基于改进型PCNN与模糊算法的湿地生态承载力评价

Evaluating Ecological Carrying Capacity of Wetland Based on Improved Pulse Coupled Neural Network and Fuzzy Algorithm

在脉冲耦合神经网络(PCNN)模型两大基本特性(耦合机制、脉冲输出)的基础上对其进行了改进,连接输入部分等于上一次点火时的脉冲,直接体现了前后神经元之间的联系;动态阈值等于生态承载力评价标准的等级范围,这样调节阈值更容易对样本进行分类;省略了不必要的参数,减少了模型的复杂度;将PCNN与多目标模糊模式识别模型结合,提出了基于模糊PCNN的生态承载力评价新模型,并采用13个评价指标对三江平原6个地理分区的生态承载力评价指标标准和PCNN模型调整后的数据分别计算它们的隶属度,最后得出各个地理分区的生态承载力综合评价结果。结果表明三江平原大部分生态系统较稳定,资源与环境承载能力比较高,但是湿地生态系统健康状况比较差,湿地生态环境质量下降比较快,需要加强改善沼泽湿地生态环境,提高水资源的利用效率等措施。同时表明改进型PCNN与多目标模糊模式识别模型结合应用于生态承载力评价中是可行的,既拓宽了PCNN的应用领域,又为生态承载力的评价问题提供了新的研究方法。

Pulse Coupled Neural Network（PCNN）,called as the third generation of neural network,with the basic characteristics of coupling and pulse output,is widely implemented on image processing and obtained the certain result.In this paper,the PCNN model is improved as follows： the value of link load part equals to the pulse in the last ignition action in order to reflect the relationship between the before and after neural cell directly,dynamic threshold equals to the classification range of ecological carrying capacity evaluation criterion to classify the samples easily and unnecessary parameter is omitted to reduce the complexity of PCNN model.After the combination of PCNN and multi-objective and fuzzy pattern identified model,the new ecological carrying capacity evaluation model is put forward based on fuzzy PCNN.And 13 evaluation indexes were adopted in ecological carrying capacity evaluation criterion and data adjusted through PCNN model of 6 geography zonings in Sanjiang Plain to calculate their degrees of membership relatively.At last,integrative evaluation results of ecological carrying capacity for every geography zoning were obtained.The result shows that most ecological systems of Sanjiang Plain are quite stable and carrying capacity of resources and environments are very high.At the same time,health status of wetland ecological systems is not so good,and the quality of marsh ecological systems is decreasing fast.So wetland ecological systems are required to improve and the utilization efficiency of water resource is also needed to advance.The experiment results show the feasibility of this model in the status evaluation of agriculture water resource utilization,expanding the application areas of PCNN model and providing a new alternative for water resource evaluation.