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China aims to reduce carbon dioxide emissions and achieve peak carbon and carbon neutrality goals. Natural gas, as a high-quality fossil fuel energy, is an important transition resource for China in the process of carbon reduction, so it is necessary to predict China's natural gas demand. In this paper, a novel natural gas demand combination forecasting model is constructed to accurately predict the future natural gas demand. The Lasso model and the polynomial model are used to build a combinatorial model, which overcomes the shortcomings of traditional models, which have low data dimensions and poor prediction abilities. In the modeling process, the cross-validation method is used to adjust the modeling parameters. By comparing the performance of the combinatorial forecasting model, the single forecasting model and other commonly used forecasting models, the results show that the error (2.99%) of the combinatorial forecasting model is the smallest, which verifies the high accuracy and good stability advantages of the combinatorial forecasting model. Finally, the paper analyzes the relevant data from 1999 to 2022 and predicts China's natural gas demand in the next 10 years. The results show that the annual growth rate of China's natural gas demand in the next 10 years will reach 13.33%, at 8.3 × 1011 m3 in 2033, which proves that China urgently needs to rapidly develop the gas supply capacity of gas supply enterprises. This study integrates the impact of multiple factors on the natural gas demand, predicts China's natural gas demand from 2023 to 2033, and provides decision-making support for China's energy structure adjustment and natural gas import trade. [ABSTRACT FROM AUTHOR]

China's total energy consumption and production rank first in the world. However, China's energy structure is not reasonable. Therefore, accurate prediction of future energy trends is of great significance for the Chinese government to adjust the energy structure. In this paper, we propose an optimized Grey Euler model with polynomial term, which is abbreviated as OSGEM(1,1,N), to forecast the total energy consumption and production of China in comparison with the commonly used prediction models. The data from 2002 to 2018 are used to simulate the parameters in the proposed model, and the data from 2019 to 2021 are used to test the improved approach. The results show that the OSGEM(1,1,N) model outperforms the other models. Finally, the OSGEM(1,1,N) model is used to forecast the total energy consumption of China from 2022 to 2025 and different results from the previous research results have been obtained. [ABSTRACT FROM AUTHOR]

The discrete grey modelling technique is a novel methodology of grey prediction models, which is effective to improve the effectiveness and applicability of grey models. In order to build a more general and effective univariate grey prediction model, the discrete grey modelling technique is utilised in this paper to build a Quadratic Polynomial Discrete Grey Model (QPDGM). The properties of the QPDGM have been discussed, which indicate that the new model can be regarded as an extension of the conventional discrete grey model and nonhomogeneous grey model, and it is also coincidence with three classes of exponential sequences. The QPDGM is finally applied to predict the energy consumption of China, including the electric power, crude oil and natural gas consumptions. The results have been compared to some commonly used univariate grey prediction models, which indicates the QPDGM is generally more accurate than other models. [ABSTRACT FROM AUTHOR]

This paper aims to explore how job involvement and supervisor developmental feedback (SDF) interact to affect employee creativity. Through the lens of person-supervisor fit theory, we employed polynomial regression with response surface analysis to map the interconnections between job involvement, SDF, and creativity. We conducted two independent studies to investigate the relationship. In the first study, we analyzed 389 MBA students' (former and current) responses from a large university in China and in the second study, we surveyed 392 full time employees from a high-technology company. The two studies confirmed a dynamic relationship among these three variables (i.e., job involvement, SDF, and creativity). The polynomial regression results indicated that employee creativity peaks when job involvement and SDF are both high. In addition, when job involvement is low but SDF is high, or vice versa, employee creativity is at a high level as well. [ABSTRACT FROM AUTHOR]

A fiber-optic gyroscope (FOG) with lower precision but higher cost advantage is typically selected according to working conditions and engineering budget. Thermal drift is the main factor affecting FOG precision. External thermal calibration methods by algorithms can effectively weaken the influence of thermal drift. This paper presents a thermal calibration method of a two-dimensional N-order polynomial (TDNP) and compares it with artificial neural network (ANN) methods to determine a software FOG thermal calibration method for landslide displacement monitoring. The TDNP thermal calibration coefficient matrix was established, and the thermal calibration capability of the TDNP method with different orders N was evaluated on the basis of error analysis. The ANN model with 1 to 18 hidden neural layers was established on the basis of LM, BR, and SCG algorithms to choose a suitable ANN. Finally, the mean absolute errors of FOG thermal calibration through the TDNP with different orders and the LM were compared. This method was applied in the Huangtupo landslide area, China. The results highlight that the TDNP method with order 5 had better performance and satisfied the requirements of landslide displacement monitoring. The research results can compensate for the lack of adaptability of the FOG thermal calibration method in landslide displacement monitoring. [ABSTRACT FROM AUTHOR]

This paper develops a new grey prediction model with quadratic polynomial term. Analytical expressions of the time response function and the restored values of the new model are derived by using grey model technique and mathematical tools. With observations of the confirmed cases, the death cases and the recovered cases from COVID-19 in China at the early stage, the proposed forecasting model is developed. The computational results demonstrate that the new model has higher precision than the other existing prediction models, which show the grey model has high accuracy in the forecasting of COVID-19. [ABSTRACT FROM AUTHOR]

Usually, the rational polynomial coefficient (RPC) model of spaceborne synthetic aperture radar (SAR) is fitted by the original range Doppler (RD) model. However, the radar signal is affected by two-way atmospheric delay, which causes measurement error in the slant range term of the RD model. In this paper, two atmospheric delay correction methods are proposed for use in terrain-independent RPC fitting: single-scene SAR imaging with a unique atmospheric delay correction parameter (plan 1) and single-scene SAR imaging with spatially varying atmospheric delay correction parameters (plan 2). The feasibility of the two methods was verified by conducting fitting experiments and geometric positioning accuracy verification of the RPC model. The experiments for the GF-3 satellite were performed by using global meteorological data, a global digital elevation model, and ground control data from several regions in China. The experimental results show that it is feasible to use plan 1 or plan 2 to correct the atmospheric delay error, no matter whether in plain, mountainous, or plateau areas. Moreover, the geometric positioning accuracy of the RPC model after correcting the atmospheric delay was improved to better than 3 m. This is of great significance for the efficient and high-precision geometric processing of spaceborne SAR images. [ABSTRACT FROM AUTHOR]

When performing spatial regression analysis in environmental data applications, spatial heterogeneity in the regression coefficients is often observed. Spatially varying coefficient models, including geographically weighted regression and spline models, are standard tools for quantifying such heterogeneity. In this paper, we propose a spatially varying coefficient model that represents the spatially varying parameters as a mixture of local polynomials at selected locations. The local polynomial parameters have attractive interpretations, indicating various types of spatial heterogeneity. Instead of estimating the spatially varying regression coefficients directly, we develop a penalized least squares regression procedure for the local polynomial parameter estimation, which both shrinks the parameter estimation and penalizes the differences among parameters that are associated with neighboring locations. We develop confidence intervals for the varying regression coefficients and prediction intervals for the response. We apply the proposed method to characterize the spatially varying association between particulate matter concentrations (PM2.5) and pollutant gases related to the secondary aerosol formulation in China. The identified regression coefficients show distinct spatial patterns for nitrogen dioxide, sulfur dioxide, and carbon monoxide during different seasons. [ABSTRACT FROM AUTHOR]

Summary  In 1985 China began the reform of its Science & Technology (S&T) sector inherited from the planned economy. To disclose the impact of the drawn-out reform on the efficiency of the whole sector, we measure the scientific productivity of China's S&T institutes. The analysis is based on R&D input and output data at the country aggregate and provincial level. We utilize Polynomial Distributed Lag model to uncover the structure of the lag between R&D input and output. The findings reveal that the growth rate of scientific productivity of China's S&T institutes has been negative since the 1990s. [ABSTRACT FROM AUTHOR]

Near-surface PM2.5 estimates remain a global scientific research challenge due to their effect on human fitness and atmospheric environmental quality. However, practical near-surface PM2.5 estimates are impeded by the incomplete monitoring data. In this study, we propose the trigonometric polynomial fitting (TPF) method to estimate near-surface PM2.5 concentrations in south-central China during 2015. We employ 10-fold cross-validation (CV) to assess the reliability of TPF in estimating practical PM2.5 values. When compared to alternative methods such as the orthogonal polynomial fitting (OBF) method based on Chebyshev basis functions, Kriging interpolation, and radial basis function (RBF) interpolation, our results show that utilizing TPF31, with a maximum order of 3 in the x direction and a maximum order of 1 in the y direction, leads to superior efficiency through error minimization. TPF31 reduces MAE and RMSE by 1.93%, 24%, 6.96% and 3.6%, 23.07%, 10.43%, respectively, compared to the other three methods. In addition, the TPF31 method effectively reconstructs the spatial distribution of PM2.5 concentrations in the unevenly distributed observation stations of Inner Mongolia and the marginal regions of the study area. The reconstructed spatial distribution is remarkably smooth. Despite the non-uniform distribution of observation stations and the presence of missing data, the TPF31 method demonstrates exceptional effectiveness in accurately capturing the inherent physical attributes of spatial distribution. The theoretical and experimental results emphasize that the TPF method holds significant potential for accurately reconstructing the spatial distribution of PM2.5 in China. [ABSTRACT FROM AUTHOR]

Purpose – Research on workplace loneliness has thus far been dominated by perceptions of followers; hence, few researchers have considered the perspective of leader-follower congruence. The purpose of this paper is to examine how the leader-follower relationship mediates the relationship between leader-follower congruence/incongruence in workplace loneliness and turnover intentions. Design/methodology/approach – Data were collected from 232 leader-follower dyads from ten companies in China. Polynomial regression combined with the response surface methodology was used to test the hypotheses. Findings – Four conclusions were drawn. First, leader-member exchange (LMX) was higher when leaders and followers were aligned in terms of workplace loneliness than otherwise. Second, in the case of leader-follower congruence, LMX rose as their workplace loneliness fell. Third, in the case of incongruence, followers had lower LMX when they were lonelier than their leaders. Finally, LMX partially mediated the leader-follower congruence/incongruence effect of workplace loneliness on followers’ turnover intention. Originality/value – This study emphasized the importance of leaders’ congruence with followers in workplace loneliness. Additionally, it extended research on leader-follower congruence from a positive perspective to a negative one. [ABSTRACT FROM AUTHOR]

Chang'E-5 (CE-5) is China's first lunar sample return mission. This paper focuses on the trajectory determination of the CE-5 lander and ascender during the landing and ascending phases, and the positioning of the CE-5 lander on the Moon. Based on the kinematic statistical orbit determination method using B-spline and polynomial functions, the descent and ascent trajectories of the lander and ascender are determined by using ground-based radiometric ranging, Doppler and interferometry data. The results show that a B-spline function is suitable for a trajectory with complex maneuvers. For a smooth trajectory, B-spline and polynomial functions can reach almost the same solutions. The positioning of the CE-5 lander on the Moon is also investigated here. Using the kinematic statistical positioning method, the landing site of the lander is 43.0590°N, 51.9208°W with an elevation of −2480.26 m, which is less than 200 m different from the LRO (Lunar Reconnaissance Orbiter) image data. [ABSTRACT FROM AUTHOR]

This paper presents a synthesis technique of the dual offset shaped reflector antenna using Differential Evolution with Global and Local neighborhoods (DEGL) algorithm. The main reflector and subreflector are parameterized by Zernike polynomial expansion. With these expansion coefficients, the antenna is optimized to achieve a contoured beam covering the China territory in Ku-band. The performance of the antenna is calculated by Physical Optics (PO) and Physical Theory of Diffraction (PTD) techniques. The calculated results are validated by the commercial software GRASP9.3.01. [ABSTRACT FROM AUTHOR]

The government of China is now trying to use natural gas as partial substitute of other fuels, such as coal and gasoline. Developing the natural gas industry has been written in the 13th Five Year Plan of China, which is the most important official policy of China. Predicting the natural gas consumption comes to be very important for the government and energy companies to make decisions. In this paper, we propose a novel time-delayed polynomial grey prediction model, which is abbreviated as TDPGM(1, 1), based on the grey system theory to forecast the natural gas consumption of China in comparison with the commonly used prediction models. The data from 1995 to 2004 are used to build the prediction models, and the data from 2005 to 2013 are used to assess the modelling accuracy. The results show that the TDPGM(1, 1) model outperforms the other models. Finally the TDPGM(1, 1) model is used to forecast the natural gas consumption of China from 2014 to 2020 and different results from the previous research results have been obtained. [ABSTRACT FROM AUTHOR]

• A novel discrete GM(2,1) model with a polynomial term is proposed. • The generalization and adaptability of the proposed model were validated from the theoretical and practical perspectives. • The newly-designed model is applied to predict per capita living electricity consumption. The forecast of electrical energy demand has played an increasingly relevant role in sustainable electrical power system. This paper develops a new method for forecasting China's per capita living electricity consumption by grey modelling technique. Considering the multiple and mixed change patterns, a novel discrete grey model with polynomial term (abbreviated as DGM(2,1, kn)) is proposed in this study. Firstly, the polynomial term is introduced into the discrete DGM(2,1) model. Secondly, the Tikhonov regularization method is employed to solve the overfitting problem. Lastly, two published cases and China's per capita living electricity consumption are used to validate the generalization and adaptability of the newly-designed model. The numerical results of such experiments show that the proposed model outperforms other competitive models in terms of accuracy level. Therefore, the projections of China's per capita living electricity consumption in 2020 and 2025 have been made for providing a solid reference for the formulation of electrical power strategies. [ABSTRACT FROM AUTHOR]

Clean energy, represented by hydropower, wind power, and nuclear power, plays a crucial role in addressing the issue of power shortage and promoting the transition of the energy structure. Scientific and accurate forecasting of clean energy generation volume can provide the necessary reference for relevant authorities to formulate reasonable energy policies. This paper proposes a novel fractional time-delay polynomial discrete grey model, FTDP-DGM(1,1), for forecasting clean energy generation volume in China. Firstly, both the structural parameters and the time response function are derived directly from the discrete equation. Secondly, the genetic algorithm is employed to determine the optimal value of the nonlinear parameter in the model, with the optimization objective of minimizing the mean absolute percentage error. Then, the proposed model is applied to the simulation and prediction of hydro, wind, and nuclear energy generation volume in China. The results show the validity and superiority of the model. Finally, out-of-sample forecasts are performed, and the forecasting results show that the proposed model has good performance with values of 1.29%, 2.94%, and 2.32% for mean absolute percentage error(MAPE), respectively. It is expected that in 2021–2025, China's hydro, wind, and nuclear power generation volume will continue to grow at a rate of 1.45%, 10.74%, and 10.66% respectively. Based on the forecast results, policy recommendations are suggested. [ABSTRACT FROM AUTHOR]

Abstract: Accurate sensors are the prerequisite for any building control and management operation to succeed. However, due to the lack of awareness of the importance, sensors are often out of calibration. This paper proposes a preventive approach to determine sensor maintenance requirements, which aims to explicitly quantify the importance of sensors and determine a proper calibration frequency for sensors with high importance. The approach takes account of the sensor bias growth mechanism and relates the sensor importance to a user-defined building performance index. The sensor importance is evaluated under a stochastic framework, which essentially is the way in which sensor bias grows. The calibration frequency is identified using a polynomial function which describes the degradation rate of the building performance index. The proposed approach is applied to a building located in Hong Kong. Results show that the proposed approach can effectively identify important sensors and their calibration frequency. [Copyright &y& Elsevier]

Abstract: Pipe breaks often occur in water distribution networks, imposing great pressure on utility managers to secure stable water supply. However, pipe breaks are hard to detect by the conventional method. It is therefore necessary to develop reliable and robust pipe break models to assess the pipe''s probability to fail and then to optimize the pipe break detection scheme. In the absence of deterministic physical models for pipe break, data-driven techniques provide a promising approach to investigate the principles underlying pipe break. In this paper, two data-driven techniques, namely Genetic Programming (GP) and Evolutionary Polynomial Regression (EPR) are applied to develop pipe break models for the water distribution system of Beijing City. The comparison with the recorded pipe break data from 1987 to 2005 showed that the models have great capability to obtain reliable predictions. The models can be used to prioritize pipes for break inspection and then improve detection efficiency. [Copyright &y& Elsevier]

Ozone formation regimes are closely related to the ratio of volatile organic compounds (VOCs) to NOx. Different ranges of HCHO/NO2 indicate three formation regimes, including VOC-limited, transitional, and NOx -limited regimes. Due to the unstable interactions between a diversity of precursors, the range of the transitional regime, which plays a key role in identifying ozone formation regimes, remains unclear. To overcome the uncertainties from single models and the lack of reference data, we employed two models, polynomial simulation and convergent cross-mapping (CCM), to identify the ranges of HCHO/NO2 across China based on ground observations and remote sensing datasets. The ranges of the transitional regime estimated by polynomial simulation and CCM were [1.0, 1.9] and [1.0, 1.8]. Since 2013, the ozone formation regime has changed to the transitional and NOx -limited regime all over China, indicating that ozone concentrations across China were mainly controlled by NOx. However, despite the NO2 concentrations, HCHO concentrations continuously exert a positive influence on ozone concentrations under transitional and NOx -limited regimes. Under the circumstance of national NOx reduction policies, the increase in VOCs became the major driver for the soaring ozone pollution across China. For an effective management of ozone pollution across China, the emission reduction in VOCs and NOx should be equally considered. [ABSTRACT FROM AUTHOR]

Purpose: Drawing on the transactional cost economics (TCE) perspective, we aim to investigate the effects of the balance and imbalance between contractual and relational governance on a firm's bridging responses to supply chain disruptions. By adopting the institutionally contingent perspective, we further examine the moderating effect of cultural distance on the relationship between governance mechanisms and bridging responses. Design/methodology/approach: Based on data collected from 183 firms in China, we use polynomial regression and response surface analyses to test our research model. Findings: The bridging responses increase along with an increasing balance level between contractual and relational governance and decrease along with an increasing imbalance level between contractual and relational governance. Moreover, the positive effect of balance between contractual and relational governance is strengthened by a large cultural distance. We also find that a large cultural distance amplifies the negative effect of the combination of high relational governance and low contractual governance yet weakens that of the combination of high contractual governance and low relational governance. Originality/value: Our study provides nuanced insights into the effects of the balance and imbalance between contractual and relational governance on bridging responses and into the cultural boundary conditions under which these effects vary. [ABSTRACT FROM AUTHOR]

The Ziyuan-3 (ZY-3) is the first civil high-resolution optical stereoscopic mapping satellite developed by China. It was launched on January 9, 2012, and as of January 9, 2020, it has been in a continuous operation for 8 years in orbit. The direct geolocation performances of ZY-3 based on the Rational Polynomial Coefficients (RPC) model are discussed, and the monoscopic and stereoscopic geometric accuracy of ZY-3 with ground control point (GCP) have also been studied using a bundle block adjustment with the affine correction in image space. Through the analysis of 47 sets of ZY-3 stereo data in Harbin, China, it can be found that from 2012 to 2019, the ZY-3 geolocation accuracy without GCP remains stable, with an average planimetric accuracy of approximately 16.2m, an average elevation accuracy of about 7.5m. The internal accuracy of the panchromatic triplet images is better than 1.0 pixel, the planimetric accuracy and elevation accuracy of stereo triplets and and stereo pairs are better than 2.0 meters with control points. In general, the results show that the ZY-3 satellite has been in good and stable condition during in-orbit operation in the past 8 years, and the various test indicators have been able to meet the design specifications. [ABSTRACT FROM AUTHOR]

Based on the statistical data, natural gas consumption of China from 1995 to 2011, Boltzmann model and a third-order polynomial curve model are employed to fit the historical data, which aim to explore the rule of the past variation tendency and find out the proper model for forecasting. Fitting results demonstrate that a combination model based on the Boltzmann model and a third-order polynomial curve model can show great fitting result and its residual sum of squares and mean absolute percentage error are remarkably less than those of any previous models. According to the combined model, the average annual growth rate of the consumption in the next 7 years is 16.27% from 2012 to 2018. [ABSTRACT FROM AUTHOR]

Temperature field data from the steel truss arch girder and longitudinal displacement data from six groups of rubber bearings were collected by the structural health monitoring system for the Dashengguan Yangtze Bridge. By using long-term monitoring data, two correlations are investigated: the linear correlation between the longitudinal displacement and the temperature field (including uniform temperature and temperature gradient); and the linear correlation of the longitudinal displacements in different locations. A multivariate linear regression equation is used to model the first correlation, and a Lagrange polynomial interpolation is used to model the second correlation. The final mathematical models, representing the healthy state of the bearings, can be applied to simulate the longitudinal displacements of the main girder. Furthermore, the change regularity of longitudinal displacements for the degraded rubber bearings is revealed taking advantage of a hysteretic model and presumed envelope curves of frictions caused by bearing degradation. A method of detection and location for the degraded bearings is proposed in four detailed steps, and the numerical results demonstrate that this method is effective. [ABSTRACT FROM AUTHOR]

Background: Hand, Foot, and Mouth Disease (HFMD) is a worldwide infectious disease. In China, many provinces have reported HFMD cases, especially the south and southwest provinces. Many studies have found a strong association between the incidence of HFMD and climatic factors such as temperature, rainfall, and relative humidity. However, few studies have analyzed cluster effects between various geographical units. Methods: The nonlinear relationships and lag effects between weekly HFMD cases and climatic variables were estimated for the period of 2008–2013 using a polynomial distributed lag model. The extra-Poisson multilevel spatial polynomial model was used to model the exact relationship between weekly HFMD incidence and climatic variables after considering cluster effects, provincial correlated structure of HFMD incidence and overdispersion. The smoothing spline methods were used to detect threshold effects between climatic factors and HFMD incidence. Results: The HFMD incidence spatial heterogeneity distributed among provinces, and the scale measurement of overdispersion was 548.077. After controlling for long-term trends, spatial heterogeneity and overdispersion, temperature was highly associated with HFMD incidence. Weekly average temperature and weekly temperature difference approximate inverse “V” shape and “V” shape relationships associated with HFMD incidence. The lag effects for weekly average temperature and weekly temperature difference were 3 weeks and 2 weeks. High spatial correlated HFMD incidence were detected in northern, central and southern province. Temperature can be used to explain most of variation of HFMD incidence in southern and northeastern provinces. After adjustment for temperature, eastern and Northern provinces still had high variation HFMD incidence. Conclusion: We found a relatively strong association between weekly HFMD incidence and weekly average temperature. The association between the HFMD incidence and climatic variables spatial heterogeneity distributed across provinces. Future research should explore the risk factors that cause spatial correlated structure or high variation of HFMD incidence which can be explained by temperature. When analyzing association between HFMD incidence and climatic variables, spatial heterogeneity among provinces should be evaluated. Moreover, the extra-Poisson multilevel model was capable of modeling the association between overdispersion of HFMD incidence and climatic variables. [ABSTRACT FROM AUTHOR]

We examine whether mixed-frequency investor sentiment affects stock returns. In line with recent evidence from China, we find that the aggregate effect and the individual effect of mixed-frequency investor sentiment are statistically significant, and mixed-frequency investor sentiment is more important than the low-frequency one. Moreover, mixed-frequency investor sentiment, which is mixed by high-frequency data, can be more important than the market premium. [ABSTRACT FROM PUBLISHER]

A new approach was proposed to reformulate the biobjectives optimization model of portfolio management into an unconstrained minimization problem, where the objective function is a piecewise quadratic polynomial. We presented some properties of such an objective function. Then, a class of penalty algorithms based on the well-known conjugate gradient methods was developed to find the solution of portfolio management problem. By implementing the proposed algorithm to solve the real problems from the stock market in China, it was shown that this algorithm is promising. [ABSTRACT FROM AUTHOR]