Matches in SemOpenAlex for { <https://semopenalex.org/work/W4246062704> ?p ?o ?g. }
Showing items 1 to 73 of
73
with 100 items per page.
- W4246062704 endingPage "165" @default.
- W4246062704 startingPage "145" @default.
- W4246062704 abstract "An inferential or soft sensor is a mathematical relation that calculates or predicts a controlled property using other available process data. When it is very difficult or costly to measure an important parameter online like distillation tower top product impurity, soft sensors are used to predict that inferential property from other easily measurable parameters like top temperature, and pressure. Sometimes soft sensors are used as back-ups to an existing analyzer to reduce or eliminate dead time, both from the process and the analyzer cycle. Usually, four types of soft sensors are used in industry: principle-based soft sensor, data-driven soft sensors, gray model-based soft sensors, and hybrid model-based soft sensors. There are many methods to develop industrial soft sensors, and usually they include the following steps: data collection and data inspection; data preprocessing and data conditioning; selection of relevant input output variables; aligning data; model selection, training, and validation; analysis of dynamics; and finally deployment and maintenance. Due to difficulty to develop first principle based soft sensors, data driven soft sensors are very popular in industry. This chapter discusses the major data-driven methods for soft sensing that dominate the industry: principle component analysis, partial least squares, artificial neural networks, neuro-fuzzy systems, and support vector machines." @default.
- W4246062704 created "2022-05-12" @default.
- W4246062704 date "2017-08-23" @default.
- W4246062704 modified "2023-09-26" @default.
- W4246062704 title "Soft Sensors" @default.
- W4246062704 cites W1480376833 @default.
- W4246062704 cites W1649946951 @default.
- W4246062704 cites W1689445748 @default.
- W4246062704 cites W1968763291 @default.
- W4246062704 cites W1982142851 @default.
- W4246062704 cites W1988790447 @default.
- W4246062704 cites W1998345503 @default.
- W4246062704 cites W1999935041 @default.
- W4246062704 cites W2000651380 @default.
- W4246062704 cites W2018097969 @default.
- W4246062704 cites W2033266347 @default.
- W4246062704 cites W2036165891 @default.
- W4246062704 cites W2052740976 @default.
- W4246062704 cites W2122752936 @default.
- W4246062704 cites W2130444042 @default.
- W4246062704 cites W2143322006 @default.
- W4246062704 cites W2156267802 @default.
- W4246062704 cites W2974238426 @default.
- W4246062704 cites W4205110562 @default.
- W4246062704 cites W4212883601 @default.
- W4246062704 cites W56434051 @default.
- W4246062704 doi "https://doi.org/10.1002/9781119243434.ch10" @default.
- W4246062704 hasPublicationYear "2017" @default.
- W4246062704 type Work @default.
- W4246062704 citedByCount "0" @default.
- W4246062704 crossrefType "other" @default.
- W4246062704 hasConcept C10551718 @default.
- W4246062704 hasConcept C111919701 @default.
- W4246062704 hasConcept C115575686 @default.
- W4246062704 hasConcept C124101348 @default.
- W4246062704 hasConcept C127413603 @default.
- W4246062704 hasConcept C133731056 @default.
- W4246062704 hasConcept C140073362 @default.
- W4246062704 hasConcept C154945302 @default.
- W4246062704 hasConcept C33954974 @default.
- W4246062704 hasConcept C41008148 @default.
- W4246062704 hasConcept C50644808 @default.
- W4246062704 hasConcept C98045186 @default.
- W4246062704 hasConceptScore W4246062704C10551718 @default.
- W4246062704 hasConceptScore W4246062704C111919701 @default.
- W4246062704 hasConceptScore W4246062704C115575686 @default.
- W4246062704 hasConceptScore W4246062704C124101348 @default.
- W4246062704 hasConceptScore W4246062704C127413603 @default.
- W4246062704 hasConceptScore W4246062704C133731056 @default.
- W4246062704 hasConceptScore W4246062704C140073362 @default.
- W4246062704 hasConceptScore W4246062704C154945302 @default.
- W4246062704 hasConceptScore W4246062704C33954974 @default.
- W4246062704 hasConceptScore W4246062704C41008148 @default.
- W4246062704 hasConceptScore W4246062704C50644808 @default.
- W4246062704 hasConceptScore W4246062704C98045186 @default.
- W4246062704 hasLocation W42460627041 @default.
- W4246062704 hasOpenAccess W4246062704 @default.
- W4246062704 hasPrimaryLocation W42460627041 @default.
- W4246062704 hasRelatedWork W1744457912 @default.
- W4246062704 hasRelatedWork W1815983343 @default.
- W4246062704 hasRelatedWork W2169113737 @default.
- W4246062704 hasRelatedWork W2348038154 @default.
- W4246062704 hasRelatedWork W2366204170 @default.
- W4246062704 hasRelatedWork W2379118468 @default.
- W4246062704 hasRelatedWork W2382178541 @default.
- W4246062704 hasRelatedWork W2899084033 @default.
- W4246062704 hasRelatedWork W4386030136 @default.
- W4246062704 hasRelatedWork W811092902 @default.
- W4246062704 isParatext "false" @default.
- W4246062704 isRetracted "false" @default.
- W4246062704 workType "other" @default.