Impact of Ningbo Port Logistics on Regional Economic Development of Zhejiang Province

In related academic circles, the research on port logistics industry and regional economic development has become a hot topic in recent years, and there are already extensive studies about this topic. Taking Ningbo Port as an example, this paper analyzed its logistics development status, and discussed the existing problems. Besides, taking the time series data of Ningbo Port from 2007 to 2016 as sample data, and using the quantitative analysis methods such as correlation analysis and regression analysis, it systematically studied the interaction between the port development and regional economic development. Finally, on the basis of the problems, it came up with some recommendations.

Regional Logistics Demand Forecast Based on Least Square and Radial Basis Function

Regional logistics demand forecast is the basis for government departments to make logistics planning and logistics related policies.It has the characteristics of a small amount of data and being nonlinear,so the traditional prediction method can not guarantee the accuracy of prediction.Taking Xiamen City as an example,this paper selects the primary industry,the secondary industry,the tertiary industry,the total amount of investment in fixed assets,total import and export volume,per capita consumption expenditure,and the total retail sales of social consumer goods as the influencing factors,and uses a combining model least square and radial basis function(LS-RBF)neural network to analyze the related data from years 2000 to 2019,so as to predict the logistics demand from years 2020 to 2024.The model can well fit the training data,and the experimental results obtained from the comparison between the predicted value and the actual value in 2019 show that the error rate is very small.Therefore,the prediction results are reasonable and reliable.This method has high prediction accuracy,and it is suitable for irregular regional logistics demand forecast.

The Cooperation of Industrial Clusters and Regional Logistics of Shaanxi Province: An Evaluation Research

As a middle organization between enterprise organization which gains the competition advantage and eration of industrial clusters and regional logistics refers development of modern regional logistics. On the basis and market, industrial cluster is now the space industrial innovation advantage for a nation or a region. The coop- to improvement of industrial clusters＇ competitiveness and of reviewing the recent years＇ situation of Shaanxi Prov- ince＇s regional logistics and its industrial clusters, this paper analyzes positively about the supporting role of the regional logistics, builds gray relational model by choosing corresponding indicators, and carries out test of signif- icance. Finally it brings out strategic recommendations to and regional logistics enhance the level of cooperation of industrial clusters

Development of Agricultural Product Logistics in Tianjin in the Context of the Coordinated Development Strategy of Beijing-Tianjin-Hebei Region

Since February 26,2014,Chinese president Xi Jinping of the Central Committee of the Communist Party of China listened to the report on the coordinated development of Beijing-Tianjin-Hebei Region and delivered an important speech,and officially raised the coordinated development of Beijing-Tianjin-Hebei Region as a major national strategy,the integration of Beijing-Tianjin-Hebei Region has entered the"fast lane".Guided by accelerating the construction of agricultural product supply areas,agricultural high-tech industry demonstration areas,and agricultural product logistics center areas,Tianjin seizes the opportunity of coordinated development of Beijing-Tianjin-Hebei Region,brings into full play to the advantages of Tianjin s three-dimensional transportation network,perfect market system,high-quality port services,rapid growth of cold chain and e-commerce,to promote the faster and better development of Tianjin s agriculture.In addition,focusing on comprehensively improving Tianjin s regional agricultural product logistics service capabilities,Tianjin is establishing a distribution center for agricultural products,an e-commerce center,and a high-end agricultural product distribution center serving the Beijing-Tianjin-Hebei Region,to promote the construction of Tianjin agricultural product logistics center.

Prediction of the Logistics Demand Based on an Innovative Mixed Model: an Empirical Case from Nanping City,China

The research intends to make scientific prediction of the logistics demand of Nanping City based on mathematical model calculation so as to provide reasonable strategic guidance for the sustainable and healthy development of urban logistics industry.It constructs a comprehensive index system composed of freight volume and other eight relevant economic indices to form the foundation for the model construction.Combining forecasting models of principal component regression and GM(1,1)together,it makes mathematical calculation to predict the logistics demand of Nanping City from the years 2018 to 2022.The research makes systematical analyses of the indices influencing the precise prediction of logistics demand from a new perspective,which offers an innovative and practical option for urban logistics prediction.In line with the prediction,it offers some suggestions for the improvement of demand prediction and some strategies for the better development of the logistics industry in Nanping City.

SWOT Analysis of Agricultural Product Logistics Development——A Case Study of Shaanxi Province

SWOT method is used to analyze strengths and weaknesses in internal environment and opportunities and threats in external environment of development of agricultural product logistics in Shaanxi Province. The research indicates that the logistic development strategy of agricultural products in Shaanxi Province should bring into full play strengths in traffic, production, labor force, and science and technology. Besides, it is required to overcome weaknesses in information mechanism and management mode. Furthermore, we should take full advantage of domestic and international resources to develop famous, excellent and special products, to achieve high-efficient, rapid, and convenient development of logistics for agricultural products.

Accounting for the Effects of Climate Variability in Regional Flood Frequency Estimates in Western Nigeria

Extreme flood events are becoming more frequent and intense in recent times, owing to climate change and other anthropogenic factors. Nigeria, the case-study for this research experiences recurrent flooding, with the most disastrous being the 2012 flood event that resulted in unprecedented damage to infrastructure, displacement of people, socio-economic disruption, and loss of lives. To mitigate and minimize the impact of such floods now and in the future, effective planning is required, underpinned by analytics based on reliable data and information. Such data are seldom available in many developing regions, owing to financial, technical, and organizational drawbacks that result in short-length and inadequate historical data that are prone to uncertainties if directly applied for flood frequency estimation. This study applies regional Flood Frequency Analysis (FFA) to curtail deficiencies in historical data, by agglomerating data from various sites with similar hydro-geomorphological characteristics and is governed by a similar probability distribution, differing only by an “index-flood”;as well as accounting for climate variability effect. Data from 17 gauging stations within the Ogun-Osun River Basin in Western Nigeria were analysed, resulting in the delineation of 3 sub-regions, of which 2 were homogeneous and 1 heterogeneous. The Generalized Logistic distribution was fitted to the annual maximum flood series for the 2 homogeneous regions to estimate flood magnitudes and the probability of occurrence while accounting for climate variability. The influence of climate variability on flood estimates in the region was linked to the Madden-Julian Oscillation (MJO) climate indices and resulted in increased flood magnitude for regional and direct flood frequency estimates varying from 0% - 35% and demonstrate that multi-decadal changes in atmospheric conditions influence both small and large floods. The results reveal the value of considering climate variability for flood frequency analysis, especially when non-stationarity is established by homogeneity analysis.

Using Statistical Learning Algorithms in Regional Landslide Susceptibility Zonation with Limited Landslide Field Data

Regional Landslide Susceptibility Zonation(LSZ) is always challenged by the available amount of field data, especially in southwestern China where large mountainous areas and limited field information coincide. Statistical learning algorithms are believed to be superior to traditional statistical algorithms for their data adaptability. The aim of the paper is to evaluate how statistical learning algorithms perform on regional LSZ with limited field data. The focus is on three statistical learning algorithms, Logistic Regression(LR), Artificial Neural Networks(ANN) and Support Vector Machine(SVM). Hanzhong city, a landslide prone area in southwestern China is taken as a study case. Nine environmental factors are selected as inputs. The accuracies of the resulting LSZ maps are evaluated through landslide density analysis(LDA), receiver operating characteristic(ROC) curves and Kappa index statistics. The dependence of the algorithm on the size of field samples is examined by varying the sizes of the training set. The SVM has proven to be the most accurate and the most stable algorithm at small training set sizes and on all known landslide sizes. The accuracy of SVM shows a steadilyincreasing trend and reaches a high level at a small size of the training set, while accuracies of LR and ANN algorithms show distinct fluctuations. The geomorphological interpretations confirm the strength of SVM on all landslide sizes. Our results show that the strengths of SVM in generalization capability and model robustness make it an appropriate and efficient tool for regional LSZ with limited landslide field samples.

高质量发展视域下区域绿色物流的多重并发因果关系与多元路径

区域绿色物流是推进物流业绿色发展的重要元素,也是实现区域高质量发展和产业高级化的关键目标与突破口。运用模糊集定性比较分析方法(fsQCA),以中国30个省(市)为研究对象,基于组态视角探究高质量发展视域下区域绿色物流的多重并发因果关系与多元实现路径。结果显示:高质量发展各要素对区域绿色物流的影响具有多重并发性与地域差异性。其中,激发高水平区域绿色物流的驱动路径包括四条三类,创新是关键驱动力量;导致非高水平区域绿色物流的制约路径有五条两类,创新与绿色发展的协同作用具有重要影响。因此,提高区域绿色物流水平应从技术、资金、人才等方面全方位提升物流创新能力,从资源、环境、生态等方面加强创新与绿色的多维度互动,从各地不同情况出发制定差异化提升政策。

基于网格化Logistic回归模型的区域突发环境事件应急决策方法

针对突发环境事件不确定性较高,应急决策方案复杂,实行成本较高的问题,提出一种基于网格化Logistic回归模型的区域突发环境事件应急决策方法。利用德尔菲方法选取区域突发环境事件影响变量,以变量为输入,构建基于Logistic回归模型的区域突发环境事件发生概率计算模型,将研究区域划分为单元格形式,划分区域等级,明确安全区范围。在多个约束条件下,利用蚁群算法求取目标函数,得出最优人员疏散路径,完成应急决策方案设计。实验结果表明:该方法能够有效应对突发环境事件,且从建模至完成人员疏散的时间约0.5 h,总耗时较短,实现了区域突发环境事件应急决策,从而保障了人员和财产安全。研究对区域突发环境事件的防控具有指导意义。

辽西地区新石器时代文化空间分布特征及其演进预测研究

以辽西地区新石器时期的小河西文化、兴隆洼文化、赵宝沟文化、红山文化和小河沿文化遗址为研究对象,使用ArcGIS软件对各文化时期遗址数据进行提取,借助Logistic回归分析方法构建辽西地区新石器时期遗址的分布预测模型,得出遗址分布与海拔高程等自然地理要素之间的关系,生成辽西地区新石器时期遗址分布概率图。研究结果表明,辽西地区新石器时期聚落选址与自然地理要素关系密切,河流对遗址分布影响较大,海拔高程、坡度影响其次,坡向影响最弱。遗址预测模型显示较高概率分布区集中分布于距离河流较近的河谷、丘陵地带和地势较高的台地。预测模型可为探讨辽西地区史前人地关系演变提供重要参考,为考古发掘工作提供科学判断与决策支持,提高考古工作效率。

长三角城市群物流业高质量发展水平测度研究及评价

以长三角城市群物流业为研究对象,采用熵权TOPSIS法和核密度估计分析方法,测度2010—2021年长三角城市群物流业高质量发展水平并分析区域发展差异。研究发现:长三角城市群物流业高质量发展水平向好趋势明显,但仍然有待提高。有18个城市的物流业高质量发展水平低于均值。其中上海的物流业高质量发展水平最高,居于第2位的苏州相比于上海还有较大差距。从各区域来看,区域发展不均衡的特征较明显,各区域物流业高质量发展水平存在一定差距,上海物流业高质量发展水平显著高于其他区域,物流业高质量发展水平排名靠后的城市主要集中在安徽,该区域内发展差距呈现缩小趋势。

竞争态势下区域生态物流科技资源配置协同演化模型构建研究

优化行业科技资源配置是推动物流业科技创新的关键,是其走现代化转型的必经之路。文章以区域物流生态系统作为研究对象,将科技资源配置效率作为外生变量来缓解种群内竞争强度,改进了传统的Lotka-Volterra模型。借助该模型推导了物流种群间竞争关系的四种约束条件以及产生的对应竞争态势,以不同物流种群竞争共存为目标,根据推导的约束条件,通过MATLAB软件进行了仿真计算。结果表明,在满足约束条件的基础上,物流种群间竞争的共存会产生两种不同结果。据此,建议政府可以将科技资源配置效率作为抓手来进一步推动“赛马”机制在生态物流行业中的应用。

区域智慧物流发展水平评价指标体系构建

在对国内外区域物流、区域智慧物流评价体系相关研究进行综述的基础上,结合评价指标体系构建中存在的问题,遵循指标选取的原则,从物流经济、物流基础设施、物流业务量以及智慧物流中的“智慧”4个维度,构建了包括4个一级指标和24个二级指标的区域智慧物流发展水平评价指标体系,完善了以往的相关指标。在此基础上,建立了基于熵权-灰色度关联法的区域智慧物流发展水平评价模型,提出了评价思路,基于天津市、深圳市、上海市、宁波市、武汉市和郑州市等六个地区2020-2022三年的相关数据,对其智慧物流发展水平进行了评价,本研究可以为我国区域智慧物流发展提供导向。

浙江省区域物流网络构建与鲁棒性分析

文章为构建浙江省区域物流网络,分析各城市物流发展水平,利用修正后的引力模型,量化城市之间的物流联系强度,并在此基础上结合复杂网络,分析该省区域物流网络的拓扑结构。为防止突发事件造成该省物流网络瘫痪,文章利用Python工具,通过随机攻击、蓄意攻击和基于贪心策略的蓄意攻击三种攻击方式,对区域物流网络进行分析比较。研究发现,浙江省不仅地级市可以带动物流发展,一部分市级以下地区的物流发展能力也较强,同样可以带动物流发展。从物流鲁棒性仿真模拟分析来看,基于贪心策略的蓄意攻击方式对物流网络的影响最大,针对物流发展较好的城市应得到重点保护,防止网络瘫痪。