Path Distribution Research Articles

Analysis of Urban Residents’ Travelling Characteristics and Hotspots Based on Taxi Trajectory Data

This study utilizes taxi trajectory data to uncover urban residents’ travel patterns, offering critical insights into the spatial and temporal dynamics of urban mobility. A fusion clustering algorithm is introduced, enhancing the clustering accuracy of trajectory data. This approach integrates the hierarchical density-based spatial clustering of applications with noise (HDBSCAN) algorithm, modified to incorporate time factors, with kernel density analysis. The fusion algorithm demonstrates a higher noise point detection rate (15.85%) compared with the DBSCAN algorithm alone (7.31%), thus significantly reducing noise impact in kernel density analysis. Spatial correlation analysis between hotspot areas and paths uncovers distinct travel behaviors: During morning and afternoon peak hours on weekdays, travel times (19–40 min) exceed those on weekends (16–35 min). Morning peak hours see higher taxi utilization in residential and transportation hubs, with schools and commercial and government areas as primary destinations. Conversely, afternoon peaks show a trend towards dining and entertainment zones from the abovementioned places. In the evening rush, residents enjoy a vibrant nightlife, and there are numerous locations for picking up and dropping off people. A chi-square test on weekday travel data yields a p-value of 0.023, indicating a significant correlation between the distribution of travel hotspots and paths.

When will global gender gaps close?

Global gender gaps are commonly expected to gradually close along a deterministic path over time. This paper uses Markov chains as in Quah (1993) to simulate the future dynamic path of the global distribution of gender labor force participation gaps based on country data from the last 30 years. The simulations suggest that global gender gaps will never close. A large share of countries will feature elevated gaps in the long run owing to the potential for individual episodes of increasing gaps found in the data. Absent improved and strengthened policy measures, the observed waste and misallocation of women's skills and talents may persist indefinitely.

Numerical investigation on oil leakage and migration from the accidental hole of tank wall in oil terminal of pipeline transportation system

As a crucial component of the oil transportation system, the oil terminal (or oil tank farm) may often pose some serious threats and damage to the ecological environment and production safety for the oil leakage. An effective emergency management strategy is particularly significant, involving the accurate assessment of leakage time, oil migration path, volume distribution, etc. Therefore, the volume of fluid (VOF) and liquid phase leakage model were applied to investigate the migration and distribution characteristic after the accidental hole occurs in the tank wall, and influence factors including height and diameter of the hole were considered in our study. Results show that the lower the leaking hole position is, the faster the horizontal injection rate of the leakage hole, the increase of the accumulation area of the oil on the ground, and the difference in the overall pressure value at the leakage hole is nearly four times. Under different leakage diameters, the oil spill is symmetrical. The larger the leakage diameter, the higher the amount of oil leakage and the initial leakage speed, the maximum speed is 1.5 times the minimum speed, causing harm to safety and environmental pollution. These results can quickly locate the leakage location of the tank and provide valuable references for emergency management of the oil pipeline transportation system.

Hierarchical porous Pt/Hβ catalyst with controllable acidity for efficient hydrogenation of naphthalene

A series of hierarchical porous Pt/Hβ catalysts with different mesopores-acidity were synthesized without using secondary template. The pore structures of the catalysts were altered by constructing mesopores through alkali etching to reduce the mass transfer resistance. Moreover, the metal-support interaction (MSI) was optimized to improve the dispersion of the Pt metal particles. The smaller metal species could expose more active sites during the hydrogenation process, along with a more pronounced electron-deficiency effect. Furthermore, the effect of acid sites distribution on the hydrogenation reaction path and product distribution were also investigated. The strong acid-mesopores-metal factor (X) was defined to describe the relationship with the yield of decalin. The yield of decalin was well correlated with a high R2 value of 0.97. The Pt/Hβ-75 catalyst showed the best synergistic effect between acidity, mesopore and Pt species, leading to the optimal naphthalene conversion (96.7%) and higher yield of decalin (76.7%) at a relatively low temperature, which exhibited a better activity than other catalysts reported in literature for hydrogenation of naphthalene at a similar reaction condition. Besides, the hydrogenation reaction mechanism of naphthalene over Pt supported catalysts was further investigated by density functional theory, and the effect of Pt NPs size on the catalytic reaction process and activity was preliminarily revealed.

Constraints-related microscopic fatigue crack propagation behaviour of polycrystalline alloys

Based on the microscopic polycrystalline fatigue crack propagation (MPFCP) model, the MPFCP behaviours of GH4169 alloy under different micro-notch depths and lengths (constraints) were studied from aspects of MPFCP path, MPFCP rate and stress distribution. The influences of the initial crack angle on MPFCP behaviour were further explored. It was observed that the grain boundary, the grain size and the stress state were different during crack propagation under different constraints, resulting in different MPFCP paths. The MPFCP path was straighter under high constraints, and the MPFCP rate was related to the micro-notch size and the loading direction. The crack tip needed more stress accumulation at low constraints than under high constraints to ensure smooth MPFCP behaviour. The influence of the initial crack angle on the MPFCP path was mainly reflected in the grain interior where the initial crack was located. The initial crack angle had a greater influence on the MPFCP rate than on the MPFCP path.

High Genetic Diversity in Third-Generation Cephalosporin-Resistant Escherichia coli in Wastewater Systems of Schleswig-Holstein.

The spread of multidrug-resistant bacteria from humans or livestock is a critical issue. However, the epidemiology of resistant pathogens across wastewater pathways is poorly understood. Therefore, we performed a detailed comparison of third-generation cephalosporin-resistant Escherichia coli (3GCREC) from wastewater treatment plants (WWTPs) to analyze dissemination pathways. A total of 172 3GCREC isolated from four WWTPs were characterized via whole genome sequencing. Clonal relatedness was determined using multi-locus sequence typing (MLST) and core genome MLST. Resistance genotypes and plasmid replicons were determined. A total of 68 MLST sequence types were observed with 28 closely related clusters. Resistance genes to eight antibiotic classes were detected. In fluoroquinolone-resistant isolates, resistance was associated with three-or-more point mutations in target genes. Typing revealed high genetic diversity with only a few clonal lineages present in all WWTPs. The distribution paths of individual lines could only be traced in exceptional cases with a lack of enrichment of certain lineages. Varying resistance genes and plasmids, as well as fluoroquinolone resistance-associated point mutations in individual isolates, further corroborated the high diversity of 3GCREC in WWTPs. In total, we observed high diversity of 3GCREC inside the tested WWTPs with proof of resistant strains being released into the environment even after treatment processes.

Multi‐objective optimization for optimal energy transporting path and energy distribution in electric vehicles energy internet

SummaryEnergy internet permits the power to stream lithely for broadcast and it aids in transporting energy to each user using electric vehicles (EVs). The energy that EVs utilize is generated using certain sources. Still, considering poor weather, the power station averts the production of energy and needs to acquire power transmitted to another location. One resolution is to set stations that aid to save surfeit energies and minimize energy loss during transportation. This paper devises a new model for choosing charging stations to charge EVs. Energy is transferred from the energy source to the charge station via bus station through optimal path using Battle Royale Jaya Optimization (BRJO) routing with fitness attributes like distance to select the shortest path and energy. The prediction of energy is done with a deep recurrent neural network (DRNN) and the charge is distributed optimally to EVs by employing a proposed Competitive Swarm‐Battle Royale Jaya Optimization (CSBRJO) by utilizing multi‐parameters, like priority, distance, predicted energy, waiting time, and EV count needed for charging. The CSBRJO outperformed with the smallest distance of 6.935 km, energy consumption of 1.676 J, path length of 5.05 m, and waiting time of 4.645 sec.

Research on Path Optimization of Vehicle-Drone Joint Distribution considering Customer Priority

To meet the personalized distribution needs of customers, comprehensively consider customer value, the urgency of customer needs, and the impact of priority distribution to the customer on the enterprise, and based on regional restrictions, put forward vehicle-drone joint distribution path optimization problem considering customer priority. First, the goal is to minimize the sum of total distribution cost and customer priority cost integrating soft time windows and constructing a path optimization model of the vehicle-drone joint distribution. Second, a two-stage hybrid algorithm is proposed for the problem model. In the first stage, the deep neural network and the grid search improved support vector machine algorithm (DNN-GSM-SVM) are used to screen and classify customer priority features, and in the second stage, adaptive large-scale neighborhood search improved genetic algorithms (ALNS-GA) are used to solve the problem of vehicle-drone joint distribution path planning problem. Finally, combined with the numerical example, the optimization scheme of the vehicle-drone joint distribution path considering priority is analyzed. Compared with the three algorithms and error analysis, the effectiveness of the model and the two-stage algorithm was verified. Compared with the results of the scheme that does not consider priority, the results show that priority can significantly improve customer satisfaction. The efficiency of the vehicle-drone joint distribution was verified by comparing the three scenarios.

The plasma path development model (PPDM) in rocks during rock breaking by high-voltage pulse discharge

High-voltage pulse discharge rock-breaking technology (high-voltage pulse discharge rock-breaking technology, HPDT) is widely used in the energy mining industry. In HPDT, in order to analyze the path distribution characteristics of plasma, based on the homogeneous dielectric breakdown theory, the segmental breakdown criterion for the plasma path is proposed. The plasma path development model (plasma path development model, PPDM) is established with the help of the discrete element method, finite element method, and numerical calculation method. For a typical granite-liquid combination, the development process and distribution characteristics of the plasma path inside the rock are calculated for different distances between electrodes. The results show that the fracture of rock is the result of air gap breakdown. Finally, the accuracy of the model is analyzed and the method to reduce the error is given. This work lays a foundation for quantifying the crushing efficiency of HPDT and improving its application range.

Simulation Research on Logistics Distribution Path Based on Colony Intelligence Optimisation

Abstract In light of the growing emphasis on “logistics integration,” this paper contends that the logistics network system requires comprehensive integration and optimization. We propose the use of the Bacterial Foraging Optimization (BFO) algorithm to enhance the Vehicle Routing Problem (VRP). The penalty function method is employed to direct the BFO algorithm in identifying the optimal vehicle path encoding and to improve the convergence operations for logistics distribution. This study analyzes the fundamental characteristic elements of the VRP, introduces a basic model for the VRP, and develops a logistics distribution path optimization model that minimizes the total cost by thoroughly considering the expenses associated with cold chain low-carbon logistics distribution. A simulation environment is established, and algorithm parameters are set to determine the optimal solutions for both the BFO and the Improved BFO (IBFO) algorithms in the test function. An example is selected for practical application, wherein the design of the distribution center and points is carried out, and the colony intelligence optimization algorithm is applied to simulate the logistics and distribution paths. Combined with the specific case of cold chain distribution of food, the optimization of the cold chain logistics distribution path is solved. In the case study, when the carbon penalty coefficient is ε = 15, the optimal logistics and distribution site selection program is Guangxi and Guizhou, and the total cost of the supply chain is 16,363,365.92 yuan. At this time, the supply chain cost is optimal. Compared with the carbon penalty coefficient ε = 20, the economic cost increased by 70152.24 yuan, but the carbon emission decreased by 1890.9 kg. The optimization of logistics and distribution processes encourages enterprises to develop strategies that promote low carbon and environmental protection and achieve better economic and ecological outcomes.

Mechanism Analysis of Smart Logistics Technology to Enhance the Logistics Efficiency of Rural E-Commerce

Abstract Under the advancement of reform and opening-up policy, the development direction of e-commerce enterprises has gradually shifted from the city to the rural areas with lower levels of economic development. This paper builds a rural e-commerce intelligent logistics system based on the Internet of Things (IoT) technology and proposes an improved ant colony algorithm to plan the optimal path of rural e-commerce logistics and distribution by mining the transfer probability of each distribution point in logistics and distribution as well as pheromone updating mechanism, so as to improve the logistics efficiency and customer satisfaction. Experiments show that the improved ACO algorithm in this paper performs significantly better than the genetic algorithm and particle swarm algorithm in logistics and distribution path planning and can control the transportation cost and penalty cost at a lower level. When considering the cargo loss of fresh products in logistics distribution, the satisfaction rate of traditional logistics distribution is only 65.2%, while the satisfaction rate of logistics distribution based on intelligent logistics technology is 87.9% on average. The distribution path planned by the ant colony algorithm has less mileage, lower cost, and higher logistics efficiency. This paper provides a feasible path for further improvement of rural e-commerce logistics efficiency, which can promote the development of the logistics industry in the direction of more intelligent, personalized, and green.

Research on takeaway distribution path optimisation based on genetic algorithm combined with particle swarm optimised simulated annealing

Research on takeaway distribution path optimisation based on genetic algorithm combined with particle swarm optimised simulated annealing

Mathematical problems for designing a short-distance relief goods distribution network in urban areas

In the humanitarian relief efforts after an earthquake strikes, local capabilities are critical in the first hours to assess the situation and deliver relief supplies to the victims. Usually, the relief goods required by victims are unlikely to be found in the impacted areas, and resources from other places need time to be mobilized to the affected areas. Often in earthquakes in cities in developing countries, relief goods do not arrive on time causing victims to suffer even more. In this paper, we present the mathematical formulations and solutions techniques for designing a short-distance distribution network of relief goods, which can be managed by local governments. In the preparation phase, as a part of the immediate response plan based on scenarios, the facilities location and the preliminary distribution paths must be determined. Hence, a p-median problem and a multi-depot heterogeneous fleet vehicle routing problem (MDHFVRP) must be solved. These problems are usually small and there is time to find a solution. However, in the response phase, a dynamical VRP must be solved.

Comparative Study Dynamics Analysis of a Multi-story Building with and without a Floating Column

Parking spaces, lobby areas, terrace gardens, and other amenities are highly sought-after in densely populated urban regions. Although floating columns can be useful and an achievable choice, it is important to research their structural performance and cost-effectiveness in the event of substantial ground motion imposed on by an earthquake. A building’s overall dimensions, geometry, and shape all impact how it acts and acts when subjected to seismic loads. For this reason, it is necessary to assess how well floating column buildings perform in seismically vulnerable places in comparison to conventional buildings. In this work, the performance of structures with floating columns for seismic loading is observed using dynamic analytic techniques in accordance with IS 1893 (2005). This study analyses both the floating columns and the conventional building without floating columns. When compared to a regular building, the research reveals that the floating column buildings exhibit a very quick increase in base shear and story displacement. The horizontal displacements experienced by floating column buildings are proportionally larger due to an increase in the fundamental time period. If the lateral displacement exceeds the codespecified maximum limit, damage to structural and non-structural parts may result. Because of the discontinuity in the load distribution path, seismic base shear and overturning moment are also increasing in the case of buildings with floating columns. Additionally, while asymmetrically introducing floating columns, torsional irregularity has been produced but the modal mass participation ratio has decreased. While it is true that the use of floating columns in high-rise structures allows for continuous open floor plans, they are also dangerous and susceptible in seismically active locations

Variation of Hydraulic Resistance in Pressure Pipelines of an Open-Type Hydraulic System

Pressure distributive pipelines with path distribution of fluid are part of various technical systems. Pressure losses at abrupt and smooth pipe reductions are components of total pressure losses in these pipelines. After all, the equalization of fluid distribution along the length of distributive pipelines is achieved, in particular, by reducing their diameter in the direction of flow. Depending on the configuration of the pipe reductions, pressure losses at this pipeline element can vary. For an open-type hydraulic system, a regulatory characteristics of pressure in the pipeline has been obtained with a constant fluid flow in a general form. The influence of measures necessary to change energy losses in the pipeline on the hydraulic resistance of the unregulated section of the pipeline has been taken into account. Options for these measures have been proposed for a pressure pipeline with pipe reduction.

ECONOMIC GROWTH FORECAST MODEL URBAN SUPPLY CHAIN LOGISTICS DISTRIBUTION PATH DECISION USING AN IMPROVED GENETIC ALGORITHM

The proposed way of estimating the associated macroeconomic index based on a supply chain network is a novel strategy that might give useful insights for firms and organizations trying to enhance their supply chain logistics operations. To aid in this process, the suggested technique utilizes multiple regression analysis and adaptive extreme learning machine models to determine the relative importance of each indicator in the supply chain logistics decision-making process. Firms may be able to save expenses and boost economic value by employing enhanced genetic algorithms and mathematical modeling to develop a logistics distribution model for urban supply chains based on reconstructive genetic algorithms. It is possible that the paper's study of the issues plaguing the current distribution of logistics in metropolitan areas would prove valuable to organizations that are seeking to improve their own supply chain logistics procedures. This paper appears to take a thorough strategy that might assist assure the accuracy of the forecasting method by preprocessing macroeconomic indicators using imputation, classification, and other approaches to generate a time series consistency model. Some novel ways that may shed light on logistics in the supply chain include using a two-dimensional discrete mesh structure built on wireless sensors to depict the national economic development scenario and using a coding matrix to convey the extent of economic growth. A thorough and all-encompassing way that might aid organizations in making better judgments about their supply chain logistics strategies is to employ multiple regression analysis, an adaptive extreme learning machine model, and other approaches to examine the effect degree of each key indicator. Experiments demonstrating excellent and steady prediction accuracy of the algorithm model are encouraging and point to the possible usefulness of the suggested forecasting approach. The paper's contributions, including its analysis of supply chain logistics cost accounting, determination of the basic path optimization, improvement of the genetic algorithm, and design of the mathematical model of supply chain logistics distribution path decision, all look promising in terms of their potential to help businesses cut costs and boost economic value. The positive outcome of the successful design of the mathematical model demonstrates the possible efficacy of the suggested technique.

Bawean Geotrack: Linkage Between Geodiversity, Biodiversity, And Cultural Diversity for Driving The Acceleration Bawean Island-Gresik Geopark

Bawean Island, Gresik Regency is geographically located in the Java Sea, precisely located between Borneo and Java. Currently, Bawean Island is being fought to become a Geological Heritage and continues to be developed, so that it can be proposed as a National Geopark. The Geology, Biology, and Cultural Diversity that exists on Bawean Island are still separate pieces that need further research so that it can be presented in a holistic order as geotourism. The purpose of this study is to examine geosite recommendations on Bawean Island and to reconstruct the geological history of the biological and cultural diversity of the community that developed from the past to the present in a Geosite Distribution Path Map (Geotrack). The methods used are literature review, observation of DEM imagery to determine morphology, and Geosite Potential Survey which is followed by feasibility study calculations based on parameters from the Geological Survey Center. The results of this study are in the form of a Geotrack Map consisting of 24 Geosites (15 Geodiversity, 3 Biodiversity, and 6 Cultural Diversity) which are contained in a digital system in the form of WebGIS so that all elements of society can access it. The occurrence of transgression and marine regression in the past caused by the formation of ancient volcanoes supports the formation of a typical flora and fauna ecosystem on Bawean Island. In addition, the formation of an island in the middle of the Java Sea surrounded by other cultures and civilizations led to the acculturation and cultural assimilation of the Bawean island.

Numerical simulation of hydrothermal flow in the North China Plain: A case study of Henan Province

The distribution and flow of geothermal energy in the North China region are influenced by geological structures and rock thermal properties. However, the interactions between geothermal energy, groundwater movement, and hydrogeochemical processes are not well understood. In this study, a numerical model was developed to simulate these interactions under different geological conditions. The results showed that the stress field of geological structures affects the flow path and velocity distribution of geothermal fluid, leading to distortion and uneven temperature distribution. The distribution of high-mineralized zones of geothermal water indicated the main recharge area in the northern part of the North China Basin (Henan). Hydrochemistry analysis revealed a dynamic balance between centrifugal and centripetal flows in sandstone geothermal water. The study provides important insights for the exploration and development of underground geothermal water, as well as the assessment and optimization of geothermal resources in large basins.

The Propagation Properties of a Lorentz–Gauss Vortex Beam in a Gradient-Index Medium

Based on the Huygens–Fresnel integral and ABCD matrix, the propagation equation for the Lorentz–Gauss vortex beam (LGVB) in a gradient-index medium (GRIN) is rederived. The evolution of the intensity and phase distributions of an LGVB through a GRIN medium are numerically calculated as a function of the gradient-index parameter with changes in the incident beam parameters. The results showed that the propagation path and intensity distributions changed periodically with increasing propagation distance. In contrast, phase distributions change at multiples of π/β or 2π/β, depending on whether the M values are odd or even, respectively. At the same time, the parameters of the gradient index determine the periodic values of the Lorentz–Gauss vortex beams during propagation, and as β increased, the period of evolution decreased. The Lorentz–Gauss vortex beam propagating through the gradient index will develop from a square beam to a Gaussian vortex beam more quickly with an increase of w0x=w0y. In addition, the topological charge affects the size of the dark spot at the center of the beam and the size of the beam, causing the phase distributions to change periodically in the medium. This study is beneficial for laser optics and optical communications.

Optimization of low‐carbon cold chain logistics distribution path for agricultural products based on two‐stage algorithm

AbstractWith the development of market economy, cold chain logistics has become the mainstream of the current transportation industry. Reducing transportation costs and optimizing transportation routes from an environmentally friendly perspective is the main research focus. This study starts with an emphasis on environmental protection and cost savings and optimizes existing cold chain logistics expenses. Using the clustering and annealing algorithms, the path optimization model with the lowest cost is constructed and analyzed. The K‐means algorithm is utilized to cluster and partition logistics areas, and then optimized simulated annealing algorithm is used to control and utilize logistics costs and resources. The experimental results show that the optimized algorithm reduces costs by 11.36% and increases the loading rate of the vehicle by 11.95%. The delivery time has been reduced by 18.1%. The two‐stage algorithm can optimize and improve the path model, reduce transportation costs, improve cold chain transportation efficiency, and verify the feasibility of the model.