Prediction and stratification for the surgical adverse events after minimally invasive esophagectomy:A two-center retrospective study

BACKGROUND Minimally invasive esophagectomy(MIE)is a widely accepted treatment for esophageal cancer,yet it is associated with a significant risk of surgical adverse events(SAEs),which can compromise patient recovery and long-term survival.Accurate preoperative identification of high-risk patients is critical for improving outcomes.AIM To establish and validate a risk prediction and stratification model for the risk of SAEs in patients with MIE.METHODS This retrospective study included 747 patients who underwent MIE at two centers from January 2019 to February 2024.Patients were separated into a train set(n=549)and a validation set(n=198).After screening by least absolute shrinkage and selection operator regression,multivariate logistic regression analyzed clinical and intraoperative variables to identify independent risk factors for SAEs.A risk stratification model was constructed and validated to predict the probability of SAEs.RESULTS SAEs occurred in 10.2%of patients in train set and 13.6%in the validation set.Patients with SAE had significantly higher complication rate and a longer hospital stay after surgery.The key independent risk factors identified included chronic obstructive pulmonary disease,a history of alcohol consumption,low forced expiratory volume in the first second,and low albumin levels.The stratification model has excellent prediction accuracy,with an area under the curve of 0.889 for the training set and an area under the curve of 0.793 for the validation set.CONCLUSION The developed risk stratification model effectively predicts the risk of SAEs in patients undergoing MIE,facilitating targeted preoperative interventions and improving perioperative management.

基于改进Event模型的通用航空器碰撞风险分析

随着通用航空的发展,空中交通流量将持续扩大,航空器碰撞风险增加。对Event模型进行改进,将拼接四棱锥碰撞盒代替原长方体碰撞盒,曲面间隔层代替平面间隔层,建立通用航空器碰撞风险模型。最后将塞斯纳172及运5B通用航空器作为实例对所建模型进行验证,结果表明,在两组均采用广义帕累托分布的条件下,改进后Event模型碰撞风险值分别为改进前的31.65%、14.98%,碰撞风险值较改进前大大减少,结果精度更高,能更好地评估交叉航路碰撞风险。

Event-driven process execution model for process virtual machine

Current orchestration and choreography process engines only serve with dedicate process languages.To solve these problems,an Event-driven Process Execution Model(EPEM) was developed.Formalization and mapping principles of the model were presented to guarantee the correctness and efficiency for process transformation.As a case study,the EPEM descriptions of Web Services Business Process Execution Language(WS-BPEL) were represented and a Process Virtual Machine(PVM)-OncePVM was implemented in compliance with the EPEM.

Optimal switching policy for performance enhancement of distributed parameter systems based on event-driven control

This paper aims to improve the performance of a class of distributed parameter systems for the optimal switching of actuators and controllers based on event-driven control. It is assumed that in the available multiple actuators, only one actuator can receive the control signal and be activated over an unfixed time interval, and the other actuators keep dormant. After incorporating a state observer into the event generator, the event-driven control loop and the minimum inter-event time are ultimately bounded. Based on the event-driven state feedback control, the time intervals of unfixed length can be obtained. The optimal switching policy is based on finite horizon linear quadratic optimal control at the beginning of each time subinterval. A simulation example demonstrate the effectiveness of the proposed policy.

Smart home architecture based on event-driven DPWS～+

With the advances of electronic information technology and computer network, especially the embedded technology, smart home is no more just a vision but being practical. The interoperability of heterogeneous devices and flexibility of devices＇ usage are two key problems that challenge the implementation of smart home. To deal with these two issues, this paper proposes an event-driven service oriented architecture using device profile for web services （DPWS）. DPWS inherits the advantages of the traditional web services in achieving interoperability without dependence on platform, while improving service discovery and security as well as being optimized for deploying on resource constrained devices. By providing a visual interface for describing a service workflow （SW）, the user can easily customize the actions of devices by services composition. Devices automatically cooperate without user＇s intervention to complete required business logic. This is achieved by fully exploiting the eventing capabilities on DPWS enabled home devices. Finally, a home theater scenario is given to illustrate the event driven mechanism for the SW in the proposed smart home framework.

Decentralized Dynamic Event-Triggered Communication and Active Suspension Control of In-Wheel Motor Driven Electric Vehicles with Dynamic Damping

This paper addresses the co-design problem of decentralized dynamic event-triggered communication and active suspension control for an in-wheel motor driven electric vehicle equipped with a dynamic damper. The main objective is to simultaneously improve the desired suspension performance caused by various road disturbances and alleviate the network resource utilization for the concerned in-vehicle networked suspension system. First, a T-S fuzzy active suspension model of an electric vehicle under dynamic damping is established. Second,a novel decentralized dynamic event-triggered communication mechanism is developed to regulate each sensor's data transmissions such that sampled data packets on each sensor are scheduled in an independent manner. In contrast to the traditional static triggering mechanisms, a key feature of the proposed mechanism is that the threshold parameter in the event trigger is adjusted adaptively over time to reduce the network resources occupancy. Third, co-design criteria for the desired event-triggered fuzzy controller and dynamic triggering mechanisms are derived. Finally, comprehensive comparative simulation studies of a 3-degrees-of-freedom quarter suspension model are provided under both bump road disturbance and ISO-2631 classified random road disturbance to validate the effectiveness of the proposed co-design approach. It is shown that ride comfort can be greatly improved in either road disturbance case and the suspension deflection, dynamic tyre load and actuator control input are all kept below the prescribed maximum allowable limits, while simultaneously maintaining desirable communication efficiency.

An Approach to Event-Driven Software Testing

In this paper, the testing technology of event-driven software is focused. It is first analyzed the difference between event-driven software and the traditional procedure-oriented software, and based on the above analysis, the mechanism of event-driven and the effect of introduction of event-driven mechanism on software testing are unveiled. Then based on the characteristic of the event-driven software, the traditional software testing method is improved, and testing policy of event based test is presented in this paper.Moreover the event coverage criteria are defined and given here. At the same time the event executing rule are further uncovered, such as ordinal event, non-ordinal event, predecessor event and concurrent event etc., and also the methods of testing according to event executing rule are studied.

Event-driven timing system based on MRF cPCI hardware for HLS-II

Hefei Light Source(HLS)-II is a vacuum ultraviole(VUV) synchrotron light source. A major upgrade of the light source was finished at the end of 2014. The timing system was rebuilt using compact peripheral component interconnect(cPCI) event-driven hardware to meet synchronization requirements of the machine. In the new system, the c PCI event-driven products manufactured by the micro-research finland(MRF) Oy are employed to achieve about 100 output signals with different interfaces. Device supports and drivers developed for common Experimental Physics and Industrial Control System(EPICS) records are used to access the registers on the timing modules. Five c PCI-bus input/output controllers(IOCs) distributed in different areas of the light source host timing modules for various subsystems. The delay resolution of this system is 9.8 ns for most channels and 9 ps for the channels used for triggering the electron gun and the injection kickers. The measured rms jitter of the output signal is less than 27 ps. Using the bucket chooser, this system enables the HLS-II to fill the storage ring with any designated bunch pattern. Benefitting from this upgrade, brightness and performance of the light source are significantly improved.

Internet-based event synchronization communication driven telerobotics

Based on QoS (quality of service) parameters: time delay, jitter, bandwidth and package loss. As time delay in the Internet is variable, it is hard to compensate it by traditional methods. Event synchronization communication driven method is proposed to overcome the negative effects induced by time delay. This method is a non-time based method and it can get rid of the effects of time in the control loop of telerobotics. Stability, transparency and synchronization can be maintained in it by event-driven method. Multimodal enhanced telerobotics is put forward with its feedback including force, video, audio and temperature etc. The use of multimodal feedback improves the efficiency and safety of the whole system. Synchronization in multimodal feedback is hard to ensure and event-driven method is also good for it. Experiments on an Internet-based shaft-hole assemblage system show good results by using event synchronization communication driven method and UDP protocol.

Projecting Spring Consecutive Rainfall Events in the Three Gorges Reservoir Based on Triple-Nested Dynamical Downscaling

Spring consecutive rainfall events(CREs) are key triggers of geological hazards in the Three Gorges Reservoir area(TGR), China. However, previous projections of CREs based on the direct outputs of global climate models(GCMs) are subject to considerable uncertainties, largely caused by their coarse resolution. This study applies a triple-nested WRF(Weather Research and Forecasting) model dynamical downscaling, driven by a GCM, MIROC6(Model for Interdisciplinary Research on Climate, version 6), to improve the historical simulation and reduce the uncertainties in the future projection of CREs in the TGR. Results indicate that WRF has better performances in reproducing the observed rainfall in terms of the daily probability distribution, monthly evolution and duration of rainfall events, demonstrating the ability of WRF in simulating CREs. Thus, the triple-nested WRF is applied to project the future changes of CREs under the middle-of-the-road and fossil-fueled development scenarios. It is indicated that light and moderate rainfall and the duration of continuous rainfall spells will decrease in the TGR, leading to a decrease in the frequency of CREs. Meanwhile, the duration, rainfall amount, and intensity of CREs is projected to regional increase in the central-west TGR. These results are inconsistent with the raw projection of MIROC6. Observational diagnosis implies that CREs are mainly contributed by the vertical moisture advection. Such a synoptic contribution is captured well by WRF, which is not the case in MIROC6,indicating larger uncertainties in the CREs projected by MIROC6.

Prediabetes: An overlooked risk factor for major adverse cardiac and cerebrovascular events in atrial fibrillation patients

BACKGROUND Prediabetes is a well-established risk factor for major adverse cardiac and cerebrovascular events(MACCE).However,the relationship between prediabetes and MACCE in atrial fibrillation(AF)patients has not been extensively studied.Therefore,this study aimed to establish a link between prediabetes and MACCE in AF patients.AIM To investigate a link between prediabetes and MACCE in AF patients.METHODS We used the National Inpatient Sample(2019)and relevant ICD-10 CM codes to identify hospitalizations with AF and categorized them into groups with and without prediabetes,excluding diabetics.The primary outcome was MACCE(all-cause inpatient mortality,cardiac arrest including ventricular fibrillation,and stroke)in AF-related hospitalizations.RESULTS Of the 2965875 AF-related hospitalizations for MACCE,47505(1.6%)were among patients with prediabetes.The prediabetes cohort was relatively younger(median 75 vs 78 years),and often consisted of males(56.3%vs 51.4%),blacks(9.8%vs 7.9%),Hispanics(7.3%vs 4.3%),and Asians(4.7%vs 1.6%)than the non-prediabetic cohort(P<0.001).The prediabetes group had significantly higher rates of hypertension,hyperlipidemia,smoking,obesity,drug abuse,prior myocardial infarction,peripheral vascular disease,and hyperthyroidism(all P<0.05).The prediabetes cohort was often discharged routinely(51.1%vs 41.1%),but more frequently required home health care(23.6%vs 21.0%)and had higher costs.After adjusting for baseline characteristics or comorbidities,the prediabetes cohort with AF admissions showed a higher rate and significantly higher odds of MACCE compared to the non-prediabetic cohort[18.6%vs 14.7%,odds ratio(OR)1.34,95%confidence interval 1.26-1.42,P<0.001].On subgroup analyses,males had a stronger association(aOR 1.43)compared to females(aOR 1.22),whereas on the race-wise comparison,Hispanics(aOR 1.43)and Asians(aOR 1.36)had a stronger association with MACCE with prediabetes vs whites(aOR 1.33)and blacks(aOR 1.21).CONCLUSION This population-based study found a significant association between prediabetes and MACCE in AF patients.Therefore,there is a need for further research to actively screen and manage prediabetes in AF to prevent MACCE.

Anthropogenic Influence on Decadal Changes in Concurrent Hot and Dry Events over China around the Mid-1990s

The frequency and duration of observed concurrent hot and dry events(HDEs) over China during the growing season(April–September) exhibit significant decadal changes across the mid-1990s. These changes are characterized by increases in HDE frequency and duration over most of China, with relatively large increases over southeastern China(SEC), northern China(NC), and northeastern China(NEC). The frequency of HDEs averaged over China in the present day(PD,1994–2011) is double that in the early period(EP, 1964–81);the duration of HDEs increases by 60%. Climate experiments with the Met Office Unified Model(MetUM-GOML2) are used to estimate the contributions of anthropogenic forcing to HDE decadal changes over China. Anthropogenic forcing changes can explain 60%–70% of the observed decadal changes,suggesting an important anthropogenic influence on HDE changes over China across the mid-1990s. Single-forcing experiments indicate that the increase in greenhouse gas(GHG) concentrations dominates the simulated decadal changes,increasing the frequency and duration of HDEs throughout China. The change in anthropogenic aerosol(AA) emissions significantly decreases the frequency and duration of HDEs over SEC and NC, but the magnitude of the decrease is much smaller than the increase induced by GHGs. The changes in HDEs in response to anthropogenic forcing are mainly due to the response of climatological mean surface air temperatures. The contributions from changes in variability and changes in climatological mean soil moisture and evapotranspiration are relatively small. The physical processes associated with the response of HDEs to GHG and AA changes are also revealed.

Increased retinal venule diameter as a prognostic indicator for recurrent cerebrovascular events:a prospective observational study

Microvasculature of the retina is considered an alternative marker of cerebral vascular risk in healthy populations.However,the ability of retinal vasculature changes,specifically focusing on retinal vessel diameter,to predict the recurrence of cerebrovascular events in patients with ischemic stroke has not been determined comprehensively.While previous studies have shown a link between retinal vessel diameter and recurrent cerebrovascular events,they have not incorporated this information into a predictive model.Therefore,this study aimed to investigate the relationship between retinal vessel diameter and subsequent cerebrovascular events in patients with acute ischemic stroke.Additionally,we sought to establish a predictive model by combining retinal veessel diameter with traditional risk factors.We performed a prospective observational study of 141 patients with acute ischemic stroke who were admitted to the First Affiliated Hospital of Jinan University.All of these patients underwent digital retinal imaging within 72 hours of admission and were followed up for 3 years.We found that,after adjusting for related risk factors,patients with acute ischemic stroke with mean arteriolar diameter within 0.5-1.0 disc diameters of the disc margin(MAD_(0.5-1.0DD))of≥74.14μm and mean venular diameter within 0.5-1.0 disc diameters of the disc margin(MVD_(0.5-1.0DD))of≥83.91μm tended to experience recurrent cerebrovascular events.We established three multivariate Cox proportional hazard regression models:model 1 included traditional risk factors,model 2 added MAD_(0.5-1.0DD)to model 1,and model 3 added MVD0.5-1.0DD to model 1.Model 3 had the greatest potential to predict subsequent cerebrovascular events,followed by model 2,and finally model 1.These findings indicate that combining retinal venular or arteriolar diameter with traditional risk factors could improve the prediction of recurrent cerebrovascular events in patients with acute ischemic stroke,and that retinal imaging could be a useful and non-invasive method for identifying high-risk patients who require closer monitoring and more aggressive management.

Impact of body mass index on adverse kidney events in diabetes mellitus patients: A systematic-review and meta-analysis

BACKGROUND The incidence of chronic kidney disease among patients with diabetes mellitus(DM)remains a global concern.Long-term obesity is known to possibly influence the development of type 2 diabetes mellitus.However,no previous meta-analysis has assessed the effects of body mass index(BMI)on adverse kidney events in patients with DM.AIM To determine the impact of BMI on adverse kidney events in patients with DM.METHODS A systematic literature search was performed on the PubMed,ISI Web of Science,Scopus,Ovid,Google Scholar,EMBASE,and BMJ databases.We included trials with the following characteristics:(1)Type of study:Prospective,retrospective,randomized,and non-randomized in design;(2)participants:Restricted to patients with DM aged≥18 years;(3)intervention:No intervention;and(4)kidney adverse events:Onset of diabetic kidney disease[estimated glomerular filtration rate(eGFR)of<60 mL/min/1.73 m2 and/or microalbuminuria value of≥30 mg/g Cr],serum creatinine increase of more than double the baseline or end-stage renal disease(eGFR<15 mL/min/1.73 m2 or dialysis),or death.RESULTS Overall,11 studies involving 801 patients with DM were included.High BMI(≥25 kg/m2)was significantly associated with higher blood pressure(BP)[systolic BP by 0.20,95%confidence interval(CI):0.15–0.25,P<0.00001;diastolic BP by 0.21 mmHg,95%CI:0.04–0.37,P=0.010],serum albumin,triglycerides[standard mean difference(SMD)=0.35,95%CI:0.29–0.41,P<0.00001],low-density lipoprotein(SMD=0.12,95%CI:0.04–0.20,P=0.030),and lower high-density lipoprotein(SMD=–0.36,95%CI:–0.51 to–0.21,P<0.00001)in patients with DM compared with those with low BMIs(<25 kg/m2).Our analysis showed that high BMI was associated with a higher risk ratio of adverse kidney events than low BMI(RR:1.22,95%CI:1.01–1.43,P=0.036).CONCLUSION The present analysis suggested that high BMI was a risk factor for adverse kidney events in patients with DM.

Sex and racial disparities in non-alcoholic fatty liver disease-related cardiovascular events: National inpatient sample analysis (2019)

BACKGROUND Non-alcoholic fatty liver disease(NAFLD)increases cardiovascular disease(CVD)risk irrespective of other risk factors.However,large-scale cardiovascular sex and race differences are poorly understood.AIM To investigate the relationship between NAFLD and major cardiovascular and cerebrovascular events(MACCE)in subgroups using a nationally representative United States inpatient sample.METHODS We examined National Inpatient Sample(2019)to identify adult hospitalizations with NAFLD by age,sex,and race using ICD-10-CM codes.Clinical and demographic characteristics,comorbidities,and MACCE-related mortality,acute myocardial infarction(AMI),cardiac arrest,and stroke were compared in NAFLD cohorts by sex and race.Multivariable regression analyses were adjusted for sociodemographic characteristics,hospitalization features,and comorbidities.RESULTS We examined 409130 hospitalizations[median 55(IQR 43-66)years]with NFALD.NAFLD was more common in females(1.2%),Hispanics(2%),and Native Americans(1.9%)than whites.Females often reported non-elective admissions,Medicare enrolment,the median age of 55(IQR 42-67),and poor income.Females had higher obesity and uncomplicated diabetes but lower hypertension,hyperlipidemia,and complicated diabetes than males.Hispanics had a median age of 48(IQR 37-60),were Medicaid enrollees,and had non-elective admissions.Hispanics had greater diabetes and obesity rates than whites but lower hypertension and hyperlipidemia.MACCE,all-cause mortality,AMI,cardiac arrest,and stroke were all greater in elderly individuals(P<0.001).MACCE,AMI,and cardiac arrest were more common in men(P<0.001).Native Americans(aOR 1.64)and Asian Pacific Islanders(aOR 1.18)had higher all-cause death risks than whites.CONCLUSION Increasing age and male sex link NAFLD with adverse MACCE outcomes;Native Americans and Asian Pacific Islanders face higher mortality,highlighting a need for tailored interventions and care.

Predicting major adverse cardiovascular events after orthotopic liver transplantation using a supervised machine learning model:A cohort study

BACKGROUND Liver transplant(LT)patients have become older and sicker.The rate of post-LT major adverse cardiovascular events(MACE)has increased,and this in turn raises 30-d post-LT mortality.Noninvasive cardiac stress testing loses accuracy when applied to pre-LT cirrhotic patients.AIM To assess the feasibility and accuracy of a machine learning model used to predict post-LT MACE in a regional cohort.METHODS This retrospective cohort study involved 575 LT patients from a Southern Brazilian academic center.We developed a predictive model for post-LT MACE(defined as a composite outcome of stroke,new-onset heart failure,severe arrhythmia,and myocardial infarction)using the extreme gradient boosting(XGBoost)machine learning model.We addressed missing data(below 20%)for relevant variables using the k-nearest neighbor imputation method,calculating the mean from the ten nearest neighbors for each case.The modeling dataset included 83 features,encompassing patient and laboratory data,cirrhosis complications,and pre-LT cardiac assessments.Model performance was assessed using the area under the receiver operating characteristic curve(AUROC).We also employed Shapley additive explanations(SHAP)to interpret feature impacts.The dataset was split into training(75%)and testing(25%)sets.Calibration was evaluated using the Brier score.We followed Transparent Reporting of a Multivariable Prediction Model for Individual Prognosis or Diagnosis guidelines for reporting.Scikit-learn and SHAP in Python 3 were used for all analyses.The supplementary material includes code for model development and a user-friendly online MACE prediction calculator.RESULTS Of the 537 included patients,23(4.46%)developed in-hospital MACE,with a mean age at transplantation of 52.9 years.The majority,66.1%,were male.The XGBoost model achieved an impressive AUROC of 0.89 during the training stage.This model exhibited accuracy,precision,recall,and F1-score values of 0.84,0.85,0.80,and 0.79,respectively.Calibration,as assessed by the Brier score,indicated excellent model calibration with a score of 0.07.Furthermore,SHAP values highlighted the significance of certain variables in predicting postoperative MACE,with negative noninvasive cardiac stress testing,use of nonselective beta-blockers,direct bilirubin levels,blood type O,and dynamic alterations on myocardial perfusion scintigraphy being the most influential factors at the cohort-wide level.These results highlight the predictive capability of our XGBoost model in assessing the risk of post-LT MACE,making it a valuable tool for clinical practice.CONCLUSION Our study successfully assessed the feasibility and accuracy of the XGBoost machine learning model in predicting post-LT MACE,using both cardiovascular and hepatic variables.The model demonstrated impressive performance,aligning with literature findings,and exhibited excellent calibration.Notably,our cautious approach to prevent overfitting and data leakage suggests the stability of results when applied to prospective data,reinforcing the model’s value as a reliable tool for predicting post-LT MACE in clinical practice.

A Novel Simulation Method for Power Electronics: Discrete State Event Driven Method

In the analysis of power electronics system,it is necessary to simulate ordinary differential equations(ODEs)with discontinuities and stiffness.However,there are many difficulties in using traditional discrete-time algorithms to solve such equations.Kofman and others presented the quantized state systems(QSS)algorithm in the discrete event system specification(DEVS)formalism.The discretization is applied to the state variables instead of time range in QSS.QSS is efficient to solve ODEs,but it is difficulty to be used when simulating actual power electronics systems with controller’s and other events.Based on the idea of this numerical algorithm and discrete event,a Discrete State Event Driven(DSED)simulation method is presented in this paper,which is fit for simulation of power electronics system.The method is developed to deal with non-linearity,stiffness and multi-time scale of power electronics systems.The DSED simulation method includes event definition,module seperation and modeling,event-driven mechanisms,numerical computation based on QSS,and some other operations.Simulation results verified the effectiveness and validity of the proposed method.

EVENT联合思政教学模式在提升护理实习生人文关怀能力中的应用研究

目的探讨EVENT联合思政教学模式在提升护理实习生人文关怀能力中的应用效果。方法随机抽取2022年7月至2023年7月在甲状腺疝小儿外科进行实习的护生为研究对象,对照组采用常规教学模式,实验组在对照组的基础上采用EVENT联合思政教学模式。比较两组理论成绩、自主学习能力、工作投入度及人文关怀能力。结果教学后,实验组理论成绩、自主学习能力、工作投入度及人文关怀能力均高于对照组(P<0.05)。结论EVENT联合思政教学模式能提升护理实习生理论成绩、自主学习能力、工作投入度及人文关怀能力,值得在教学中推广应用。

A Time Series Short-Term Prediction Method Based on Multi-Granularity Event Matching and Alignment

Accurate forecasting of time series is crucial across various domains.Many prediction tasks rely on effectively segmenting,matching,and time series data alignment.For instance,regardless of time series with the same granularity,segmenting them into different granularity events can effectively mitigate the impact of varying time scales on prediction accuracy.However,these events of varying granularity frequently intersect with each other,which may possess unequal durations.Even minor differences can result in significant errors when matching time series with future trends.Besides,directly using matched events but unaligned events as state vectors in machine learning-based prediction models can lead to insufficient prediction accuracy.Therefore,this paper proposes a short-term forecasting method for time series based on a multi-granularity event,MGE-SP(multi-granularity event-based short-termprediction).First,amethodological framework for MGE-SP established guides the implementation steps.The framework consists of three key steps,including multi-granularity event matching based on the LTF(latest time first)strategy,multi-granularity event alignment using a piecewise aggregate approximation based on the compression ratio,and a short-term prediction model based on XGBoost.The data from a nationwide online car-hailing service in China ensures the method’s reliability.The average RMSE(root mean square error)and MAE(mean absolute error)of the proposed method are 3.204 and 2.360,lower than the respective values of 4.056 and 3.101 obtained using theARIMA(autoregressive integratedmoving average)method,as well as the values of 4.278 and 2.994 obtained using k-means-SVR(support vector regression)method.The other experiment is conducted on stock data froma public data set.The proposed method achieved an average RMSE and MAE of 0.836 and 0.696,lower than the respective values of 1.019 and 0.844 obtained using the ARIMA method,as well as the values of 1.350 and 1.172 obtained using the k-means-SVR method.