Problems and Countermeasures of Fruit and Vegetable Logistics Distribution Development in Guangxi Zhuang Autonomous Region

The logistics transportation and distribution of fruits and vegetables has become one of the important links for people to obtain food,and it is also an important direction and emerging challenge in the logistics industry.As the social economy and transportation develop,the consumption ability of residents has been improved,and the high demand for fruits and vegetables has promoted the transportation of fruits and vegetables to meet the development conditions of the future fruit and vegetable industry.The study of fruit and vegetable logistics distribution can improve the efficiency of fruit and vegetable distribution,improve the construction of fruit and vegetable distribution system,and also meet the needs of people for different kinds of fruits and vegetables.Taking Guangxi fruit and vegetable distribution as an example,through empirical investigation,this paper studies the existing problems in the development of logistics distribution in the fruit and vegetable distribution industry,and puts forward corresponding measures and countermeasures according to the problems,so as to innovate the fruit and vegetable distribution mode in Guangxi Zhuang Autonomous Region.

Temporal-spatial Distribution Model of Cold Chain Logistics for Vegetables

[Objective] The aim was to study on temporal-spatial distribution model of cold chain logistics for vegetables. [Method] Broccoli was taken as an example. Detailedly, time-space distribution model of cold chain logistics for broccoli was proposed from standpoints of costs and benefits based on changes of time and space, and a comprehensive evaluation was made on timeliness, efficiency, risks, added- value of products and satisfaction of information in cold-chain logistics. [Result] The efficiency of cold chain logistics for vegetable can be greatly improved by temporal- spatial distribution model of cold chain logistics. [Conclusion] Costs and benefits of vegetables in temporal-apstial distribution could be evaluated by the model.

Lung Cancer Segmentation with Three-Parameter Logistic Type Distribution Model

Lung cancer is the leading cause of mortality in the world affectingboth men and women equally.When a radiologist just focuses on the patient’sbody, it increases the amount of strain on the radiologist and the likelihoodof missing pathological information such as abnormalities are increased.One of the primary objectives of this research work is to develop computerassisteddiagnosis and detection of lung cancer. It also intends to make iteasier for radiologists to identify and diagnose lung cancer accurately. Theproposed strategy which was based on a unique image feature, took intoconsideration the spatial interaction of voxels that were next to one another.Using the U-NET+Three parameter logistic distribution-based technique, wewere able to replicate the situation. The proposed technique had an averageDice co-efficient (DSC) of 97.3%, a sensitivity of 96.5% and a specificity of94.1% when tested on the Luna-16 dataset. This research investigates howdiverse lung segmentation, juxta pleural nodule inclusion, and pulmonarynodule segmentation approaches may be applied to create Computer AidedDiagnosis (CAD) systems. When we compared our approach to four otherlung segmentation methods, we discovered that ours was the most successful.We employed 40 patients from Luna-16 datasets to evaluate this. In termsof DSC performance, the findings demonstrate that the suggested techniqueoutperforms the other strategies by a significant margin.

Application of Robust Strategies in Location Selection of Logistics Distribution Center for Fresh Agricultural Products

In view of the uncertainty in the location selection of logistics distribution center for the fresh agricultural products,the present study established a robust model based on the maximization of principal component score taking budget cost parameters as an example.In the process of model solving,the interval form of the uncertain set was used to clarify the constraint conditions,to transform into a certain 0-1 integer linear programming model,so as to solve with the aid of LINGO software.Finally,through studying the location selection of logistics distribution center for fresh agricultural products in the Beijing-Tianjin-Hebei region,it analyzed the application of the robust model and tested the validity of the model.

Study on Location of Wuhan Steel Logistics Distribution Center

This paper studies the location of Wuhan steel logistics distribution center. First of all, according to Wuhan Iron and Steel Plant sales in Hunan Province and the relative position of the city, the transport costs are calculated from Wuhan Iron and Steel Plant to the demand point. We further analyze the necessity of establishing steel logistics distribution center, using the precise center of gravity to determine the actual location of the distribution center. After the establishment of distribution center, the total freight is reduced by 15.46 million yuan from Wuhan Iron and Steel Plant to each city in Hunan province via distribution center each year. The results of this paper can provide theoretical basis for the logistics node planning of related enterprises.

An Uncertain Programming Model for Competitive Logistics Distribution Center Location Problem

We employ uncertain programming to investigate the competitive logistics distribution center location problem in uncertain environment, in which the demands of customers and the setup costs of new distribution centers are uncertain variables. This research was studied with the assumption that customers patronize the nearest distribution center to satisfy their full demands. Within the framework of uncertainty theory, we construct the expected value model to maximize the expected profit of the new distribution center. In order to seek for the optimal solution, this model can be transformed into its deterministic form by taking advantage of the operational law of uncertain variables. Then we can use mathematical software to obtain the optimal location. In addition, a numerical example is presented to illustrate the effectiveness of the presented model.

Research on Optimizing the Distribution Path of Agricultural Cold Chain Logistics in Green Consumption Era

In recent years, with the rapid development of China's fresh market, cold chain logistics ushered in a new development opportunity. Because of the late start and slow development of cold chain logistics in China, it is difficult to achieve cross-regional and offseason sales activities, resulting in a situation of high output and small sales volume, which is also an important reason for the high price and poor quality of fresh agricultural products. With the passage of time, the characteristics of cold chain distribution of agricultural products have become an important direction for the future development of logistics industry. In this paper, aiming at the characteristics of agricultural cold chain distribution, the carbon emissions in the process of distribution were quantified as costs and added to the total cost, and an optimization model of agricultural cold chain logistics path with time window considering the minimum total cost as the objective function was constructed. The improved genetic algorithm was used to solve the problem. The simulation results show that the improved genetic algorithm is an effective method to solve the optimization problem of agricultural cold-chain logistics path considering carbon emissions, and has guiding significance for the selection of low-carbon and environmentally friendly distribution routes for agricultural cold-chain logistics distribution enterprises.

Exploring Hybrid Genetic Algorithm Based Large-Scale Logistics Distribution for BBG Supermarket

In the large-scale logistics distribution of single logistic center,the method based on traditional genetic algorithm is slow in evolution and easy to fall into the local optimal solution.Addressing at this issue,we propose a novel approach of exploring hybrid genetic algorithm based large-scale logistic distribution for BBG supermarket.We integrate greedy algorithm and hillclimbing algorithm into genetic algorithm.Greedy algorithm is applied to initialize the population,and then hill-climbing algorithm is used to optimize individuals in each generation after selection,crossover and mutation.Our approach is evaluated on the dataset of BBG Supermarket which is one of the top 10 supermarkets in China.Experimental results show that our method outperforms some other methods in the field.

基于Logistic回归的国际时尚品牌销售渠道选择影响因素分析

为了帮助国际时尚品牌合理、科学地选择销售渠道和制定销售策略,以满足不同地区不同类型消费者的需求,提高品牌市场竞争力。首先依据访谈数据确定分析因子,建立影响国际时尚品牌销售渠道选择的多因素分析理论模型,提出可能影响国际品牌销售渠道选择的消费者偏好分析指标体系,从消费者个人特征、心理偏好、品类偏好以及时尚认知4个维度设计问卷并进行调研。运用SPSS软件对问卷回收数据进行录入,并采用Logistic回归分析数据,从而验证模型假设。通过分析结果可知,以上4个维度下的诸多影响因子均对国际品牌销售渠道的选择产生显著影响,并给出了具体的指导策略。品牌商可以根据研究结果制定对应的销售策略,以有效提高销售渠道利用率,最大化提升品牌销售业绩。

Performance Appraisal Method of Logistic Distribution for Fresh Agricultural Products

Through the initial selection,screening and simplification,a set of performance appraisal system of logistic distribution suited to fresh agricultural products is established.In the process of establishing the appraisal indicator,the representative appraisal indicator of logistic distribution of fresh agricultural products is further obtained by delivering experts' survey and applying the ABC screening system.The distribution costs,transportation and service level belong to the first level indicator;packing fees,distribution processing fees,full-load ratio,haulage capacity,customer satisfaction and the strain capability of delivery personnel belong to second level indicator.At the same time,the weighing of each indicator is determined.The quantification is conducted on indicators.The qualitative indicators applies ten-point system and then coverts these indicators into percentage,that is the number between [0,1];as for the quantitative indicators,they are concluded to the interval [0,1] according to the actual value range of the indicators and by applying the grade of membership in the vague mathematics.Through the analyses of the advantages and disadvantages of the frequently used performance evaluation method and its applicable conditions,the comprehensive evaluation of logistic distribution of agricultural products obtained by using the method of fuzzy comprehensive appraisal.The results show that,in terms of reducing distribution costs,the packaging and distribution processing technology of fresh agricultural products should be improved,so as to reduce distribution costs.In the process of introducing the application of advanced technology,the high automatic logistic equipments should be introduced.

Importance of Generalized Logistic Distribution in Extreme Value Modeling

We consider a problem from stock market modeling, precisely, choice of adequate distribution of modeling extremal behavior of stock market data. Generalized extreme value (GEV) distribution and generalized Pareto (GP) distribution are the classical distributions for this problem. However, from 2004, [1] and many other researchers have been empirically showing that generalized logistic (GL) distribution is a better model than GEV and GP distributions in modeling extreme movement of stock market data. In this paper, we show that these results are not accidental. We prove the theoretical importance of GL distribution in extreme value modeling. For proving this, we introduce a general multivariate limit theorem and deduce some important multivariate theorems in probability as special cases. By using the theorem, we derive a limit theorem in extreme value theory, where GL distribution plays central role instead of GEV distribution. The proof of this result is parallel to the proof of classical extremal types theorem, in the sense that, it possess important characteristic in classical extreme value theory, for e.g. distributional property, stability, convergence and multivariate extension etc.

Themes and Challenges in Making Urban Freight Distribution Sustainable

The purpose of this article is to explore and classify themes and challenges in making urban freight distribution sustainable.The study has a cross sectional design which started by a narrative literature review and analysis of a sample of related literature(like peer-reviewed articles and EU(European Union)documents).It ended with complementary discussion and recommendation for tackling the challenges.The results of the study illustrate eight and seven emerged categories of themes and challenges,respectively.It is concluded that there is great need for a packet of mixed strategies as well as a more holistic perspective where all actors together analyse and design future set-ups and operation of urban freight distribution.Such a holistic view is essential in order to:understand how different actors of the chain look upon sustainable urban freight distribution,avoid sub-optimal policies/governing rules,and suggest close-to-reality solutions for tackling the challenges.Freight distribution in urban areas is the main focus of this article.In addition,the study is demarcated to eco/environmental aspect of sustainability although it is impossible to completely exclude its interaction with economic and social aspects.The results offered in this paper provide a systematic structure for classifying issues related to sustainable urban freight distribution;something which will be beneficial for managers and policy-makers when they approach sustainable supply chain management challenges.This study provides a synthesized classification of themes and challenges which can guide researchers,industries,authorities,and policy-makers in future sustainability efforts.

Estimation of scale parameters of logistic distribution by linear functions of sample quantiles

The large sample estimation of standard deviation of logistic distribution employs the asymptotically best linear unbiased estimators based on sample quantiles. The sample quantiles are established from a pair of single spacing. Finally, a table of the variances and efficiencies of the estimator for 5≤n≤65 is provided and comparison is made with other linear estimators.

Simulation Program to Determine Sample Size and Power for a Multiple Logistic Regression Model with Unspecified Covariate Distributions

Binary logistic regression models are commonly used to assess the association between outcomes and covariates. Many covariates are inherently continuous, and have a variety of distributions, including those that are heavily skewed to the left or right. Existing theoretical formulas, criteria, and simulation programs cannot accurately estimate the sample size and power of non-standard distributions. Therefore, we have developed a simulation program that uses Monte Carlo methods to estimate the exact power of a binary logistic regression model. This power calculation can be used for distributions of any shape and covariates of any type (continuous, ordinal, and nominal), and can account for nonlinear relationships between covariates and outcomes. For illustrative purposes, this simulation program is applied to real data obtained from a study on the influence of smoking on 90-day outcomes after acute atherothrombotic stroke. Our program is applicable to all effect sizes and makes it possible to apply various statistical methods, logistic regression and related simulations such as Bayesian inference with some modifications.

On Finding Geodesic Equation of Two Parameters Logistic Distribution

In this paper, we used two different algorithms to solve some partial differential equations, where these equations originated from the well-known two parameters of logistic distributions. The first method was the classical one that involved solving a triply of partial differential equations. The second approach was the well-known Darboux Theory. We found that the geodesic equations are a pair of isotropic curves or minimal curves. As expected, the two methods reached the same result.

Logistic Regression for Prediction and Diagnosis of Bacterial Regrowth in Water Distribution System

This paper focuses on the quantitative expression of bacterial regrowth in water distribution system. Considering public health risks of bacterial regrowth,the experiment was performed on a distribution system of selected area.Physical,chemical,and microbiological parameters such as turbidity,temperature,residual chlorine and pH were measured over a three-month period and correlation analysis was carried out.Combined with principal components analysis(PCA) ,a logistic regression model is developed to predict and diagnose bacterial regrowth and locate the zones with high risks of microbiology in the distribution system.The model gives the probability of bacterial regrowth with the number of heterotrophic plate counts as the binary response variable and three new principal components variables as the explanatory variables.The veracity of the logistic regression model was 90%,which meets the precision requirement of the model.

Inferences for the Generalized Logistic Distribution Based on Record Statistics

Estimation for the parameters of the generalized logistic distribution (GLD) is obtained based on record statistics from a Bayesian and non-Bayesian approach. The Bayes estimators cannot be obtained in explicit forms. So the Markov chain Monte Carlo (MCMC) algorithms are used for computing the Bayes estimates. Point estimation and confidence intervals based on maximum likelihood and the parametric bootstrap methods are proposed for estimating the unknown parameters. A numerical example has been analyzed for illustrative purposes. Comparisons are made between Bayesian and maximum likelihood estimators via Monte Carlo simulation.

Gumbel-Exponentiated Weibull {Logistic} Lifetime Distribution and Its Applications

A new generalized exponentiated Weibull model called Gumbel-exponentiated Weibull {Logistic} distribution is introduced and studied. The new distribution extends the exponentiated Weibull distribution with additional parameters and bimodal densities. Some new and earlier distributions formed the sub-models of the proposed distribution. The mathematical properties of the new distribution including expressions for the hazard function, survival function, moments, order statistics, mean deviation and absolute mean deviation from the mean, and entropy were derived. Monte Carlo simulation study was carried out to assess the finite sample behavior of the parameter estimates by maximum likelihood estimation approach. The superiority of the new generalized exponentiated Weibull distribution over some competing distributions was proved empirically using the fitted results from three real life datasets.

具有Logistic增长和心理作用的随机SIRS传染病模型定性分析

基于流行病受环境噪声和心理作用的影响,建立了一类具有Logistic增长和心理作用的随机SIRS传染病模型,目的在于讨论Logistic增长和心理作用对模型全局动力学的影响。首先,通过构造Lyapunov函数并利用Itˆo公式,证明了该模型全局正解的存在唯一性;然后,在适当的条件下,利用随机Lyapunov函数方法,应用LaSalle不变性原理得到该模型正解存在遍历平稳分布的充分条件。结果表明:环境和心理变化在一定条件下会对疾病起抑制作用。最后,通过数值模拟验证了理论结果的正确性。

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。