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Promoting low-carbon in the construction industry is important for achieving the overall low-carbon goals. Public–private partnership is very popular in public infrastructure projects. However, different perceptions of low-carbon and behaviors of public and private sectors can hinder the realization of low-carbon in these projects. In order to analyze the willingness of each stakeholder to cooperate towards low-carbon goals, an evolutionary game model is constructed.

An evolutionary game model that considers the opportunistic behavior of the participants is developed. The evolutionary stable strategies (ESSs) under different scenarios are examined, and the factors that influence the willingness to cooperate between the government and private investors are investigated.

The results illustrate that a well-designed system of profit distribution and subsidies can enhance collaboration. Excessive subsidies have negative impact on cooperation between the two sides, because these two sides can weaken income distribution and lead to the free-riding behavior of the government. Under the situation of two ESSs, there is also an optimal revenue distribution coefficient that maximizes the probability of cooperation. With the introduction of supervision and punishment mechanism, the opportunistic behavior of private investors is effectively constrained.

An evolutionary game model is developed to explore the cooperation between the public sector and the private sector in the field of low-carbon construction. Based on the analysis of the model, this paper summarizes the conditions and strategies that can enable the two sectors to cooperate.

The purpose of this paper is to solve the problem of adaptive predefined-time control for spacecraft rendezvous maneuver with input quantization and unknown parameters.

A significant error-shifting function is established to ensure that the limitation of the initial condition can be ignored. Then, a combination of neural networks method and minimum-learning-parameter method is used to mitigate the adverse effects caused by nonlinear system dynamics. An input quantization method is applied to improved efficiency of data communication between controller and actuator in rendezvous maneuver control system.

The simulation results verify the correctness and effectiveness of the designed control strategy which can effectively overcome the disadvantages caused by coupling nonlinear system dynamics.

This paper designs an adaptive predefined-time control method for spacecraft rendezvous maneuver control with input quantization based on backstepping control method.

This paper aims to study the issues of output reachable set estimation for the linear singular Markovian jump systems (SMJSs) with time-varying delay based on a proportional plus derivative (PD) bumpless transfer (BT) output feedback (OF) control scheme.

To begin with, a sufficient criterion is given in the form of a linear matrix inequality based on the Lyapunov stability theory. Then, a PD-BT OF controller is designed to keep all the output signs of the system are maintain within a predetermined ellipsoid. Finally, numerical and practical examples are used to demonstrate the efficiency of the approach.

Based on PD control and BT control method, an OF control strategy for the linear SMJSs with time-varying delay is proposed.

The output reachable set synthesis of linear SMJSs with time-varying delay can be solved by using the proposed approach. Besides, to obtain more general results, the restrictive assumptions of some parameters are removed. Furthermore, a sufficiently small ellipsoid can be obtained by the design scheme adopted in this paper, which reduces the conservatism of the existing results.

With the rapid development of e-commerce in China, the third-party payment system greatly improved the efficiency and volume of the entire trading market. The purpose of this paper is to put forward a suitable prediction model to analyse its development trend.

The authors analyse internet third-party payments in China, taking into account online payment transaction values coupled with an ARMA model and the fractional grey model (FGM). First, the rolling FGM model is applied in order to characterise the trends of the transaction volume. The influence of the initial value change on the FGM model is analysed. The optimisation mean absolute percentage error (MAPE) model is constructed to determine the optimal translational values, the corresponding optimal accumulation order and optimal inverse accumulation order.

This paper uses China’s recent third-party online payment data to quantify its development trend. The authors find the coupling model suitable for the development trend of third-party online payment transaction. The results show that the model is suitable to quantify its development trend of China’s recent third-party online payment.

Considering the complex influence factors that lead to the third-party online payment volume data of time-varying grey feature, this paper combines the FGM with ARMA model to describe the development of third-party payment mode.

The purpose of this work is to apply the Fourier–Ritz method to study the vibration behavior of the moderately thick functionally graded (FG) parabolic and circular panels and shells of revolution with general boundary conditions.

The modified Fourier series is chosen as the basis function of the admissible functions of the structure to eliminate all the relevant discontinuities of the displacements and their derivatives at the edges, and the vibration behavior is solved by means of the Ritz method. The complete shells of revolution can be achieved by using the coupling spring technique to imitate the kinematic compatibility and physical compatibility conditions of FG parabolic and circular panels at the common meridian of θ = 0 and 2π. The convergence and accuracy of the present method are verified by other contributors.

Some new results of FG panels and shells with elastic restraints, as well as different geometric and material parameters, are presented and the effects of the elastic restraint parameters, power-law exponent, circumference angle and power-law distributions on the free vibration characteristic of the panels are also presented, which can be served as benchmark data for the designers and engineers to avoid the unpleasant, inefficient and structurally damaging resonant.

The paper could provide the reference for the research about the moderately thick FG parabolic and circular panels and shells of revolution with general boundary conditions. In addition, the change of the boundary conditions can be easily achieved by just varying the stiffness of the boundary restraining springs along all the edges of panels without making any changes in the solution procedure.

The construction industry has experienced an irreversible digital transformation to smart construction. Many countries have published supporting policies to encourage the development of smart construction. However, there is no universally valid approach. This paper thus aims to evaluate smart construction policies issued by 24 pilot cities in China and identify applicable policy tools and their impact.

This paper collected 33 governmental documents on smart construction through the official websites in China. Different policy tools were classified into supply-side, demand-side and environment-side categories. The supporting policies of smart construction development in pilot cities were quantitatively evaluated by using a policy modeling consistency index (PMC-index) model.

Supply-type and environment-type policy instruments were used more frequently than demand-type policies in 24 pilot cities. Most of the 24 pilot cities had an evaluation of PMC-index over 8, realizing the consistency of smart construction policies. Eight pilot cities had an evaluation of PMC-index of 6–7.99, realizing acceptable consistency. Only Foshan City has an evaluation of PMC-index below 4, which may reflect a poor consistency of policy implementation. The paper proposes consistencies of smart construction policies of 24 pilot cities and valid policy instruments, including the presale of commercial residential buildings, additional bonus points in the tendering process and cooperating with multiple departments when promoting smart construction.

This paper contributes to expanding policy evaluation studies in the smart construction field and provides concrete suggestions for policymakers to formulate more effective and specific policies and strategies for the development of smart construction.

This paper aims to address the safety concerns of path-planning algorithms in dynamic obstacle warehouse environments. It proposes a method that uses improved artificial potential fields (IAPF) as expert knowledge for an improved deep deterministic policy gradient (IDDPG) and designs a hierarchical strategy for robots through obstacle detection methods.

The IAPF algorithm is used as the expert experience of reinforcement learning (RL) to reduce the useless exploration in the early stage of RL training. A strategy-switching mechanism is introduced during training to adapt to various scenarios and overcome challenges related to sparse rewards. Sensor inputs, including light detection and ranging data, are integrated to detect obstacles around waypoints, guiding the robot toward the target point.

Simulation experiments demonstrate that the integrated use of IDDPG and the IAPF method significantly enhances the safety and training efficiency of path planning for mobile robots.

This method enhances safety by applying safety domain judgment rules to improve APF’s security and designing an obstacle detection method for better danger anticipation. It also boosts training efficiency through using IAPF as expert experience for DDPG and the classification storage and sampling design for the RL experience pool. Additionally, adjustments to the actor network’s update frequency expedite convergence.

Traditional algorithms require at least two complete vector observations to estimate orientation parameters. However, sensor faults and disturbances may cause some components of vector observations unavailable. This paper aims to propose algorithms to realize orientation estimation using vector observations with one or two components lost.

The fundamental of the proposed method is using norm equation and dot product equation to estimate the lost components, then, using an improved TRIAD to calculate attitude matrix. Specific algorithms for one and two lost components cases are constructed respectively, and the nonuniqueness of orientation estimation is analyzed from a geometric point of view. At last, experiments are performed to test the proposed algorithms.

The loss of components results in the loss of orientation information. The introduction of the norm equation and dot product equation can partially compensate for the loss of information. Experiment results and analysis show that the proposed algorithms can provide effective orientation estimation, and in vast majority of applications, the proposed algorithms can provide a unique solution in one lost component case and double solutions in two lost components case.

The proposed method addresses the problem of orientation estimation when one or two components of vector observations are unavailable. The introduction of the norm equation and dot product equation makes the calculation cost low, while the analyses from a geometric point of view makes the study of nonuniqueness more intuitive.

Grey modeling technique is an important element of grey system theory, and academic articles applied to agricultural science research have been published since 1985, proving the broad applicability and effectiveness of the technique from different aspects and providing a new means to solve agricultural science problems. The analysis of the connotation and trend of the application of grey modeling technique in agricultural science research contributes to the enrichment of grey technique and the development of agricultural science in multiple dimensions.

Based on the relevant literature selected from China National Knowledge Infrastructure, the Web of Science, SpiScholar and other databases in the past 37 years (1985–2021), this paper firstly applied the bibliometric method to quantitatively visualize and systematically analyze the trend of publication, productive author, productive institution, and highly cited literature. Then, the literature is combed by the application of different grey modeling techniques in agricultural science research, and the literature research progress is systematically analyzed.

The results show that grey model technology has broad prospects in the field of agricultural science research. Agricultural universities and research institutes are the main research forces in the application of grey model technology in agricultural science research, and have certain inheritance. The application of grey model technology in agricultural science research has wide applicability and precise practicability.

By analyzing and summarizing the application trend of grey model technology in agricultural science research, the research hotspot, research frontier and valuable research directions of grey model technology in agricultural science research can be more clearly grasped.

This article aims to propose a model to support the assessment and prioritization of risk in manufacturing processes.

The model integrates the failure modes and effects analysis (FMEA) criteria with the evaluation procedures of a new hesitant fuzzy linguistic-technique for Order of Preference by Similarity to Ideal Solution (HFL-TOPSIS) variation. A case study evaluating failure risk in a wiring harness assembly process demonstrated the model's applicability. A sensitivity analysis was performed to verify the effect of the variation in the weights assigned to the decision-makers (DMs).

The failure mode (FM) ranking was FM4 > FM9 > FM17 > FM2>FM8>FM12 > FM16 > FM19 > FM11 > FM3>FM18 > FM15 > FM13 > FM10 > FM14 > FM7 > FM1 > FM5 > FM6. These outcomes suggest that “stripping length less than specified” was the top priority among the 19 FMs evaluated. Sensitivity tests demonstrated the effect of the DMs’ weights on the ranking of FMs. A comparison with FMEA and HFL-TOPSIS demonstrates the model's greater capacity to discriminate levels of risk priority, as it identifies a total of 19 risk levels compared with 9 levels in the other approaches.

The adoption of the proposed model can drive substantial improvements in risk management practices across industries, provided that the organization has a decision-making team experienced with FMEA. Therefore, this approach promotes the continuous improvement of operations and ensures that mitigation actions effectively address critical FMs.

This is the first study to propose a risk evaluation model that accounts for DMs' hesitation in defining criteria weights through linguistic expressions. Additionally, it addresses uncertainty when assessing weights for the DMs’ opinions and considers multiple factors that affect these weights in decision-making for risk prioritization.