT were observed.CONCLUSION Regular aerobic exercise training has beneficial effects on cardiorespiratory fitness and endothelial function in T2DM patients.HIIT may be superior by improving these parameters to a greater extent than MICT.

Fitness of Four-Parameter Beta Distribution Function for Forecasting Gold Reserve and Its Production Lifespan in Ghana

Ghana, renowned for its abundant gold reserves, plays a significant role in the global mining industry. Effective management and accurate forecasting of these reserves are vital for sustainable resource utilization and economic planning. Forecasting gold reserves and estimating their production lifespan are complex tasks that require robust statistical models capable of capturing the underlying dynamics of gold deposit accumulation and extraction. To this end, the four-parameter Beta distribution function emerges as a promising candidate due to its flexibility and ability to handle non-negative data. This research aims to investigate the fitness and applicability of the four-parameter Beta distribution function for forecasting Ghana’s gold reserves and estimating the production lifespan of this precious resource. The empirical paper relied mainly on quarterly secondary datasets on gold reserve between the years 2009 and 2022 secured from the Minerals Commission of Ghana, Accra. Several known statistical distributions including Beta, Weibull, Normal, Logistic and Gamma were explored with Maximum Likelihood Estimation (MLE) and evaluated using model selection criteria as AIC and BIC. Goodness of Fits were evaluated using Kolmogorov-Smirnov Test (K-S), Cramer-Von Mises Statistic and Anderson-Darling Statistic. Based on the analysis conducted, the four-parameter Beta distribution provided the best fit for gold reserve in Ghana. At a 99.9% confidence level and considering the current annual average gold production estimate of 3,700,031.248 to 4,302,647.888 ounces, the projected lifespan of gold production in Ghana extends to the year 1,953,765. This astounding estimate suggests that the country’s gold reserves are expected to sustain production for an extended period, providing a critical resource for economic development and supporting the mining industry well into the distant future.

Fitness of Four-Parameter Beta Distribution Function for Forecasting Gold Reserve and Its Production Lifespan in Ghana

Ghana, renowned for its abundant gold reserves, plays a significant role in the global mining industry. Effective management and accurate forecasting of these reserves are vital for sustainable resource utilization and economic planning. Forecasting gold reserves and estimating their production lifespan are complex tasks that require robust statistical models capable of capturing the underlying dynamics of gold deposit accumulation and extraction. To this end, the four-parameter Beta distribution function emerges as a promising candidate due to its flexibility and ability to handle non-negative data. This research aims to investigate the fitness and applicability of the four-parameter Beta distribution function for forecasting Ghana’s gold reserves and estimating the production lifespan of this precious resource. The empirical paper relied mainly on quarterly secondary datasets on gold reserve between the years 2009 and 2022 secured from the Minerals Commission of Ghana, Accra. Several known statistical distributions including Beta, Weibull, Normal, Logistic and Gamma were explored with Maximum Likelihood Estimation (MLE) and evaluated using model selection criteria as AIC and BIC. Goodness of Fits were evaluated using Kolmogorov-Smirnov Test (K-S), Cramer-Von Mises Statistic and Anderson-Darling Statistic. Based on the analysis conducted, the four-parameter Beta distribution provided the best fit for gold reserve in Ghana. At a 99.9% confidence level and considering the current annual average gold production estimate of 3,700,031.248 to 4,302,647.888 ounces, the projected lifespan of gold production in Ghana extends to the year 1,953,765. This astounding estimate suggests that the country’s gold reserves are expected to sustain production for an extended period, providing a critical resource for economic development and supporting the mining industry well into the distant future.

Large Scattered Data Fitting Based on Radial Basis Functions

Solving large radial basis function （RBF） interpolation problem with non-customized methods is computationally expensive and the matrices that occur are typically badly conditioned. In order to avoid these difficulties, we present a fitting based on radial basis functions satisfying side conditions by least squares, although compared with interpolation the method loses some accuracy, it reduces the computational cost largely. Since the fitting accuracy and the non-singularity of coefficient matrix in normal equation are relevant to the uniformity of chosen centers of the fitted RBE we present a choice method of uniform centers. Numerical results confirm the fitting efficiency.

The Application of Multiquadric Function Fitting to Borehole Strain Time Series Data Processing

Based on the existing continuous borehole strain observation,the multiquadric function fitting method was used to deal with time series data. The impact of difference kernel function parameters was discussed to obtain a valuable fitting result,from which the physical connotation of the original data and its possible applications were analyzed.Meanwhile,a brief comparison was made between the results of multiquadric function fitting and polynomial fitting.

函数系数自回归模型推广形式的Back-Fitting估计

文章针对时间序列中函数系数自回归模型给出其推广形式,借助向后拟合的思想介绍推广形式中函数系数部分和参数部分的估计,该方法可以得到模型中的常值系数估计量的精确表达式;并通过一个数值模拟表明所提出的估计方法具有可行性和稳定性。

Fitting集与根函数

群类理论是在有限可解群研究工作的基础上发展起来的,但近年来对有限群论的许多方面都起到越来越大的作用.Fitting类是重要群类之一.为了更深入地研究Fitting类,主要研究了Fitting集所具有的性质,用构造的方法证明了Fitting集与根函数之间可以建立一个一一对应的关系,证明了两个根函数的合成依然是根函数,并刻画了与该合成相关联的Fitting集,得到两个重要的定理.这对于Fitting类的研究具有重要意义.

Thermodynamic Fit Functions of the Two-Phase Fluid and Critical Exponents

Two-phase fluid properties such as entropy, internal energy, and heat capacity are given by thermodynamically defined fit functions. Each fit function is expressed as a temperature function in terms of a power series expansion about the critical point. The leading term with the critical exponent dominates the temperature variation between the critical and triple points. With β being introduced as the critical exponent for the difference between liquid and vapor densities, it is shown that the critical exponent of each fit function depends (if at all) on β. In particular, the critical exponent of the reciprocal heat capacity c﹣1 is α=1-2β and those of the entropy s and internal energy u are?2β, while that of the reciprocal isothermal compressibility?κ﹣1T is γ=1. It is thus found that in the case of the two-phase fluid the Rushbrooke equation conjectured α +?2β + γ=2 combines the scaling laws resulting from the two relations c=du/dT and?κT=dlnρ/dp. In the context with c, the second temperature derivatives of the chemical potential μ and vapor pressure p are investigated. As the critical point is approached, ﹣d2μ/dT2 diverges as c, while?d2p/dT2 converges to a finite limit. This is explicitly pointed out for the two-phase fluid, water (with β=0.3155). The positive and almost vanishing internal energy of the one-phase fluid at temperatures above and close to the critical point causes conditions for large long-wavelength density fluctuations, which are observed as critical opalescence. For negative values of the internal energy, i.e. the two-phase fluid below the critical point, there are only microscopic density fluctuations. Similar critical phenomena occur when cooling a dilute gas to its Bose-Einstein condensate.

Separating Overlapped Peaks of SF6 Decomposed Products Based on Iterative Curve-fitting Method

The SF6 decomposed products are very alike,so the peaks of the SF6 decomposed products are overlapped.It make us hard to quantitatively calculate.This paper introduced a method to separate the overlapped chromatogram peaks with iterative curve-fitting and Gauss function,and deduced the formula of the iterative curve-fitting;provided a method to calculate the initial value of the peaks intensity and width by iterative formula,and confirm the final peaks intensity and width to separate the overlapped signals.By the analysis of the real chromatogram data,it proved the validity of this method on the main components used in distinguishing the GIS internal defects.This method overcomes the influence of SF6 peak to the other thin concentration peaks,so it can be used in the study of the quantitative analysis of the decomposed products on different failures and different voltages.

Appropriateness of Reduced Modified Three-Parameter Weibull Distribution Function for Predicting Gold Production in Ghana

Forecasting mine production is pertinent to gold mining as it serves as production goals for investors. It is therefore important to identify the exact distribution that gold production as a response variable naturally follows. It is even more appropriate to have a model(s) with few predictor variables. This paper seeks to identify appropriate statistical distribution functions for fitting gold production in Ghana. The empirical paper relied mainly on quarterly secondary datasets on gold production between the years 2009 and 2022 secured from the Minerals Commission of Ghana, Accra. Several known statistical distributions including Weibull, Log-Normal, Generalized Extreme Value (GEV) were explored with Maximum Likelihood Estimation (MLE) and evaluated using model selection criteria as AIC, AICc and BIC. Goodness of Fits were evaluated using Kolmogorov-Smirnov Test (K-S), Cramer-Von Mises Statistic and Anderson-Darling Statistic. Based on the analysis conducted, the reduced modified 3-parameter Weibull distribution provided the best fit for gold production in Ghana. Though the reduced modified Weibull function is proposed, it is important however to recognize that other external factors can influence production levels. Also, the average quarterly fitted gold production is 1000334.8918 ± 75,327.080 (±7.5%) [i.e., 925,007.812 – 1,075,661.972]. This indicates that the average annually fitted gold production lies between 3700031.248 and 4302647.888 ounces at 99.9% confidence level. Therefore, the predicted gold production for the year 2022 is 3.7million ounces at 99.9% confidence level.

Appropriateness of Reduced Modified Three-Parameter Weibull Distribution Function for Predicting Gold Production in Ghana

Forecasting mine production is pertinent to gold mining as it serves as production goals for investors. It is therefore important to identify the exact distribution that gold production as a response variable naturally follows. It is even more appropriate to have a model(s) with few predictor variables. This paper seeks to identify appropriate statistical distribution functions for fitting gold production in Ghana. The empirical paper relied mainly on quarterly secondary datasets on gold production between the years 2009 and 2022 secured from the Minerals Commission of Ghana, Accra. Several known statistical distributions including Weibull, Log-Normal, Generalized Extreme Value (GEV) were explored with Maximum Likelihood Estimation (MLE) and evaluated using model selection criteria as AIC, AICc and BIC. Goodness of Fits were evaluated using Kolmogorov-Smirnov Test (K-S), Cramer-Von Mises Statistic and Anderson-Darling Statistic. Based on the analysis conducted, the reduced modified 3-parameter Weibull distribution provided the best fit for gold production in Ghana. Though the reduced modified Weibull function is proposed, it is important however to recognize that other external factors can influence production levels. Also, the average quarterly fitted gold production is 1000334.8918 ± 75,327.080 (±7.5%) [i.e., 925,007.812 – 1,075,661.972]. This indicates that the average annually fitted gold production lies between 3700031.248 and 4302647.888 ounces at 99.9% confidence level. Therefore, the predicted gold production for the year 2022 is 3.7million ounces at 99.9% confidence level.

NON-STATIONARY SIGNAL DENOISING USING TIME-FREQUENCY CURVE SURFACE FITTING

Based on the theory of adaptive time-frequency decomposition and Time-Frequency Dis- tribution Series (TFDS), this paper presents a novel denoising method for non-stationary signal. Ac- cording to the input signal features, an appropriate kind of elementary functions with great concen- tration in the Time-Frequency (TF) plane is selected. Then the input signal is decomposed into a linear combination of these functions. The elementary function parameters are determined by using ele- mentary function TF curve surface to fit the input signal’s TFDS. The process of curved surface fitting corresponds to the signal structure matching process. The input signal’s dominating component whose structure has the resemblance with elementary function is fitted out firstly. Repeating the fitting process, the residue can be regarded as noises, which are greatly different from the function. Selecting the functions fitted out initially for reconstruction, the denoised signal is obtained. The performance of the proposed method is assessed by means of several tests on an emulated signal and a gearbox vi- brating signal.

新型冠状病毒感染后潜水员适潜性评估

新型冠状病毒感染(COVID-19)对全身几乎所有器官都会产生影响,其中最主要的受累器官为肺和心脏。随着COVID-19康复患者数量不断增加,越来越多的证据表明,因COVID-19住院治疗获得康复的患者中有相当大比例的人群存在后遗症,主要表现为呼吸系统和心血管系统的症状。对于潜水员,COVID-19后的运动耐受、心肺功能的恢复对其适潜性具有重要影响。一些组织和机构发布了潜水员COVID-19后的适潜性评估指南。本文对COVID-19后的呼吸和心血管系统后遗症及相关的适潜性评估方案进行简要介绍,并基于已有的相关要求和我国实际,初步提出我国潜水员COVID-19后的适潜性评估要求。

改进蚁群算法的送餐机器人路径规划

蚁群算法拥有良好的全局性、自组织性、鲁棒性,但传统蚁群算法存在许多不足之处。为此,针对算法在路径规划问题中的缺陷,在传统蚁群算法的状态转移公式中,引入目标点距离因素和引导素,加快算法收敛性和改善局部最优缺陷。在带时间窗的车辆路径问题(vehicle routing problem with time windows,VRPTW)上,融合蚁群算法和遗传算法,并将顾客时间窗宽度以及机器人等待时间加入蚁群算法状态转移公式中,以及将蚁群算法的解作为遗传算法的初始种群,提高遗传算法的初始解质量,然后进行编码,设置违反时间窗约束和载重量的惩罚函数和适应度函数,在传统遗传算法的交叉、变异操作后加入了破坏-修复基因的操作来优化每一代新解的质量,在Solomon Benchmark算例上进行仿真,对比算法改进前后的最优解,验证算法可行性。最后在餐厅送餐问题中把带有障碍物的仿真环境路径规划问题和VRPTW问题结合,使用改进后的算法解决餐厅环境下送餐机器人对顾客服务配送问题。

基于功能性体适能指标构建老年慢性阻塞性肺疾病患者的居家康复护理方案

目的 基于功能性体适能指标构建老年慢性阻塞性肺疾病患者的居家康复护理方案。方法 通过文献检索、病例回顾,以及结合老年慢性阻塞性肺疾病患者日常生活需要、疾病特点、体适能等核心指标,构建老年慢性阻塞性肺疾病患者居家康复护理方案初稿。编制专家函询问卷,并通过小组讨论,遴选出12名呼吸、康复相关专家,进行2轮专家函询。结果 2轮专家函询问卷回收率均为83.3%。专家权威系数为0.90。居家康复护理方案共有4个一级指标、11个二级指标和33个三级指标。结论 以功能性体适能指标构建的老年慢性阻塞性肺疾病患者居家康复护理方案具有可实施性、科学性、创新性,可为临床应用提供理论依据。

基于不确定性的多尺度暴雨强度和外江洪水位联合分布研究

城市洪涝治理方案以及排涝设施规模建设都与城市暴雨强度和外江洪水位息息相关,因此需要对暴雨强度与外江洪水位联合概率分布进行深入研究。以武汉市为例,采用Copula函数建立小时尺度城市暴雨强度和外江洪水位的联合分布,使用极大似然估计值(Max-Likelihood)、模型选择准则、RMSE和NSE拟合优度来评估不同Copula模型的性能,利用局部优化(Local optimization,LO)和马尔科夫链蒙特卡洛(Markov chain Monte Carlo,MCMC)方法来分析Copula模型的不确定性。结果表明:暴雨强度和外江洪水位两要素存在明显的正相关,1 h最大连续降水量和最大日水位相关性最高,最优联合分布函数为Gumbel Copula函数;模型不确定性分析表明MCMC模拟的最优参数与理论参数值基本吻合,效果明显优于局部优化算法,且模型不确定性结果与拟合优度评价结果一致,进一步验证了联合分布函数参数的有效性。相同频率情况下,单变量值低于两变量联合频率对应的暴雨强度和外江洪水位值,高于两变量同现频率对应的暴雨强度和外江洪水位值;两变量同现重现期高于单变量设计重现期,而联合重现期低于单变量设计重现期。同频率下的暴雨强度与水位的组合风险率都远远低于单变量情况下的频率值,50 a以上排涝风险率大于设计暴雨重现期,但最大不超过联合风险率。

基于正弦函数拟合的高动态捷联惯导姿态更新算法

为提高捷联惯导在高动态条件下的姿态解算精度,基于等效旋转矢量泰勒级数展开法,提出一种基于正弦函数拟合的高动态捷联惯导姿态更新算法。以正弦函数拟合载体运动角速度,考虑Bortz方程高阶项的影响,对陀螺角增量表示的旋转矢量进行泰勒六阶展开,对比旋转矢量不同形式表达式求得误差补偿系数。在MATLAB平台上,以圆锥运动与大角速率转动并存环境作为仿真条件,对所提算法与传统算法进行对比仿真分析。仿真结果表明,在小半锥角低频圆锥运动伴随高速角速率转动情况下,所提算法性能较好,当半锥角为0.5°、角频率为2.26πrad/s、常值角速率为5.30 rad/s、姿态解算周期为0.02 s时,所提正弦函数拟合三子样旋转矢量算法与传统扩展形式频率级数/显示频率三子样圆锥算法相比误差降低了2个数量级。

高斯函数拟合的地磁日变规律分析及改正

地磁数据的采集精度直接影响着地磁匹配定位的准确度,地磁日变改正是获取高精度地磁数据的重要前提.在远海以及一些远离台站有效范围的偏远区域设立日变站相对困难,而且保证日变站持续稳定的工作对日变站的设立提出了更高要求.日变改正步骤复杂而繁琐,大多通过多台站联合改正或监测相应时刻日变站的变化实现,对于区域地磁数据采集过程的日变改正研究相对较少.针对这些问题,文章顾及地磁静日变化存在一定周期性的特点,基于高斯拟合函数对单点位多个太阳日下的地磁场变化规律进行分析,并对区域多点的地磁场数据进行日变拟合及改正分析.试验结果表明:在一定区域范围内高斯函数拟合得到的点位磁场的静日变化能够满足地磁日变改正精度,拟合误差在几个nT以内,中误差也不超过10 nT;区域点位实验中,将高斯函数拟合获得的日变改正值与常规方法获得的日变改正值进行对比,其中82.3%的点位日变改正值的差值在±5 nT以内.因此,基于高斯函数拟合的地磁日变改正分析能够根据观测时间获得相应区域的日变改正估值,实现日变改正,获得高精度地磁数据,为地磁匹配定位提供了基础.

基于van Genuchten模型土壤水分特征曲线的vanfit和MATLAB软件模拟研究

研究了土壤水分特征曲线对探讨土壤水分运动机理及溶质运移动力学机制具有重要科学意义。由于测定土壤水分特征曲线的长历时性和时间限制,在从相关参考文献中提取土壤水分特征曲线测定数据的基础上,建立土壤水分特征曲线的资料库,采用van Genuchten模型对土壤水分特征曲线进行描述,分别应用vanfit软件和MATLAB软件下的lsqcurvefit函数2种方法对土壤进行van Genuchten模型下的4个参数拟合分析。结果表明,2个程序拟合结果大体相近且优良,均方差较小,拟合曲线大致相同,且土壤质地不同,其土壤水分特征曲线差别较大。