Open AccessSludge Conditioning Soft Measuement Based on GA-RVM
Author(s) -
Lei Luo
Publication year - 2020
Publication title -
iop conference series. earth and environmental science
Language(s) - English
Resource type - Journals
eISSN - 1755-1307
pISSN - 1755-1315
DOI - 10.1088/1755-1315/512/1/012054
Subject(s) - conditioning , kernel (algebra) , relevance vector machine , value (mathematics) , genetic algorithm , function (biology) , computer science , relevance (law) , mathematics , bellman equation , mathematical optimization , artificial intelligence , support vector machine , statistics , biology , combinatorics , evolutionary biology , political science , law
To solve the highly non-linear problem of sludge conditioning, the Relevance Vector Machine (RVM), was used to softly measure the sludge conditioning process.The parameters of the kernel function seriously affect the comprehensive performance of RVM. Using genetic algorithm (GA)to obtain the optimal kernel function parameters is an effective solution. The simulation results indicated that the filtering performance was basically consistent with the actual value of dosage and the model prediction result, and the target value could be well predicted. It showed that the model had a certain value for industrial application.