Agricultural products supply-chain finance, as one of the solutions to the issue of “capital problems” of agriculture, countryside and farmers, has proposed a kind of characteristics model to assess the risk of agri...Agricultural products supply-chain finance, as one of the solutions to the issue of “capital problems” of agriculture, countryside and farmers, has proposed a kind of characteristics model to assess the risk of agricultural production, processing and marketing, which can improve the issue of farmers and enterprises lacking of funds. This model is proposed on the basis of uncertain information processing method of D-S theory and its data combination rules, combined with the “discount rate” correction model, and it includes a risk assessment index system of agricultural products supply-chain finance, fully considering the five aspects of production, processing, marketing, cooperation of supply chain and collateral. At last, a taro supply chain is taken for example. And the risk assessment of its supply-chain finance based on this model has been discussed in detail. And the result has proved that the model and its algorithm are practical and feasible.展开更多
From raw material storage through final product distribution,a cold supply chain is a technique in which all activities are managed by temperature.The expansion in the number of imported meat and other comparable comm...From raw material storage through final product distribution,a cold supply chain is a technique in which all activities are managed by temperature.The expansion in the number of imported meat and other comparable commodities,as well as exported seafood has boosted the performance of cold chain logistics service providers.On the basis of the standard basicpursuit(BP)neural network,a rough BP particle swarm optimization(PSO)neural network model is constructed by combining rough set and particle swarm algorithms to aid cold chain food production enterprises in quickly picking the best cold chain logistics service providers.To reduce duplicate information in the original data and make the input index more compact,the model employs rough set.Instead of using gradient descent to train the weights of the neural network,particle swarm optimization is utilized to ensure that the output results are not readily caught in local minima and that the network’s generalization capacity is improved.Finally,an example is presented to demonstrate the model’s validity and viability.The findings reveal that the model’s prediction error is 40.94 percent lower than the BP neural network model,and the prediction result is more accurate and dependable,providing a new technique for cold chain food production companies to swiftly pick the best cold chain logistics service provider.展开更多
Establishing a mathematical supply-chain model is a proposition that has received attention due to its inherent benefits of evolving global supply-chain efficiencies.This paper discusses the prevailing relationships f...Establishing a mathematical supply-chain model is a proposition that has received attention due to its inherent benefits of evolving global supply-chain efficiencies.This paper discusses the prevailing relationships found within apparel supply-chain environments,and contemplates the complex issues indicated for constituting a mathematical model.Principal results identified within the data suggest,that the multifarious nature of global supply-chain activities require a degree of simplification in order to fully dilate the necessary factors which affect,each subsection of the chain.Subsequently,the research findings allowed the division of supply-chain components into subsections,which amassed a coherent method of product development activity.Concurrently,the supply-chain model was found to allow systematic mathematical formulae analysis,of cost and time,within the multiple contexts of each subsection encountered.The paper indicates the supplychain model structure,the mathematics,and considers how product analysis of cost and time can improve the comprehension of product lifecycle management.展开更多
文摘Agricultural products supply-chain finance, as one of the solutions to the issue of “capital problems” of agriculture, countryside and farmers, has proposed a kind of characteristics model to assess the risk of agricultural production, processing and marketing, which can improve the issue of farmers and enterprises lacking of funds. This model is proposed on the basis of uncertain information processing method of D-S theory and its data combination rules, combined with the “discount rate” correction model, and it includes a risk assessment index system of agricultural products supply-chain finance, fully considering the five aspects of production, processing, marketing, cooperation of supply chain and collateral. At last, a taro supply chain is taken for example. And the risk assessment of its supply-chain finance based on this model has been discussed in detail. And the result has proved that the model and its algorithm are practical and feasible.
基金This research was supported by the MSIT(Ministry of Science and ICT),Korea,under the National Research Foundation(NRF),Korea(2022R1A2C4001270).
文摘From raw material storage through final product distribution,a cold supply chain is a technique in which all activities are managed by temperature.The expansion in the number of imported meat and other comparable commodities,as well as exported seafood has boosted the performance of cold chain logistics service providers.On the basis of the standard basicpursuit(BP)neural network,a rough BP particle swarm optimization(PSO)neural network model is constructed by combining rough set and particle swarm algorithms to aid cold chain food production enterprises in quickly picking the best cold chain logistics service providers.To reduce duplicate information in the original data and make the input index more compact,the model employs rough set.Instead of using gradient descent to train the weights of the neural network,particle swarm optimization is utilized to ensure that the output results are not readily caught in local minima and that the network’s generalization capacity is improved.Finally,an example is presented to demonstrate the model’s validity and viability.The findings reveal that the model’s prediction error is 40.94 percent lower than the BP neural network model,and the prediction result is more accurate and dependable,providing a new technique for cold chain food production companies to swiftly pick the best cold chain logistics service provider.
文摘Establishing a mathematical supply-chain model is a proposition that has received attention due to its inherent benefits of evolving global supply-chain efficiencies.This paper discusses the prevailing relationships found within apparel supply-chain environments,and contemplates the complex issues indicated for constituting a mathematical model.Principal results identified within the data suggest,that the multifarious nature of global supply-chain activities require a degree of simplification in order to fully dilate the necessary factors which affect,each subsection of the chain.Subsequently,the research findings allowed the division of supply-chain components into subsections,which amassed a coherent method of product development activity.Concurrently,the supply-chain model was found to allow systematic mathematical formulae analysis,of cost and time,within the multiple contexts of each subsection encountered.The paper indicates the supplychain model structure,the mathematics,and considers how product analysis of cost and time can improve the comprehension of product lifecycle management.
