搜索资源列表
PS0-SVR
- ：针对发酵过程中生物参数难以实时在线测量的问题，建立了用于生物参数状态预估的 支持向量机软测量模型。考虑到该支持向量回归(SVR)模型的复杂性和冷化特征取决于其三 个参数 ，c， 能否取到最优值，采用粒子群优化(PSO)算法实现对参数 ，c， 的同时寻优。在 此基础上，以饲料用 ．甘露聚糖酶为对象，建立了基于PSO—SVR的发酵过程产物浓度状态预估 模型。发酵罐控制结果表明：该模型具有很好的学习精度和泛化能力，可实现对 ．甘露聚糖酶 产物浓度的实时在线预估。-In
RBF-neural-network-based-on-RS-theory-of-grinding.
- 基于RBF神经网络和RS理论的磨矿分级系统软测量模型-RBF neural network based on RS theory of grinding and classification system of soft sensor model
UKF-based-AC-induction-electric-dynamometer
- UKF的交流异步电力测功机软测量模型UKF-based AC induction electric dynamometer soft sensor model-UKF-based AC induction electric dynamometer soft sensor model
guochengshenjingwangluo
- 过程神经网络软测量测试出不能实际测量的值-Process neural network soft sensor can not test the actual measured values
LSl
- LS_SVM的烧结矿化学成分软测量模型LS_SVM sinter chemical composition soft sensor model-LS_SVM sinter chemical composition soft sensor model
tions
- LS_SVM软测量模型工业应用LS_SVM soft sensor model and its industrial applications-LS_SVM soft sensor model and its industrial applications
hgfhf
- LS_SVM的软测量模型及其工业应用LS_SVM soft sensor model and its industrial application-LS_SVM soft sensor model and its industrial application
PLS
- 基于PLS的软测量建模与测试程序，能较好地跟踪目标值的变化趋势-PLS soft sensor modeling and testing procedures, can track the target value trend
paper3
- Soft authentication using an infrared ceiling sensor network
soft-sensor
- rbf神经网络软测量matlab程序，svm软测量matlab程序-RBF neural network soft measurement Matlab procedures, SVM soft Matlab procedures
pls-(2)
- 利用c++实现pls软测量，对初学者有很好的帮助-according to pls,use c++ to achieve the soft sensor,which is helpful to the beginner
fengyao
- 比较了软阈值，硬阈值及当今各种阈值计算方法,采用累计贡献率的方法，虚拟力的无线传感网络覆盖。- Comparison of soft threshold and hard threshold and today various threshold calculation method, The method of cumulative contribution rate Virtual power wireless sensor network coverage.
GPR
- 利用高斯过程回归建立软测量模型，主程序名为OnlineStage.m,包含数据，可以直接运行，亲测可用。-Gaussian process regression soft sensor model, the main program named OnlineStage.m, contains data that can be run directly, pro-test available.
PSO-SVM
- 利于PSO优化的SVM，可用于解决软测量建模过程中的非线性问题(SVM, which is beneficial to PSO optimization, can be used to solve the nonlinear problems in soft sensor modeling)
DBN-ELM-master
- DBN-ELM应用于软测量，可以预测精度，并且可以和其它软测量模型进行对比。(Application of DBN-ELM in Soft Sensing,it can predict the accuracy and compare with other soft sensor models.)