人工神经网络和模糊识别理论作为模拟生物体的信息处理系统。
The artificial neural network(ANN) and the fuzzy recognition(FR) are information process systems to simulate biological mechanism.
把模糊环境下的模糊识别理论具体应用到地下水脆弱性评价中。
The proposed fuzzy pattern recognition model under fuzzy environment is applied to theevaluation of groundwater vulnerability.
根据模糊识别理论，建立了各影响因素与压裂效果之间的模糊关系。
Based on the fuzzy diagnosis theory, the fuzzy relation between the effecting factors and the fracturing results is set up.
在模糊识别理论的基础上提出了一种适宜于复杂系统工况识别的单模糊模式直接距离法。
Based on the fuzzy identification theory, a single fuzzy model direct distance method is raised, which is suitable for operating model identification of complex system.
根据模糊聚类与模糊识别理论，基于模糊环境下的目标函数，提出了一种确定预报因子权重的理论模式。
According to fuzzy clustering theory and fuzzy pattern recognition theory, a theory and model deciding forecast factor weight was present on basis of fuzzy object function in this paper.
探讨了系统危险等级模糊特征量的置信度准则，指出了属性识别理论中置信度准则的不合理性。
Believing degree criterion of fuzzy characteristic quantity of risk grade of system was discussed, and unreason of believing degree in property recognized theory was pointed out.
利用模糊数学和模式识别理论以及动态聚类方法等，提出了堤防工程安全评估专家主观和客观赋权模型；
To evaluate embankment safety, this paper constructs the models obtaining subjective and objective weight of experts with the methods of fuzzy mathematics, pattern recognition and dynamic clustering.
并结合模糊模式识别理论，建立了流型的模糊判别准则。
Combined with fuzzy pattern recognition theory, the fuzzy identification criterions of flow patterns are established.
采用线性分析和模糊模式识别理论，对动态心电图QRS波形进行检测和分析的算法进行了语法描述，并在此基础上给出了心率失常分析系统实现的具体方法。
A linear analysis and pattern recognition method to detect and analyze dynamic cardiogram QRS wave are applied I this paper and an effective method for HRW analysis system is introduced.
将模糊模式识别理论模型与级别变量特征值相结合，形成改性模糊模式识别法。
By combining the fuzzy recognition model with the eigenvalues of grade variables, an improved fuzzy recognition model is established.
将模糊模式识别理论模型与级别变量特征值相结合，形成改性模糊模式识别法。
By combining the fuzzy recognition model with the eigenvalues of grade variables, an improved fuzzy recognition model is established.
应用推荐