Supervised Latent Factor Analysis for Process Data Regression Modeling and Soft Sensor Application


This transient proposed a new supervised latent factor analysis (FA) technique for method knowledge regression modeling. Totally different from the ancient principal part analysis/regression model, the new model will successfully estimate heterogeneous variances from totally different method variables, which is a lot of sensible. Underneath the identical probabilistic modeling framework, the single supervised latent FA model is further extended to the mixture form. Efficient expectation–maximization algorithms are developed for parameter learning in both single and mixture supervised latent FA models. Based on the regression modeling between simple-to-measure and difficult-to-live method variables, two soft sensors are engineered for quality prediction in the process. 2 case studies are provided to evaluate the modeling and performances of the new strategies.

Did you like this research project?

To get this research project Guidelines, Training and Code... Click Here

PROJECT TITLE :Supervised Polarimetric SAR Image Classification Using Tensor Local Discriminant Embedding - 2018ABSTRACT:Feature extraction may be a terribly vital step for polarimetric artificial aperture radar (PolSAR) image
PROJECT TITLE :Cost-Optimal Caching for D2D Networks With User Mobility: Modeling, Analysis, and Computational Approaches - 2018ABSTRACT:Caching well-liked files at the user equipments (UEs) provides an efficient way to alleviate
PROJECT TITLE :Design, Analysis, and Implementation of ARPKI: An Attack-Resilient Public-Key Infrastructure - 2018ABSTRACT:This Transport Layer Security (TLS) Public-Key Infrastructure (PKI) is based on a weakest-link security
PROJECT TITLE :Supervised Topic Modeling Using Hierarchical Dirichlet Process-Based Inverse Regression: Experiments on E-Commerce Applications - 2018ABSTRACT:The proliferation of e-commerce involves mining client preferences and
PROJECT TITLE : Supervised and Unsupervised Aspect Category Detection for Sentiment Analysis with Co-Occurrence Data - 2017 ABSTRACT: Using on-line consumer reviews as electronic word of mouth to help purchase-decision making

Ready to Complete Your Academic MTech Project Work In Affordable Price ?

Project Enquiry