A Comprehensive Measurement Study Analyzing Cross-Border Logistics in Harbin New District

The business environment is an important index for measuring the international competitiveness of a country or region.Improving the business environment not only helps the logistics industry reduce costs and increase efficiency but also promotes the transformation and upgrading of the logistics sector.This paper focuses on the business environment of cross-border logistics enterprises in Harbin New District as the research object.It constructs the business environment index system of logistics enterprises in Harbin New District through empirical research using the subjective weighting method.The research data are then analyzed to identify the shortcomings in optimizing the business environment of cross-border logistics in Harbin New District.The paper proposes countermeasures and suggestions,aiming to provide a decision-making reference for promoting the high-quality development and all-round revitalization of Harbin New District.

Spatial Structure of China's E-commerce Express Logistics Network Based on Space of Flows

The intermediate link compression characteristics of e-commerce express logistics ne tworks influence the tradition al mode of circulation of goods and economic organization,and alter the city spatial pattern.Based on the theory of space of flows,this study adopts China Smart Logistics Network relational data to build China's e-commerce express logistics network and explore its spatial structure characteristics through social network analysis(SNA),the PageRank technique,and geospatial methods.The results are as follows:the network density is 0.9270,which is close to 1;hence,indicating that e-commerce express logistics lines between Chinese cities are nearly complete and they form a typical network structure,thereby eliminating fragmented spaces.Moreover,the average minimum number of edges is 1.1375,which indicates that the network has a small world effect and thus has a high flow efficiency of logistics elements.A significant hierarchical diffusion effect was observed in dominant flows with the highest edge weights.A diamond-structured network was formed with Shanghai,Guangzhou,Chongqing,and Beijing as the four core nodes.Other node cities with a large logistics scale and importance in the network are mainly located in the 19 city agglomerations of China,revealing the fact that the development of city agglomerations is essential for promoting the separation of experience space and changing the urban spatial pattern.This study enriches the theory of urban networks,reveals the flow laws of modern logistics elements,and encourages coordinated development of urban logistics.

Cross-border Urban Networks Based on Manufacturing Global Value Chain:A Study of Listed Companies in Western China

Cross-border investment is essential for western China’s globalization.Global value chain(GVC)forms cross-border investment networks between industries in western China and overseas cities.Focusing on GVC,this study uses the social network analysis method,entropy method,multi-index comprehensive evaluation method,and quadratic assignment procedure analysis method to examine the characteristics and influencing factors of the urban networks of research and development(R&D),production,and sales formed as a result of the overseas investments of listed manufacturing companies in western China.Results showed that the three types of investment networks involved multiple industry types and multiple central cities with differentiated diversity and multicentrality.The R&D urban network’s leading sub-industries were the mechanical equipment and instruments,medicine and biological products,and metal and nonmetal industries.The destination cities were mostly those home to educational and scientific research centers.The production urban network’s leading sub-industries were the mechanical equipment,instrument,and food and beverage industries.The destination cities were mostly regional central cities in developing countries.The sales urban network’s leading sub-industries were the mechanical equipment and instrument,metal and nonmetal,and petrochemical and plastics industries.The destination cities were numerous and scattered.In addition,the R&D urban network easily formed specialized clusters,core nodes easily controlled the production urban network,and individual nodes did not easily control the sales urban network.Technological and economic system advantages greatly impacted the three network types.Considering the different influencing factors,this study suggests optimizing the institutional investment environment to narrow the institutional gap,adjusting and optimizing the investment layout to expand overseas markets,and increasing R&D funds to stimulate technological progress and overseas investments in western China.

A Study on Establishing a Cross-border E-commerce Logistics System for Agricultural Products in Sichuan Province in the Context of the Belt and Road Initiative

The rapid development of cross-border e-commerce,especially since Chengdu was listed as an Integrated Pilot Zone for Cross-Border E-Commerce in 2016,has led to a rising trade value of agricultural products in the metropolis.This upward trend is also attributed to the China-Europe Railway Express and the Chengdu International Aviation Hub Integrated Functional Area,two infrastructure systems that have opened more international logistics channels for agricultural products in Sichuan province.However,the development of cross-border logistics has failed to respond to the rapid growth of cross-border e-commerce for agricultural products.This problem has given rise to longer delivery cycles,higher costs,and reduced product quality,hindering the development of cross-border e-commerce for agricultural products.Currently,most research efforts are focused on selecting a logistics mode which has created an urgency is to establish a logistics system.To that end,we must utilize the opportunities and preferential policies brought about by the Belt and Road Initiative to advance the establishment of a cross-border logistics system for agricultural products,which will create more channels for selling Sichuan’s agricultural products overseas.This article analyzes the current situation of the cross-border logistics system for agricultural products produced by the province and studies the potential relationships between a logistics system and cross-border trade of agricultural products.It seeks to build a logistics system that meets the demands of cross-border transactions using economic theories focused on cross-border e-commerce and logistics.Such a logistic system will help shorten long delivery cycles,cut delivery costs,and guarantee the quality of agricultural products.Also,it can contribute to the rapid development of cross-border e-commerce of agricultural products and solve problems in developing the agricultural products logistics system of Sichuan province.

Analyzing the Construction of the International Logistics Supply Chain Management Model from the Perspective of Cross-Border E-commerce

Cross-border e-commerce has progressively evolved with the deepening of economic globalization,and it now holds a significant place in the field of e-commerce.However,due to China’s late entry into the international logistics supply chain,there are issues such as complex environment,uneven information technology,and disagreements on standards,resulting in certain cross-border e-commerce disadvantages in China.Therefore,in this context,this study analyzes the construction of international logistics supply chain management model from the perspective of cross-border e-commerce,so as to provide some reference for the development of China’s international logistics supply chain.

MODELING AND ROBUST DESIGN OF REMANUFACTURING LOGISTICS NETWORKS BASED ON DESIGN OF EXPERIMENT

The uncertainty of time, quantity and quality of recycling products leads tothe bad stability and flexibility of remanufacturing logistics networks, and general design onlycovered the minimizing logistics cost, thus, robust design is presented here to solve theuncertainty. The mathematical model of remanufacturing logistics networks is built based onstochastic distribution of uncontrollable factors, and robust objectives are presented. Theintegration of mathematical simulation and design of experiment method is performed to do sensitiveanalysis. The influence of each factor and level on the system is investigated, and the main factorsand optimum combination are studied. The numbers of factors, level of each factor and designprocess of experiment are investigated as well. Finally, the process of robust design based ondesign of experiment is demonstrated by a detailed example.

Optimization Model of Cold-Chain Logistics Network for Fresh Agricultural Products —Taking Guangdong Province as an Example

Cold-chain demand of fresh agricultural products is increasing in China, while network layout of cold-chain logistics is in disorder and its cost is huge. To address this problem, this paper casts an optimal model of cold-chain logistics network and tackles it with genetic algorithms. This optimal model takes running total cost of logistics network as the objective, and embeds a nonlinear mixed integer programming including two assignment issues. The model determines optimal layout and logistics management for pre-cooling stations and logistics center for fresh agricultural products. Our main contribution is to consider construction cost and operation cost of cold chain logistics simultaneously. Case study illustrates the effectiveness of the model.

Application of Regularized Logistic Regression and Artificial Neural Network Model for Ozone Classification across El Paso County, Texas, United States

This paper focuses on ozone prediction in the atmosphere using a machine learning approach. We utilize air pollutant and meteorological variable datasets from the El Paso area to classify ozone levels as high or low. The LR and ANN algorithms are employed to train the datasets. The models demonstrate a remarkably high classification accuracy of 89.3% in predicting ozone levels on a given day. Evaluation metrics reveal that both the ANN and LR models exhibit accuracies of 89.3% and 88.4%, respectively. Additionally, the AUC values for both models are comparable, with the ANN achieving 95.4% and the LR obtaining 95.2%. The lower the cross-entropy loss (log loss), the higher the model’s accuracy or performance. Our ANN model yields a log loss of 3.74, while the LR model shows a log loss of 6.03. The prediction time for the ANN model is approximately 0.00 seconds, whereas the LR model takes 0.02 seconds. Our odds ratio analysis indicates that features such as “Solar radiation”, “Std. Dev. Wind Direction”, “outdoor temperature”, “dew point temperature”, and “PM10” contribute to high ozone levels in El Paso, Texas. Based on metrics such as accuracy, error rate, log loss, and prediction time, the ANN model proves to be faster and more suitable for ozone classification in the El Paso, Texas area.

Multi-Feature Fusion-Guided Multiscale Bidirectional Attention Networks for Logistics Pallet Segmentation

In the smart logistics industry,unmanned forklifts that intelligently identify logistics pallets can improve work efficiency in warehousing and transportation and are better than traditional manual forklifts driven by humans.Therefore,they play a critical role in smart warehousing,and semantics segmentation is an effective method to realize the intelligent identification of logistics pallets.However,most current recognition algorithms are ineffective due to the diverse types of pallets,their complex shapes,frequent blockades in production environments,and changing lighting conditions.This paper proposes a novel multi-feature fusion-guided multiscale bidirectional attention(MFMBA)neural network for logistics pallet segmentation.To better predict the foreground category(the pallet)and the background category(the cargo)of a pallet image,our approach extracts three types of features(grayscale,texture,and Hue,Saturation,Value features)and fuses them.The multiscale architecture deals with the problem that the size and shape of the pallet may appear different in the image in the actual,complex environment,which usually makes feature extraction difficult.Our study proposes a multiscale architecture that can extract additional semantic features.Also,since a traditional attention mechanism only assigns attention rights from a single direction,we designed a bidirectional attention mechanism that assigns cross-attention weights to each feature from two directions,horizontally and vertically,significantly improving segmentation.Finally,comparative experimental results show that the precision of the proposed algorithm is 0.53%–8.77%better than that of other methods we compared.

Discrete logistics network design model under interval hierarchical OD demand based on interval genetic algorithm

Aimed at the uncertain characteristics of discrete logistics network design,an interval hierarchical triangular uncertain OD demand model based on interval demand and network flow is presented.Under consideration of the system profit,the uncertain demand of logistics network is measured by interval variables and interval parameters,and an interval planning model of discrete logistics network is established.The risk coefficient and maximum constrained deviation are defined to realize the certain transformation of the model.By integrating interval algorithm and genetic algorithm,an interval hierarchical optimal genetic algorithm is proposed to solve the model.It is shown by a tested example that in the same scenario condition an interval solution[3275.3,3 603.7]can be obtained by the model and algorithm which is obviously better than the single precise optimal solution by stochastic or fuzzy algorithm,so it can be reflected that the model and algorithm have more stronger operability and the solution result has superiority to scenario decision.

基于Logistic映射的社交网络敏感信息加密算法

为保护多种社交网络敏感信息安全,研究基于Logistic映射的社交网络敏感信息加密算法.此算法采用基于经验模态分解的社交网络信息预处理方法,以经验模态分解的方式,对复杂的社交网络信息去冗后,通过基于演化超网络的社交网络敏感信息挖掘方法,提取去冗后社交网络信息中敏感信息;由基于Logistic映射分组加密算法,生成敏感信息二进制随机序列,将其分为两部分明文,一部分明文执行置乱处理,另一部分明文执行异或运算,构建社交网络敏感信息的密文,完成社交网络敏感信息加密.实验结果表明,所提算法加密性能良好,可以有效改变文本类、图像类社交网络敏感信息,原始敏感信息特征完全改变,可保护多种社交网络敏感信息安全.

Modeling of Robust Design of Remanufacturing Logistics Networks

The uncertainty of time, quantity and quality of recycling products leads to the bad stability and flexibility of remanufacturing logistics networks, while general design only covers the minimizing logistics cost, so robust design is presented to solve it. The mathematical model of remanufacturing logistics networks is built on the stochastic distribution of uncontrollable factors, and robust objectives are presented. The basic elements of robust design of remanufacturing logistics are redefined, and each part of mathematical model is explained in detail as well. Robust design of remanufacturing logistics networks is a problem of multi-objective optimization in essence.

Logistics Mode and Network Planning for Recycle of Crop Straw Resources

To realize the straw biomass industrialized development,it should speed up building crop straw resource recycle logistics network, increasing straw recycle efficiency,and reducing straw utilization cost. On the basis of studying straw recycle process,this paper presents innovative concept and property of straw recycle logistics network,analyses design thinking of straw recycle logistics network,and works out straw recycle logistics mode and network topological structure. Finally,it comes up with construction and operation strategies of the straw logistics network from infrastructure,organization network,and information platform.

Obtain the optimal of logistics delivery network with annealing algorithm

Simulated annealing(SA) algorithm is a heuristic algorithm,proposed one approximation algorithm of solving optimization combinatorial problems inspired by objects in the annealing process of heating crunch. The algorithm is superior to the traditional greedy algorithm,which avoids falling into local optimum and reaches global optimum. There are often some problems to find the shortest path,etc in the logistics and distribution network, and we need optimization for logistics and distribution path in order to achieve the shortest,best,most economical,and so on. The paper uses an example of SA algorithm validation to verify it,and the method is proved to be feasible.

Optimization of E-commerce Logistics Network in African Countries

The purpose of this research is to assist the Central African's logistics network authorities in making,evaluating,and realizing their decisions in regard to the development and management of e-commerce logistics network of companies・This article evaluated and used mathematical models which provided a descriptive analysis on the current situation of its'logistics network while applying the e-commerce logistics network optimization method in dealing with common issues of the logistics network in Central Africa,especially Chad.The suggested network in this study would promote the^from plant-to-from DC"ratio of 83%to 17%which conforms to the companies*objective in progressing towards direct plant shipments.In regard to that,it was proved that direct plant shipments could reduce the distribution costs from 12%to 3%of the net sales(approximately$135,000 in monthly savings).

Designing a Reverse Logistics Network Model for Waste Batteries

The logistics industry plays an important role in circular economy.Therefore,not only economic benefits,but also environmental protection factors have to be considered in reverse logistics.This paper uses the multi-objective 0-1 mixed integer programming to establish a reverse logistics network optimization model for waste batteries.The objective function is to minimize both,logistics costs and carbon dioxide emissions.The model considers the basic settings of reverse logistics(including recycling nodes,manufacturing,and processing nodes)and the material flow between different settings.In solving the model,Lingo 14.0 is used in this paper.An actual case of a waste battery reverse logistics enterprise verifies the effectiveness of the model in this paper.The results show that the application of this model can effectively improve the operating efficiency of waste battery reverse logistics enterprises.

基于Logistic回归和神经网络的甘肃省道路结冰预警模型研究

为更好地开展公路交通道路结冰预报预警服务工作,利用甘肃省道路结冰高发区路段(甘肃武威以东)的交通气象站逐小时观测资料,分析道路结冰空间分布特征,探讨道路结冰与气象要素的相关性,采用Logistic回归法和神经网络算法构建道路结冰预警模型。结果表明:甘肃省道路结冰主要集中在冬季(12月至次年2月),其中00:00—10:00和22:00—23:00(北京时)出现道路结冰的频率较高。Logistic回归模型和神经网络模型对未发生结冰事件的预测准确率较高,分别为91.9%和96.2%;针对发生结冰事件,Logistic回归模型的预测准确率较低,为31.6%,而神经网络模型的预测准确率可达44.6%,说明2种模型对道路结冰预警有一定指示意义,神经网络模型预测效果优于Logistic回归模型。

糖尿病足溃疡复发风险预测模型的构建:基于Logistic回归和支持向量机及BP神经网络模型

背景全球范围内糖尿病足溃疡(DFUs)首次复发与再次复发率逐年上升,且早期复发风险高于远期风险。导致DFUs复发的风险因素较多,目前缺乏系统的筛选,因此需要探索DFUs复发的危险因素,以便早期识别复发高危人群。目的探讨Logistic回归、支持向量机(SVM)和BP神经网络(BPNN)模型在DFUs复发风险中的预测价值。方法选取2020年1月—2021年10月在宁夏医科大学总医院烧伤整形美容科、内分泌科和伤口造口门诊就诊的DFUs患者390例作为开发模型的研究对象。根据患者出院后1年内DFUs是否复发分为复发组116例(29.7%)和非复发组274例(70.3%)。收集两组患者的一般资料包括社会人口学特征、病史评估和临床病例资料并进行比较,采用糖尿病足部自我管理行为量表(DFSBS)评估患者糖尿病足部自我管理行为,采用慢性病风险感知问卷评估患者DFUs风险感知水平。采用多因素Logistic回归分析探讨DFUs患者出院后1年内DFUs复发的影响因素;将患者按照7∶3划分为训练集和测试集,运用Logistic回归变量筛选策略,分别建立Logistic回归、SVM和BPNN模型;绘制各模型预测DFUs复发风险的受试者工作特征(ROC)曲线。结果两组DFUs患者BMI、独居、糖尿病病程、吸烟史、饮酒史、受累足趾截肢史、足溃疡分级、踝肱指数、糖化血红蛋白、溃疡位置在脚底、足趾受累、足部存在行走障碍、骨髓炎、多重耐药菌感染、糖尿病周围神经病变、下肢动脉粥样硬化、足部自我管理行为、DFUs风险感知水平比较,差异均有统计学意义(P<0.05)。多因素Logistic回归分析结果显示,BMI[OR=0.394,95%CI(0.285,0.546),P<0.001]、糖尿病病程[OR=1.635,95%CI(1.303,2.051),P<0.001]、吸烟史[OR=0.186,95%CI(0.080,0.434),P<0.001]、足溃疡分级[OR=2.139,95%CI(1.133,4.038),P=0.019]、糖化血红蛋白[OR=2.289,95%CI(1.485,3.528),P<0.001]、溃疡位置在脚底[OR=3.148,95%CI(1.344,7.373),P=0.008]、足部自我管理行为[OR=0.744,95%CI(0.673,0.822),P<0.001]和DFUs风险感知水平[OR=0.892,95%CI(0.845,0.942),P<0.001]是DFUs患者1年内DFUs复发的影响因素。Logistic回归、SVM和BPNN模型在测试集中预测DFUs复发风险的正确率分别82.43%、94.87%、87.17%,ROC曲线下面积(AUC)分别为0.843、0.937、0.820。Logistic回归、SVM和BPNN模型预测DFUs复发风险的ROC曲线AUC比较,差异有统计学意义(Z=2.741,P<0.05);SVM模型预测DFUs复发风险的ROC曲线AUC高于Logistic回归和BPNN模型(Z=5.937,P=0.013;Z=3.946,P<0.001)。结论SVM模型预测DFUs患者出院后1年内DFUs复发风险的正确率、灵敏度、特异度、AUC等指标均较好,为相对最优的模型,建议进一步推广应用以验证预测模型的效能。

Optimization of causative factors using logistic regression and artificial neural network models for landslide susceptibility assessment in Ujung Loe Watershed, South Sulawesi Indonesia

Landslide susceptibility maps(LSMs) play a vital role in assisting land use planning and risk mitigation. This study aims to optimize causative factors using logistic regression(LR) and an artificial neural network(ANN) to produce a LSM. The LSM is produced with 11 causative factors and then optimized using forward-stepwise LR(FSLR), ANN, and their combination(FSLR-ANN) until eight causative factors were found for each method. The ANN method produced superior validation results compared with LR. The ROC values for the training data set ranges between 0.8 and 0.9. On the other hand, validation with the percentage of landslide fall into LSM class high and very high, ANN method was higher(92.59%) than LR(82.12%). FSLR-ANN with nine causative factors gave the best validation results with respect to area under curve(AUC) values, and validation with the percentage of landslide fall into LSM class high and very high. In conclusion, ANN was found to be better than LR when producing LSMs. The best Optimization was combination of FSLR-ANN with nine causative factors and AUC success rate 0.847, predictive rate 0.844 and validation with landslide fall into high and very high class with 91.30%. It is an encouraging preliminary model towards a systematic introduction of FSLR-ANN model for optimization causative factors in landslide susceptibility assessment in the mountainous area of Ujung Loe Watershed.