Landslides are one of the most widespread natural hazards that cause damage to both property and life every year. Therefore, the landslide susceptibility evaluation is necessary for land hazard assessment and mitigation of landslide-related losses. Selecting an appropriate mapping unit is an essential step for landslide susceptibility evaluation. This study tested the back propagation (BP) neural network technique to develop a landslide susceptibility map in Qingchuan County, Sichuan Province, China. It compared the results of applying six different slope unit scales for landslide susceptibility maps obtained using hydrological analysis. We prepared a dataset comprising 973 historical landslide locations and six conditioning factors (elevation, slope degree, aspect, lithology, distance to fault lines, and distance to drainage network) to construct a geospatial database and divided the data into the training and testing datasets. We based on the BP learning algorithm to generate landslide susceptibility maps using the training dataset. We divided Qingchuan County into six different scales of slope unit: 4,401, 13,146, 39,251, 46,504, 56,570, and 69,013, then calculated the receiver operating characteristic (ROC) curve, and used the area under the curve (AUC) for the quantitative evaluation of 6 different slope unit scales of landslide susceptibility maps using the testing dataset. The verification results indicated that the evaluation generated by 56,570 slope units had the highest accuracy with a ROC curve of 0.9424. Overelaborate and rough division of slope units may not get the best evaluation results, and it is necessary to obtain the slope units most consistent with the actual situation through debugging. The results of this study will be useful for the development of landslide hazard mitigation strategies.

Most of the public-private partnership (PPP) projects have entered the operational period in China. Due to information asymmetry, opportunistic behavior exists in the operation period of PPP projects. The opportunistic behavior of the participating subjects is an obstacle to the success of PPP projects and one of the root causes of low project performance. To investigate the evolutionary law of this behavior, the payment matrix of the strategic interaction between the investors and the government is constructed based on evolutionary game theory. Using MATLAB to simulate the evolutionary state and through the analysis of the evolutionary behavior of the interaction process, the influence of individual strategy choice on group behavior is revealed. The results show that the path evolution system of opportunistic behavior during the operation period of PPP projects can converge in two states, “good” and “bad,” and the determining factor is the relative returns of investors under various strategies. Reasonable incentives and penalties and reduced regulatory costs can effectively discourage opportunistic behavior. By regulating the parameters, the path evolution of opportunistic behavior can be optimized, and the group behavior can be induced to a good state. The research results can provide a reference for reducing the opportunistic behavior of participating subjects and improving the success rate of the PPP projects.

Existing railway line (ERL) construction safety has received significant attention during the past decades due to the high accident rate and the difficulty of progress development under the limited synthesis construction time schedule (SCTS). However, the previous literature is dominated by the construction safety of new railway lines, while research on construction safety of ERLs is limited. This paper analyzed the interactions and causal relationships between construction safety risk (CSR) and multiple factors and classified feedback loops. Hence, a system dynamics model was developed, and a series of tests were conducted to simulate the evolution of CSR under different group environments. The results indicated that (1) the CSR considering ERLs is significantly relevant to the implementation degree of SCTS. For situations where there are more delays and more schedule pressure, construction safety accidents tend to have a higher level. (2) Work efficiency is negatively related to construction safety accidents probability. The increase of work intensity could reduce schedule pressure in the short term but could increase construction safety risk in a long time. Applying both appropriate work efficiency and work intensity may achieve an acceptable result. This paper adds to the knowledge of construction safety risk management in terms of implementation and offers lessons and references for future construction safety management considering ERLs.

Dam failure can trigger cascading consequences involving human safety, economic losses, social disruption, and environmental damage. Accurate assessment of these consequences remains challenging due to uncertainties associated with indicator selection, expert judgment, and consequence classification. To address these issues, this study develops an integrated model for evaluating dam failure consequences under uncertainty. A multidimensional evaluation index system consisting of life loss, economic loss, social impact, and environmental impact is established based on existing studies and expert knowledge. The hesitant cloud model is combined with an improved entropy weight method to represent the hesitancy in expert evaluations and to improve the rationality of indicator weight determination. Furthermore, set pair analysis is introduced to evaluate the uncertain relationships between assessment indicators and consequence levels. The proposed model is applied to a reservoir case in China to verify its applicability. The results indicate that the first cumulative membership value, obtained by cumulatively summing the dam failure consequence grades from “slight” to extremely severe”, that exceeds the confidence level λ is 0.7799, corresponding to the severe consequence level. This result is consistent with the comprehensive evaluation obtained using the cloud matter element method. Compared with the traditional method, the generalized set pair potential avoids the case where the opposition degree (c) equals 0. The proposed approach improves the representation of uncertainty and reduces the influence of unclear boundaries among evaluation levels. This study provides a practical decision support tool for dam failure consequence assessment and reservoir risk management.