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To address the shortcomings of the traditional back propagation (BP) neural network agent model, such as insufficient fitting accuracy and low computational efficiency, an improved method is proposed.

In this study, an improved sparrow search algorithm (ISSA) is developed to optimize the reliability calculation of the BP neural network (ISSA-BP) using an enhanced BP neural network model. The traditional sparrow search algorithm is enhanced by incorporating a golden sine strategy to improve its position-updating mechanism, thereby overcoming its tendency to converge prematurely to local optima. Additionally, an opposition-based learning strategy is integrated to explore the reverse solution around the optimal solution of the sparrow search algorithm, mitigating the risk of local optima.

The results of the test function demonstrate that the proposed method significantly enhances fitting accuracy while maintaining computational efficiency. Finally, by applying this approach to the metro bogie frame as a case study, the structural reliability of the bogie frame is evaluated using the Monte Carlo method, providing valuable insights for subsequent analysis and structural optimization.

The use of the surrogate model approach for structural reliability analysis significantly improves solution efficiency. Furthermore, the integration of ISSA with the BP neural network enhances both fitting accuracy and computational efficiency, demonstrating the superiority and practicality of the proposed method.

In response to the common low sensitivity of fiber Bragg grating (FBG) temperature sensors in measurement, an FBG temperature sensor sensitized in a substrate-type package structure is proposed.

The sensitivity of sensors is analyzed theoretically; aluminum alloys with large coefficient of thermal expansion are used; the ANSYS software is used for simulation analysis and optimization design of sensors; real sensors are developed based on simulation results; in this study, a test system was built to test the performance of the proposed sensor.

The results suggested that the sensitivity of encapsulated FBG temperature sensor is 27.3 pm/°C in the range of −20 °C to 40 °C, which is 2.7 times that of bare FBG sensor, while the linearity is up to more than 0.99.

The sensitivity of FBG temperature sensor is greatly improved by the design of the structure.

This study innovatively proposes substrate-type sensitized FBG temperature sensor. The temperature sensitivity of fiber grating can be improved by single metal structure, and the effect of structural strain can be reduced by a tab structure. The study results provide a reference for the development of like sensors and the further improvement in the sensitivity of FBG temperature sensors.

Following the call to explore what leadership theory could be applicable in temporary organizations, the purpose of this study was to develop an integrative model linking the effects of paternalistic leadership styles (i.e. authoritarian, benevolent and moral) on the behavioral integration (BI) of top management teams (TMTs) in megaproject settings.

The performance of the research model was tested based on empirical data collected from a sample of 43 megaproject TMTs.

The results show that the moral leadership style can significantly stimulate the BI of TMTs, whereas authoritarian leadership has a negative impact and benevolent leadership has no significant impact. Furthermore, trust in leader plays a partial mediating role between paternalistic leadership and BI, and the power distance value of TMT positively moderates the links between authoritarian and moral leadership styles and BI.

The TMT sample was drawn from China's megaprojects, most of which have global influence (e.g. Hong Kong–Zhuhai–Macao Bridge and Shanghai Expo), but the sampling approach limits the generalizability of the research findings to other contexts.

This study introduces the concept of BI into the realm of megaproject management and provides a novel perspective (i.e. paternalistic leadership) for exploring its antecedents. The findings, therefore, contribute to the literature by broadening the megaproject management research with a microfoundation perspective and by extending the extant paternalistic leadership in the context of temporary organizational settings.

The purpose of this paper is to analyze the relationship between the demographic characteristics of top management teams (TMTs) (i.e. age, gender, administrative level, senior management experience and educational background) and megaproject performance, with respect to schedule, cost, quality, safety and technological innovation. The results shed new light on the effectiveness of different types of TMT.

This paper collected secondary and objective data from 208 TMT members in 42 megaprojects and employed hierarchical regression analysis to test the research hypotheses.

The findings revealed that age has a significant influence on schedule performance; gender has a significant influence on safety performance; senior management experience has a significant influence on cost performance; and educational background has a significant influence on both schedule and technological innovation performance. However, this study did not find evidence of a significant relationship between the administrative level and megaproject performance.

This paper mainly focused on China’s megaprojects, most of which are globally influential (e.g. Hong Kong–Zhuhai–Macao Bridge and Shanghai Expo), however this sampling approach still limits the generalizability of research findings to other contexts.

The results of this paper contribute to a better understanding of how management team capabilities translate into better project achievements. This paper also provides implications on the criteria for selecting top megaproject managers to optimize the composition of the TMT and realize better performance.

Organizational citizenship behaviors for the environment (OCBEs) represent a crucial element of environmental sustainability for a wide range of organizations. However, the leadership mechanisms underlying OCBEs are as yet unexplored, particularly regarding the delivering megaprojects. The paper aims to investigate how transformational leadership (TFL) and transactional leadership (TSL) styles shape the environmental commitment (EC) of subordinates, motivating OCBEs in megaprojects.

Partial least squares modeling and hierarchical regression were performed on data obtained from 140 experts who have been involved in megaprojects.

Both TFL and TSL styles are effective in motivating OCBEs, although the EC of subordinates partially mediates these relationships. The power distance (PD) orientation significantly moderates the relationship between TFL and OCBEs, with the relationship being more positive when the PD of subordinates is lower. Unexpectedly, a collectivist orientation (CO) was found to elevate the effect of TSL but weaken the effect of TFL.

The mixed and contradictory findings regarding TFL and TSL styles are reconciled in the current study by integrating the contextual factors of PD and CO. The findings of the study shed new light on “playing the cards right” when using the leadership practices, i.e. how leadership can be better leveraged to cultivate subordinates' OCBEs. They also provide targeted guidance for shaping contextual factors to increase the environmental sustainability of megaprojects.

The purpose of this paper is to explore and compare haze-related content between traditional and social media in China by applying agenda-setting theory and the extended parallel process model (EPPM). Specifically, this paper examines the correlation between the two forms of media in terms of the ranking of the attributes of haze (i.e. the EPPM components) and the interrelationships among the attributes.

Content analysis and semantic network analysis were employed to address the research aims.

The results revealed that more than half of the total messages on both types of media reflected the EPPM components, either threat or efficacy information. However, the imbalance between the threat and efficacy information was more prominent in the haze-related content presented in the People’s Daily than it was on Weibo. In addition, the results from a Spearman’s rank-order correlation and a quadratic assignment procedure (QAP) indicated that there was no significant correlation between the People’s Daily and Weibo in terms of the rankings of the attributes of haze (i.e. the EPPM components) or the interrelationships among the attributes.

This study is the first to apply a theoretical approach to examine and compare the nature of haze-related messages on traditional and social media.

This study aims to propose a cooperative adhesion control method for trains with multiple motors electric locomotives. The method is intended to optimize the output torque of each motor, maximize the utilization of train adhesion within the total torque command, reduce the train skidding/sliding phenomenon and achieve optimal adhesion utilization for each axle, thus realizing the optimal allocation of the multi-motor electric locomotives.

In this study, a model predictive control (MPC)-based cooperative maximum adhesion tracking control method for multi-motor electric locomotives is presented. Firstly, train traction system with multiple motors is constructed in accordance with Newton’s second law. These equations include the train dynamics equations, the axle dynamics equations, and the wheel-rail adhesion coefficient equations. Then, a new MPC-based multi-axle adhesion co-optimization method is put forward. This method calculates the optimal output torque through real-time iteration based on the known reference slip speed to achieve multi-axle co-optimization under different circumstances.

This paper presents a MPC system designed for the cooperative control of multi-axle adhesion. The results indicate that the proposed control system is able to optimize the adhesion of multiple axles under numerous different conditions and achieve the optimal power distribution based on the reduction of train skidding/sliding.

This study presents a novel cooperative adhesion tracking control scheme. It is designed for multi-motor electric locomotives, which has rarely been studied before. And simulations are carried out in different conditions, including variable surfaces and motor failing.

To better meet people's information needs under the public health crisis, this study explored the information needs and seeking behavior of college students in the context of the COVID-19 pandemic.

This research utilized a survey and the convenience snowball sampling method. A sample of 400 college students was obtained.

The results revealed that college students have paid great attention to COVID-19-related information. They sought the information mainly for personal protection, obtaining the latest information and seeking information for family and friends. Their COVID-19-related information needs were diverse; at different stages, the concerns were different. Social media and mass media were both found to be the most useful tools for seeking COVID-19 information. Too much repetitive information, unclear authoritative and reliable informational sources, and difficulties in judging the authenticity of the information were the most common obstacles for them in information seeking. Nevertheless, the majority of the students agreed that they were very satisfied and somewhat satisfied with the current information services. This did not affect the students' understanding of the importance of health services provided by libraries.

Insights into the people's information needs and information-seeking behavior of this study could help the information providers to offer appropriate information in better ways to improve the public's virus protection capabilities and maintain the stability of social order.

In a mobile ad hoc network (MANET), design of energy‐efficient routing schemes is essential for prolonging the network lifetime. The purpose of this paper is to show that one way to achieve energy efficiency in routing is to utilize location information, which becomes practical due to the recent increasing availability of low‐cost and reliable positioning devices.

This paper proposes an eight‐direction forwarding virtual grid aided (VGA) routing scheme that uses location information to save energy. As a grid‐based scheme, VGA divides the whole network area into virtual grids.

By using eight‐direction forwarding, the proposed VGA scheme outperforms the previous four‐direction forwarding geographical adaptive fidelity (GAF) protocol. The proposed VGA scheme is motivated by the fact that, in the GAF protocol, forwarding to the four diagonal neighboring grids cannot be done in one single hop, although most nodes in these grids can hear the signal.

Theoretical analysis shows the eight‐direction forwarding protocol performs better than the four‐direction one unless the forwarding direction has an angle of less than 15^○ with the horizontal or vertical grid axis. Simulation supports the fact that the eight‐direction forwarding VGA scheme has better energy performance than the four‐direction forwarding GAF scheme without sacrificing any routing performance.

Conventional theories of market entry assume choice availability. This investment assumption is subject to challenges in the power generation market of an emerging economy where the host government controls most key resources and market entry choices. With such constraints, entrants become heavily dependent on their host country partners. This study investigates how the resource dependency frameworks explain better in respect of some US power generation firms that manage to operate electricity facilities in China whereas some have to abort. Using cross‐case analysis, patterns emerged illustrate how two groups of entrants manage key resources differently.