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The purpose of this paper is to present a solution for the uncertain fault with the propulsion subsystem of satellite formation, using the Lur’e differential inclusion linear state observers (DILSOs) and fuzzy wavelet neural network (FWNN) to perform fault detection and diagnosis.

The uncertain fault system cannot be described based on the accurate differential equations. The set-value mapping is introduced into the state equations to solve the problem of uncertainty, but it will cause output uncertainty. The problem can be solved by linearization of Lur’e differential inclusion state observers. The Lur’e DILSOs can be used to detect uncertain fault. The fault isolation and estimation can be performed using the FWNN.

The mixed approach from fault detection and diagnosis has featured fast and correct to found the uncertain fault. The simulation results to indicate that the methods of design are not only effective but also have the advantages of good approximation effect, fast detection speed, relatively simple structure and prior knowledge and realization of adaptive learning.

The hybrid algorithm can be extensively applied to engineering practice and find uncertain faults of the propulsion subsystem of satellite formation promptly.

This paper provides a fast, effective and simple mixed fault detection and diagnosis scheme for satellite formation.

The purpose of this paper is to resolve complex nonlinear dynamical problems of the pitching axis of solar sail in body coordinate system compared with inertial coordinate system. And saturation condition of controlled torque of vane in the orbit with big eccentricity ration, uncertainty and external disturbance under complex space background are considered.

The pitch dynamics of the sailcraft in the prescribed elliptic earth orbits is established considering the torques by the control vanes, gravity gradient and offset between the center-of-mass (cm) and center-of-pressure (cp). The maximal torques afforded by the control vanes are numerically determined for the sailcraft at any position with any pitch angle, which will be used as the restriction of the attitude control torques. The finite/infinite time adaptive sliding mode saturation controller and Bang–Bang–Radial Basis Function (RBF) controller are designed for the sailcraft with restricted attitude control torques. The model uncertainty and the input error (the error between real input and ideal control law input) are solved using the RBF network.

The finite true anomaly adaptive sliding mode saturation controller performed better than the other two controllers by comparing the numerical results in the paper. The control torque saturation, the model uncertainty and the external disturbance were also effectively solved using the infinite and finite time adaptive sliding mode saturation controllers by analyzing the numerical simulations. The stabilization of the pitch motion was accomplished within half orbit period.

The complex accurate dynamics can be approximated using the RBF network. The controllers can be applied to stabilization of spacecraft attitude dynamics with uncertainties in complex space environment.

Advanced control method is used in this paper; saturation of controlled torque of vane is resolved when the orbit with big eccentricity ration is considered and uncertainty and external disturbance under complex space background are settled. Moreover, complex and accurate nonlinear dynamical model of pitching axis of solar sail in body coordinate system compared with inertial coordinate system is provided.

The purpose of this paper is to present kinetic equations for tether-net system during deorbiting using a novel method differing from the traditional method.

The work presents kinetic equations for tether-net system in which the tether exhibits tensional and tensionless states alternately during deorbiting. Orbital position coordinates of net-capture and abandoned spacecrafts are adopted as generalized coordinates above-mentioned instead of librations and the length of the tether. Geostationary orbit (GEO) and the orbit whose apogee is 300 km above GEO are chosen as the initial and target orbit, respectively. Simulations are conducted to study the deorbiting results considering a variety of parameters and initial conditions.

The distinctive dynamic characteristics of tether-net system can be seen by kinetic equations based on the proposed dynamic modeling strategies. Moreover, the deorbiting results are deeply affected by the initial tension force and librations showed by simulations. The initial tension force and librations should be controlled within a reasonable range.

This is expected to provide dynamic modeling strategies for space tether-net system during deorbiting. Moreover, the preliminary principle of choosing initial conditions and parameters to meet the requirements for deorbiting can be achieved.

The research proposes a novel dynamic modeling method for space tether-net system that differs from traditional tethered system, and also proposes a superior librations expression based on orbital position coordinates of net-capture and abandoned spacecrafts.

Platform-based enterprises, as micro-entities in the platform economy, have the potential to effectively promote the low-carbon development of both supply and demand sides in the supply chain. Therefore, this paper aims to provide a multi-criteria decision-making method in a probabilistic hesitant fuzzy environment to assist platform-type companies in selecting cooperative suppliers for carbon reduction in green supply chains.

This paper combines the advantages of probabilistic hesitant fuzzy sets (PHFS) to address uncertainty issues and proposes an improved multi-criteria decision-making method called PHFS-DNMEREC-MABAC for aiding platform-based enterprises in selecting carbon emission reduction collaboration suppliers in green supply chains. Within this decision-making method, we enhance the standardization process of both the DNMEREC and MABAC methods by directly standardizing probabilistic hesitant fuzzy elements. Additionally, a probability splitting algorithm is introduced to handle probabilistic hesitant fuzzy elements of varying lengths, mitigating information bias that traditional approaches tend to introduce when adding values based on risk preferences.

In this paper, we apply the proposed method to a case study involving the selection of carbon emission reduction collaboration suppliers for Tmall Mart and compare it with the latest existing decision-making methods. The results demonstrate the applicability of the proposed method and the effectiveness of the introduced probability splitting algorithm in avoiding information bias.

Firstly, this paper proposes a new multi-criteria decision making method for aiding platform-based enterprises in selecting carbon emission reduction collaboration suppliers in green supply chains. Secondly, in this method, we provided a new standard method to process probability hesitant fuzzy decision making information. Finally, the probability splitting algorithm was introduced to avoid information bias in the process of dealing with inconsistent lengths of probabilistic hesitant fuzzy elements.

This study explores the factors that characterize the logistics service quality (LSQ) of cross-border e-commerce and identifies the different relationships between these factors with respect to customer satisfaction.

The study applied a two-stage mixed-methods design. The first stage (Stage 1) was a qualitative study of 3,000 reviews from the Amazon China e-commerce platform. The second stage (Stage 2) included a quantitative study that analyzed survey data from 590 Chinese cross-border e-commerce customers using the Kano model.

Stage 1 involved developing a conceptual framework for the LSQ of cross-border e-commerce, including six dimensions: timeliness, safety, reliability, economy, personnel contact quality and information quality. In Stage 2, the study found that only reliability and personnel contact quality indicators are linearly related to customer satisfaction. Timeliness and the safety of packaging greatly contribute to customer satisfaction, but do not cause dissatisfaction when unfulfilled. Economics and information quality indicators, and the safety of goods, are basic requirements that tend to provoke customer dissatisfaction when unmet, but do not increase customer satisfaction when they are met.

This study is one of the first to construct a conceptual model of LSQ that applies to cross-border e-commerce and to identify the instrumental nature of various LSQ attributes and their impact on improved customer satisfaction.

This paper proposes a recommendation method that mines the semantic relationship between resources and combine it with collaborative filtering (CF) algorithm for crowdsourcing knowledge-sharing communities.

First, structured tag trees are constructed based on tag co-occurrence to overcome the tags' lack of semantic structure. Then, the semantic similarity between tags is determined based on tag co-occurrence and the tag-tree structure, and the semantic similarity between resources is calculated based on the semantic similarity of the tags. Finally, the user-resource evaluation matrix is filled based on the resource semantic similarity, and the user-based CF is used to predict the user's evaluation of the resources.

Folksonomy is a knowledge classification method that is suitable for crowdsourcing knowledge-sharing communities. The semantic similarity between resources can be obtained according to the tags in the folksonomy system, which can be used to alleviate the data sparsity and cold-start problems of CF. Experimental results show that compared with other algorithms, the algorithm in this paper performs better in mean absolute error (MAE) and F1, which indicates that the proposed algorithm yields better performance.

The proposed folksonomy-based CF method can help users in crowdsourcing knowledge-sharing communities to better find the resources they need.

Taking 30 provincial samples from 2001 to 2017 in mainland China as the research objects, this paper aims to evaluate the impact and effects of foreign direct investment (FDI) on the urban–rural income gap and reveals heterogeneity across regions.

Firstly, the Theil index is used to measure the income gap between 30 provinces in mainland China from 2001 to 2017, then the spatial econometric model is used to empirically test the impact of foreign direct investment on China’s urban–rural income gap and its heterogeneity across regions. Finally, a robustness test is performed.

The results show that there is a significant inverted U-shaped relationship between FDI and the urban–rural income gap in China. That is, FDI expands the urban–rural income gap in the short term and helps to converge it in the long term. In the eastern region, FDI has a convergence effect on the urban–rural income gap in the short term, which increases the long term. However, in the central and western regions, the relationship between FDI and urban–rural income gap has a weak inverted U shape.

By assessing the impact of FDI on the urban–rural income gap, this work provides decision-making support for China and other developing countries to improve investment policies and income distribution policies.

The paper proposes a two-level closed-loop supply chain (CLSC) dynamic competitive model based on different competitive cooperation situations, and explores the impact of competitive cooperation methods on the pricing strategies, recycling and remanufacturing strategies and competitive model selection strategies of supply chain firms.

This paper establishes a CLSC game consisting of a manufacturer and two retailers. Firstly, five CLSC models are established in both horizontal and vertical dimensions, each of which competes with one another. Secondly, the recycling and remanufacturing pricing strategies are analyzed under different competition or cooperation models. Finally, the results are verified through numerical analysis.

The overall profitability of the CLSC is highest when the manufacturer–retailer partnership alliance is in place. The relationship between retailers and manufacturers is also found to be the best way to achieve overall optimization of the CLSC.

The paper investigates the relationship between the competitive partnership and the total profit of the CLSC, taking into account how to optimize the overall benefit, and focusing on how to optimize the individual interests of each participating enterprise. The results can provide basis and guidance for managers' pricing decision and competition cooperation.

This study investigates the credit supervision issue in rural e-commerce. By studying the trading strategies of buyers and sellers under different credit supervision measures and the impact of different pricing strategies on the trading strategies of both parties, this paper proposes regulatory suggestions for the increasingly severe credit problems in rural e-commerce.

In the online agricultural product transaction between farmers and consumers, both parties' decision-making is a dynamic process. Using the copying dynamic model of the evolutionary game, this study establishes two evolutionary game models to explore the factors affecting credit supervision in the rural e-commerce transaction process. Then, the study provides corresponding countermeasures and suggestions.

First, credit supervision measures implemented by rural e-commerce platforms and the Government's legal system construction and infrastructure construction guarantees influence both parties' trust choices in rural e-commerce transactions. Second, price is a key factor affecting both parties' trading strategies. In the case of relatively fair prices, the higher the proportion of farmers who choose “low price” and “honest transaction” strategies, the easier that is for consumers to choose to trust farmers. In contrast, the higher the price, the higher the proportion of consumers who choose the “trust farmers” strategy, and the more willing farmers are to choose honest transactions.

This work develops a new approach for analyzing rural e-commerce credit supervision. Moreover, this study helps establish and improve the credit supervision mechanism of rural e-commerce and further realize the long-term sustainable development of the rural economy.

The purpose of this study is to examine the impact of technological diversification (TD) on enterprise innovation performance, meanwhile focusing on the moderating effects of various organizational slack (i.e. absorbed and unabsorbed slack) and ownership types (i.e. state-owned or privately-owned) in the context of Chinese listed firms.

This study formulates five hypotheses based on organization and agency theories. Our empirical analysis employs a fixed-effect regression estimator with a unique panel dataset of Chinese-listed manufacturing firms and 13,566 firm-year observations over 9 years from 2012 to 2020.

Our findings show that an inverted U-shaped relationship exists between TD and innovation performance, varying with different types of organizational slack and ownership. In state-owned enterprises (SOEs), unabsorbed slack negatively moderates the inverted U-shaped relationship; however, in privately-owned enterprises (POEs), this relationship is positively moderated. Although absorbed slack has negative moderating effects in both SOEs and POEs, its impact is only significant for POEs.

Our results imply that organizational slack has a contrasting impact on the relationship between TD and innovation performance when the type of ownership varies. Therefore, the managers that intend to achieve optimal innovation performance through TD should understand how organizational slack can be leveraged.

This study contributes to the existing literature by applying the relationship between TD and innovative performance to the transition economy, as well as examining the double-edged sword impact of state ownership on firm innovation performance.