Superblocks are city blocks whose size is significantly larger than average. Despite their widespread use across countries such as China, few studies have investigated how these superblocks affect network traffic performance. This paper aims to narrow that gap in knowledge. To that end, we use a grid network emulating a dense city environment. Then, multiple scenarios corresponding to size, location, shape, and number of superblocks are designed by removing nodes and related links. We evaluate network traffic performance by considering the factors of travel distance, travel time, volume-to-capacity ratios on nodes and links, as well as the level of traffic heterogeneity. The results indicate that superblocks with relatively small size (i.e. less than 1/4 of the network size) do not affect traffic significantly. The importance and connectivity of nodes and links related to superblocks are crucial factors affecting the overall traffic performance. In general, the more central the superblock, the larger its influence on the network traffic, except for extremely large superblocks that can significantly affect traffic when located in the periphery, as they lead to high traffic heterogeneities. Rectangular superblocks are more detrimental than square ones. Furthermore, traffic performance can be significantly improved by dividing the superblock into several relatively smaller blocks. Our results should be of direct interest to city-planning decision-makers in dense urban centers.

To analyze the topological properties of hazardous materials road transportation network (HMRTN), this paper proposed two different ways to construct the cyberspace of HMRTN and constructed their complex network models, respectively. One was the physical network model of HMRTN based on the primal approach and the other was the service network model of HMRTN based on neighboring nodes. The two complex network models were built by using the case of Dalian HMRTN. The physical network model contained 154 nodes and 238 edges, and the statistical analysis results showed that (1) the cumulative node degree of physical network was subjected to exponential distribution, showing the network properties of random network and that (2) the HMRTN had small characteristic path length and large network clustering coefficient, which was a typical small-world network. The service network model contained 569 nodes and 1318 edges, and the statistical analysis results showed that (1) the cumulative node degree of service network was subjected to power-law distribution, showing the network properties of scale-free network and that (2) the relationship between nodes strength and their descending order ordinal and the relationship between nodes strength and cumulative nodes strength were both subjected to power-law distribution, also showing the network properties of scale-free network.

The unblocked reliability of urban road network directly impacts the effectiveness of city traffic management. First, a bi-level programming model based on the urban road network unblocked reliability concept is presented, and its upper-level model is to minimize the total investment and make the network to be system optimization at the same time, the lower-level model is a standard network equilibrium model satisfying WORDRAP's first equilibrium rule. Then, a GA is adopted to solve this problem. Finally, the network of JinFu intersection in ChengDu has been regarded as an example to verify the validity and feasibility of model and algorithm, explaining the research of unblocked reliability can provide technology and decision-making support for urban road network planning management.

The development of China's logistics Industry has been affected by many factors in its exterior service circumstance, system dynamics method has been used to analyze the relationships of theirs from the new angle. Via this way, a systemic frame has been presented. We can get the result that logistics industry and some factors of its service circumstance, such as market demand & supply, logistics infrastructure, service price and industry policy, are interactive and restrictive. There exists some basic positive or negative feedback loop

To tackle the pronounced temporal dynamics and intricate interdependencies within process manufacturing knowledge, this paper introduces an innovative framework: the Adaptive Multi-Scale Temporal Path Fusion Network (AMTPFNet). The method constructs short-term (high-frequency) and long-term (low-frequency) historical subgraphs to generate multi-scale temporal representations. It also employs a self-attention mechanism for query-aware temporal path modeling, enabling adaptive weight allocation based on varying time spans. Extensive experiments are conducted on benchmark datasets, including ICEWS18, GDELT, WIKI, and YAGO. Additionally, an application analysis is presented using electromechanical fault data. The results demonstrate that AMTPFNet exhibits remarkable effectiveness and robustness in temporal knowledge graph reasoning tasks, achieving MRR scores of 0.914 on YAGO and 0.838 on WIKI. It achieves high efficiency in predicting future production facts and assessing process quality in industrial workflows. Root causes of failures (e.g., insulation, friction) for motor components (stators, rotors) are accurately predicted, demonstrating the framework’s transferability to real-world manufacturing scenarios. Although electromechanical fault data are used as a case study, the framework generalizes to manufacturing quality prediction and is readily transferable to finance, healthcare, and social media analytics.

Railway passenger comfort value is determined by a combination of physical and psychological factors. Comfortable passenger transport environment can be regarded as a resource for social consumption, and passenger travel comfort benefits can be regarded as a special generalized cost. The improved railway passenger comfort benefit (IRPCB) is a key evaluation index for newly-built railway projects, which can be regarded as the passenger comfort benefit difference before and after the newly-built railway project. However, the important value is neglected during the actual engineering practice, because the existing calculation approach is incomplete and the basic data is hard to obtain. In this paper, we propose a new IRPCB quantitative calculation method based on passenger candidate time value set. First, we establish the suitable railway passenger candidate time value set after analyzing and summarizing the railway passenger time value calculation methods and application conditions. Then, we multiply the passenger fatigue recovery time and the passenger time value selected from the candidate time value set. Next, the multiplication difference before and after the newly-built railway project will be calculated as the IRPCB value. A numerical experience is carried out by taking the Beijing-Shanghai passenger corridor in China as a background in order to test the performance of the approach presented in this paper.