基于模糊数学与神经网络的农业产业集群评价研究

Study on Evaluation of Agricultural Industry Cluster Based on Fuzzy Mathematics and Neural Network Theory

针对目前农业产业集群评价研究现状较少状况,尝试运用模糊数学方法对指标数据运用隶属度函数处理,以一级模糊综合评价向量作为神经网络评价模型的输入,再运用神经网络模型对农业产业集群进行评价,神经网络的非线性处理能力使农业产业集群评价更加科学化,并以连云港农业产业集群评价为例给出了实证研究。

For some cases of the less evaluation study on agricultural industry cluster, this article uses fuzzy mathematics membership functions to deal with the indicators data. The first level vector of fuzzy comprehensive evaluation is used as the inputs for the Neural Network evaluation model. Then the Neural Network evaluation mode is used to evaluate the level of agricultural industry cluster. Non-linear processing capacity of neural network makes the evaluation of agricultural industry cluster more scientific, and an empirical case study of the evaluation of aaricultural industrv cluster in Lianvungang is given_