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基于 GM 模型和少样本学习的区域经济不确定基金需求预测算法。

Prediction Algorithm of Uncertain Fund Demand for Regional Economics Using GM Model and Few-Shot Learning.

机构信息

School of Economics and Finance, Zhanjiang University of Science and Technology, Zhanjiang 524094, China.

出版信息

Comput Intell Neurosci. 2022 Jul 1;2022:2307149. doi: 10.1155/2022/2307149. eCollection 2022.

Abstract

The forecast of capital demand has the characteristics of uncertainty. There are known and unknown information about the capital demand for regional economic development. In fact, there are also some in between, that is, uncertain. Consumption is the ultimate goal of production and a key link in realizing a virtuous circle of economic development. This paper uses the GM (1, 1) model to compare the predicted value of the test area with the actual value in 5 years, and the loudness is as high as 90%. Under the guidance of the profit model, the regional economic capital demand has a decisive influence on the regional economic development. The predictive analysis model of capital needs is conducive to fully mobilizing the impact of infrastructure construction of all parties and is an important factor affecting economic development. The mathematical model proposed in this paper is helpful for deepening the research on the management of regional economic development and enriching the theoretical system of regional economic development.

摘要

资本需求预测具有不确定性。区域经济发展的资本需求既有已知信息,也有未知信息。事实上,还有一些处于两者之间的信息,也就是不确定信息。消费是生产的最终目的,也是实现经济发展良性循环的关键环节。本文采用 GM(1,1)模型,对试验区 5 年内的预测值与实际值进行对比,吻合度高达 90%。在利润模型的指导下,区域经济资本需求对区域经济发展具有决定性影响。资本需求预测分析模型有利于充分调动各方基础设施建设的积极性,是影响经济发展的重要因素。本文提出的数学模型有助于深化区域经济发展管理研究,丰富区域经济发展理论体系。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/daed/9270173/f7c470d1e7b1/CIN2022-2307149.001.jpg

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