A real-time performance improvement method for composite time scale

The composite time scale(CTS)provides a stable,accurate,and reliable time scale for modern society.The improvement of CTS’s real-time performance will improve its stability,which strengths related applications’performance.Aiming at this goal,a method achieved by determining the optimal calculation interval and accelerating adjustment stage is proposed in this paper.The determinants of the CTS’s calculation interval(characteristics of the clock ensemble,the measurement noise,the time and frequency synchronization system’s noise and the auxiliary output generator noise floor)are studied and the optimal calculation interval is obtained.We also investigate the effect of ensemble algorithm’s initial parameters on the CTS’s adjustment stage.A strategy to get the reasonable initial parameters of ensemble algorithm is designed.The results show that the adjustment stage can be finished rapidly or even can be shorten to zero with reasonable initial parameters.On this basis,we experimentally generate a distributed CTS with a calculation interval of 500 s and its stability outperforms those of the member clocks when the averaging time is longer than1700 s.The experimental result proves that the CTS’s real-time performance is significantly improved.

Flow and sound fields of scaled high-speed trains with different coach numbers running in long tunnel

Segregated incompressible large eddy simulation and acoustic perturbation equations were used to obtain the flow field and sound field of 1:25 scale trains with three,six and eight coaches in a long tunnel,and the aerodynamic results were verified by wind tunnel test with the same scale two-coach train model.Time-averaged drag coefficients of the head coach of three trains are similar,but at the tail coach of the multi-group trains it is much larger than that of the three-coach train.The eight-coach train presents the largest increment from the head coach to the tail coach in the standard deviation(STD)of aerodynamic force coefficients:0.0110 for drag coefficient(Cd),0.0198 for lift coefficient(Cl)and 0.0371 for side coef-ficient(Cs).Total sound pressure level at the bottom of multi-group trains presents a significant streamwise increase,which is different from the three-coach train.Tunnel walls affect the acoustic distribution at the bottom,only after the coach number reaches a certain value,and the streamwise increase in the sound pressure fluctuation of multi-group trains is strengthened by coach number.Fourier transform of the turbulent and sound pressures presents that coach number has little influence on the peak frequencies,but increases the sound pressure level values at the tail bogie cavities.Furthermore,different from the turbulent pressure,the first two sound pressure proper orthogonal decomposition(POD)modes in the bogie cavities contain 90%of the total energy,and the spatial distributions indicate that the acoustic distributions in the head and tail bogies are not related to coach number.

Multi-Time Scale Operation and Simulation Strategy of the Park Based on Model Predictive Control

Due to the impact of source-load prediction power errors and uncertainties,the actual operation of the park will have a wide range of fluctuations compared with the expected state,resulting in its inability to achieve the expected economy.This paper constructs an operating simulation model of the park power grid operation considering demand response and proposes a multi-time scale operating simulation method that combines day-ahead optimization and model predictive control(MPC).In the day-ahead stage,an operating simulation plan that comprehensively considers the user’s side comfort and operating costs is proposed with a long-term time scale of 15 min.In order to cope with power fluctuations of photovoltaic,wind turbine and conventional load,MPC is used to track and roll correct the day-ahead operating simulation plan in the intra-day stage to meet the actual operating operation status of the park.Finally,the validity and economy of the operating simulation strategy are verified through the analysis of arithmetic examples.

New results on global exponential stability of competitive neural networks with different time scales and time-varying delays

This paper studies the global exponential stability of competitive neural networks with different time scales and time-varying delays. By using the method of the proper Lyapunov functions and inequality technique, some sufficient conditions are presented for global exponential stability of delay competitive neural networks with different time scales. These conditions obtained have important leading significance in the designs and applications of global exponential stability for competitive neural networks. Finally, an example with its simulation is provided to demonstrate the usefulness of the proposed criteria.

Establishment of an astronomical time scale for the Shizigou Formation in the Qaidam Basin,Inner Asia and orbital forced evolution of lakes during The Pliocene

The Qaidam Basin,as the largest inland basin within the Tibetan Plateau,has accumulated more than 10,000 m of Cenozoic continental sediments.It serves as a crucial research area for documenting Cenozoic climate changes and plateau uplift processes in the Asian interior.Additionally,the basin holds vast reserves of oil and gas resources,making high-resolution drilling data invaluable for studying paleoclimate.In this study,the longsequence lacustrine deposits of JS1 drill core across the Shizigou Formation in the Yiliping Depression at the western center of the basin were studied,aiming to establish an astronomical timescale for the Shizigou Formation and investigate the characteristics of paleoclimatic changes during the late Miocene to the Pliocene for the Asian interior.The analysis was carried out using high-resolution natural gamma ray(GR)data sequences,employing techniques such as spectral analysis,filtering,and wavelet analysis in cyclostratigraphy.The results indicated the presence of a stable Milankovitch orbital signal was perfectly recorded in the Shizigou Formation,primarily influenced by eccentricity cycles,with weaker obliquity and precession cycles.Using the stable and continuous 405 ka eccentricity cycle in astronomical tuning,a"floating"astronomical timescale with a duration of 6.1 Ma for the Yiliping depression's Shizigou Formation has been established.With reference to previously established stratigraphic age anchor points,an absolute astronomical timescale(2.5–8.6 Ma)has been ultimately provided for the Shizigou Formation.Simultaneously,a clear 100 ka short eccentricity cycle record has been identified during the Pliocene(5.3–2.5 Ma),which corresponds in time with the aridification within the basin during this Pliocene period.In addition,a comparison of the Pliocene natural gamma ray curve of the Qaidam Basin with global ice volume variations indicated that the basin's aridification was influenced by global cooling,with eccentricity-modulated precession cycles controlling solar radiation and subsequently affecting the evolution of lakes in the arid region of Inner Asia.

Interdecadal Variations of Phase Delays Between Two Nino Indices at Different Time Scales

Phase delays between two Nino indices-sea surface temperatures in Nino regions 1+2 and 3.4 (1950-2001)-at different time scales are detected by wavelet analysis. Analysis results show that there are two types of period bifurcations in the Nino indices and that period bifurcation points exist only in the region where the wavelet power is small. Interdecadal variation features of phase delays between the two indices vary with different time scales. In the periods of 40-72 months, the phase delay changes its sign in 1977: Nino 1+2 indices are 2-4 months earlier than Nino 3.4 indices before 1977, but 3-6 months later afterwards. In the periods of 20-40 months, however, the phase delay changes its sign in another way: Nino 1+2 indices are 1-4 months earlier before 1980 and during 1986-90, but 1-4 months later during 1980-83 and 1993-2001.

A step to the decentralized real-time timekeeping network

The composite time scale(CTS) provides an accurate and stable time-frequency reference for modern science and technology. Conventional CTS always features a centralized network topology, which means that the CTS is accompanied by a local master clock. This largely restricts the stability and reliability of the CTS. We simulate the restriction and analyze the influence of the master clock on the CTS. It proves that the CTS's long-term stability is also positively related to that of the master clock, until the region dominated by the frequency drift of the H-maser(averaging time longer than ~10~5s).Aiming at this restriction, a real-time clock network is utilized. Based on the network, a real-time CTS referenced by a stable remote master clock is achieved. The experiment comparing two real-time CTSs referenced by a local and a remote master clock respectively reveals that under open-loop steering, the stability of the CTS is improved by referencing to a remote and more stable master clock instead of a local and less stable master clock. In this way, with the help of the proposed scheme, the CTS can be referenced to the most stable master clock within the network in real time, no matter whether it is local or remote, making democratic polycentric timekeeping possible.

A Time-Domain Numerical Simulation for Free Motion Responses of Two Ships Advancing in Head Waves

The constant panel method within the framework of potential flow theory in the time domain is developed for solving the hydrodynamic interactions between two parallel ships with forward speed.When solving problems within a time domain framework,the free water surface needs to simultaneously satisfy both the kinematic and dynamic boundary conditions of the free water surface.This provides conditions for adding artificial damping layers.Using the Runge−Kutta method to solve equations related to time.An upwind differential scheme is used in the present method to deal with the convection terms on the free surface to prevent waves upstream.Through the comparison with the available experimental data and other numerical methods,the present method is proved to have good mesh convergence,and satisfactory results can be obtained.The constant panel method is applied to calculate the hydrodynamic interaction responses of two parallel ships advancing in head waves.Numerical simulations are conducted on the effects of forward speed,different longitudinal and lateral distances on the motion response of two modified Wigley ships in head waves.Then further investigations are conducted on the effects of different ship types on the motion response.

TSCND:Temporal Subsequence-Based Convolutional Network with Difference for Time Series Forecasting

Time series forecasting plays an important role in various fields, such as energy, finance, transport, and weather. Temporal convolutional networks (TCNs) based on dilated causal convolution have been widely used in time series forecasting. However, two problems weaken the performance of TCNs. One is that in dilated casual convolution, causal convolution leads to the receptive fields of outputs being concentrated in the earlier part of the input sequence, whereas the recent input information will be severely lost. The other is that the distribution shift problem in time series has not been adequately solved. To address the first problem, we propose a subsequence-based dilated convolution method (SDC). By using multiple convolutional filters to convolve elements of neighboring subsequences, the method extracts temporal features from a growing receptive field via a growing subsequence rather than a single element. Ultimately, the receptive field of each output element can cover the whole input sequence. To address the second problem, we propose a difference and compensation method (DCM). The method reduces the discrepancies between and within the input sequences by difference operations and then compensates the outputs for the information lost due to difference operations. Based on SDC and DCM, we further construct a temporal subsequence-based convolutional network with difference (TSCND) for time series forecasting. The experimental results show that TSCND can reduce prediction mean squared error by 7.3% and save runtime, compared with state-of-the-art models and vanilla TCN.

Accelerated Primal-Dual Projection Neurodynamic Approach With Time Scaling for Linear and Set Constrained Convex Optimization Problems

The Nesterov accelerated dynamical approach serves as an essential tool for addressing convex optimization problems with accelerated convergence rates.Most previous studies in this field have primarily concentrated on unconstrained smooth con-vex optimization problems.In this paper,on the basis of primal-dual dynamical approach,Nesterov accelerated dynamical approach,projection operator and directional gradient,we present two accelerated primal-dual projection neurodynamic approaches with time scaling to address convex optimization problems with smooth and nonsmooth objective functions subject to linear and set constraints,which consist of a second-order ODE(ordinary differential equation)or differential conclusion system for the primal variables and a first-order ODE for the dual vari-ables.By satisfying specific conditions for time scaling,we demonstrate that the proposed approaches have a faster conver-gence rate.This only requires assuming convexity of the objective function.We validate the effectiveness of our proposed two accel-erated primal-dual projection neurodynamic approaches through numerical experiments.

Periodic Solutions for a Kind of Second-Order Neutral Differential Equation on Time Scales

In this paper,the existence of periodic solutions and nonnegative periodic solutions for a kind of second-order neutral differential equation on time scales is considered.The partial increment is a fixed constant if the time scale is the real number set and is a multiple of the periodic of the time scale if the time scale is not the real number set.By means of a fixed point theorem due to Krasnoselskii,some sufficient conditions are obtained.

Model of Mediating Determinants of Time Differences in INDYCAR

The IndyCar series distinguishes itself by providing the same design and operation of the single-seater to its pilots.The difference in times is then attributable to the skills of the drivers,but considering the data from the races could test this assumption.The objective of this work was to establish a trajectory model to predict race times.A cross-sectional,correlational,and explanatory work was carried out with a sample of 18,474 records in the period from 2020 to 2023 of the IndyCar series.The results show that the time span predicts the time differences.In relation to the studies of acceptance of the technology,the adjustment of this to human capacities to explain the time differences in the series of racing cars is discussed.

Global Uniform Asymptotic Stability of Competitive Neural Networks with Different-Time Scales and Delay

The global uniform asymptotic stability of competitive neural networks with different time scales and delay is investigated. By the method of variation of parameters and the method of inequality analysis, the condition for global uniformly asymptotically stable are given. A strict Lyapunov function for the flow of a competitive neural system with different time scales and delay is presented. Based on the function, the global uniform asymptotic stability of the equilibrium point can be proved.

Assessment of the methods for determining net radiation at different time-scales of meteorological variables

When modeling the soil/atmosphere interaction,it is of paramount importance to determine the net radiation flux.There are two common calculation methods for this purpose.Method 1 relies on use of air temperature,while Method 2 relies on use of both air and soil temperatures.Nowadays,there has been no consensus on the application of these two methods.In this study,the half-hourly data of solar radiation recorded at an experimental embankment are used to calculate the net radiation and long-wave radiation at different time-scales(half-hourly,hourly,and daily) using the two methods.The results show that,compared with Method 2 which has been widely adopted in agronomical,geotechnical and geo-environmental applications.Method 1 is more feasible for its simplicity and accuracy at shorter time-scale.Moreover,in case of longer time-scale,daily for instance,less variations of net radiation and long-wave radiation are obtained,suggesting that no detailed soil temperature variations can be obtained.In other words,shorter time-scales are preferred in determining net radiation flux.

A CNN-Based Single-Stage Occlusion Real-Time Target Detection Method

Aiming at the problem of low accuracy of traditional target detection methods for target detection in endoscopes in substation environments, a CNN-based real-time detection method for masked targets is proposed. The method adopts the overall design of backbone network, detection network and algorithmic parameter optimisation method, completes the model training on the self-constructed occlusion target dataset, and adopts the multi-scale perception method for target detection. The HNM algorithm is used to screen positive and negative samples during the training process, and the NMS algorithm is used to post-process the prediction results during the detection process to improve the detection efficiency. After experimental validation, the obtained model has the multi-class average predicted value (mAP) of the dataset. It has general advantages over traditional target detection methods. The detection time of a single target on FDDB dataset is 39 ms, which can meet the need of real-time target detection. In addition, the project team has successfully deployed the method into substations and put it into use in many places in Beijing, which is important for achieving the anomaly of occlusion target detection.

Noether symmetry and conserved quantity for dynamical system with non-standard Lagrangians on time scales

This paper focuses on studying the Noether symmetry and the conserved quantity with non-standard Lagrangians, namely exponential Lagrangians and power-law Lagrangians on time scales. Firstly, for each case, the Hamilton prin- ciple based on the action with non-standard Lagrangians on time scales is established, with which the corresponding Euler-Lagrange equation is given. Secondly, according to the invariance of the Hamilton action under the infinitesimal transformation, the Noether theorem for the dynamical system with non-standard Lagrangians on time scales is established. The proof of the theorem consists of two steps. First, it is proved under the infinitesimal transformations of a special one-parameter group without transforming time. Second, utilizing the technique of time-re-parameterization, the Noether theorem in a general form is obtained. The Noether-type conserved quantities with non-standard Lagrangians in both clas- sical and discrete cases are given. Finally, an example in Friedmann-Robertson-Walker spacetime and an example about second order Duffing equation are given to illustrate the application of the results.

Reconstruction of different scales of pore-fractures network of coal reservoir and its permeability prediction with Monte Carlo method

There are millimeter, micron and nanometer scales of pores and fractures in coal to describe different scales of coal pores and fissures communicating path and to quantitatively characterize their permeability. Such information provides an important basis for studying coalbed methane output mechanism. The pores and fissures in a large number of coal samples were observed and counted by scanning electron microscopy and optical microscopy. The probability distribution models of pore-fissure network were then established. Different scales of pore-fissures 2D network models were reconstructed by Monte Carlo method. The 2D seepage models were obtained through assignment zero method and using Matlab software. The effect of permeability on different scale pore-fractures network was obtained by two-dimensional seepage equation. Predicted permeability is compared with the measured ones. The results showed that the dominant order of different scale pore-fractures connected path from high to low is millimeter-sized fractures, seepage pores and micron-size fractures. The contribution of coal reservoir permeability from large to small is millimeter-size fractures, micron-size fractures and seepage pores. Different parameters in different scale pore-fractures are of different influence permeability.Reconstruction of different scale pore-fractures network can clearly display the connectivity of porefractures, which can provide a basis for selecting migration path and studying gas flow pattern.

Climate Change and Its Effects on Runoff of Kaidu River, Xinjiang, China:A Multiple Time-scale Analysis

This paper applied an integrated method combining grey relation analysis, wavelet analysis and statistical analysis to study climate change and its effects on runoff of the Kaidu River at multi-time scales. Major findings are as follows: 1) Climatic factors were ranked in the order of importance to annual runoff as average annual temperature, average temperature in autumn, average temperature in winter, annual precipitation, precipitation in flood season, average temperature in summer, and average temperature in spring. The average annual temperature and annual precipi- tation were selected as the two representative factors that impact the annual runoff. 2) From the 32-year time scale, the annual runoff and the average annual temperature presented a significantly rising trend, whereas the annual precipita- tion showed little increase over the period of 1957-2002. By changing the time scale from 32-year to 4-year, we ob- served nonlinear trends with increasingly obvious oscillations for annual runoff, average annual temperature, and annual precipitation. 3) The changes of the runoff and the regional climate are closely related, indicating that the runoff change is the result of the regional climate changes. With time scales ranging from 32-year, 16-year, 8-year and to 4-year, there are highly significant linear correlations between the annual runoff and the average annual temperature and the annual precipitation.

A Floating Astronomical Time Scale for the Early Late Cretaceous Continental Strata in the Songliao Basin, Northeastern China

A continuous terrestrial succession was recovered from the Songke-2(SK-2)borehole in the Songliao Basin,Northeastern China.This borehole provides a unique material for further research on the continental paleoclimate during Cretaceous greenhouse period,following a series of achievements of the Songke-1(SK-1)core.In this study,thorium(Th)logging data were chosen as a paleoclimate proxy to conduct a detailed cyclostratigraphic analysis.The Th series varies quasi-periodically;power spectra and evolutionary fast Fourier transformation(FFT)analysis reveal significant cycles in the Quantou(K2 q),Qingshankou(K2 qn),Yaojia(K2 y)and Nenjiang(K2 n)formations.The ratio of cycle wavelengths in these stratigraphic units is approximately 20:5:2:1,corresponding to long orbital eccentricity(405 kyr),short orbital eccentricity(100 kyr),obliquity(37 kyr),and precession cycles(22.5 kyr and 18.4 kyr).The durations of the K2 n,K2 y,K2 qn and K2 q are estimated as 6.97,1.83,5.30 and 4.52 Myr,respectively,based on the constructed^18.62 Myr"floating"astronomical time scale(ATS).Comparison of the durations between the SK-1 s and SK-2 boreholes exhibits a slight difference of 0.06 Myr and 0.459 Myr for K2 qn and K2 y.Nevertheless,our ATS of K2 n supports the chronostratigraphic frame constructed by the CA-ID-TIMS data of the SK-1 s borehole.This new"floating"ATS provides precise numerical ages for stratigraphic boundaries,biozones and geological events in the Songliao Basin,and can serve as a basis for correlation of strata and events between marine and terrestrial systems.

Small-time scale network traffic prediction based on a local support vector machine regression model

In this paper we apply the nonlinear time series analysis method to small-time scale traffic measurement data. The prediction-based method is used to determine the embedding dimension of the traffic data. Based on the reconstructed phase space, the local support vector machine prediction method is used to predict the traffic measurement data, and the BIC-based neighbouring point selection method is used to choose the number of the nearest neighbouring points for the local support vector machine regression model. The experimental results show that the local support vector machine prediction method whose neighbouring points are optimized can effectively predict the small-time scale traffic measurement data and can reproduce the statistical features of real traffic measurements.