基于模糊神经网络的沉积环境判别方法研究OA
Identification Study of Sedimentary Environment Based on Fuzzy Neural Network
由于粒度分析与沉积环境间密切的关系，针对模糊逻辑与人工神经网络各自的优点，提出了一种基于模糊神经网络的沉积环境判别方法．它以碎屑岩的关键粒度参数作为网络的输入，通过标准化和模糊化及输出的去模糊化等过程，使得模糊推理与神经网络充分结合．实验证明，这种模型判别相应沉积环境的误判率为9．1％，明显低于BP神经网络的32．1％且收敛速度更快，更能够满足实际工程的需求．
As to the relationship between grain size and sedimentary environment , in this paper , an iden-tification method of sedimentary environment is proposed based on fuzzy neural network , which combines the advantages of both fuzzy logic and artificial neural network .The proposed approach includes taking the key size parameters of clastic rock as inputs , being standardized and fuzzified by the network and be-ing defuzzified of outputs .As a result , the fuzzy…查看全部>>
朱远鑫;刘富春
广东工业大学计算机学院，广东广州510006广东工业大学计算机学院，广东广州510006
信息技术与安全科学
模糊神经网络沉积环境判别分析粒度分析分类
fuzzy neural networksedimentary environmentidentification analysisgrain size analysisclassification
《广东工业大学学报》 2015 (2)
分布式离散事件系统的分散控制与分散故障诊断研究
48-52,103,6
国家自然科学基金资助项目（61273118）
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