@inproceedings{3e633a73f7f745989c742e447e458423,
title = "Long-term prediction of industrial furnace by Extended Sequential Prediction method of LOM",
abstract = "Recently, attention has been drawn by the local modeling techniques of a new idea called {"}Just-In-Time (JIT) modeling{"} or {"}Lazy Learning{"}. To apply {"}JIT modeling{"} to a large amount of database online, {"}Large-scale database-based Online Modeling (LOM){"} has been proposed. LOM is such a technique that makes the retrieval of {"}neighboring{"} data more efficient by using {"}stepwise selection{"} and quantization. This paper reports an Extended Sequential Prediction (ESP) method of LOM with the local regression model. The ESP method is able to predict process variables over a long period by modeling the operator and the plant based on LOM, the approach is to repeat a process that predicts the process variables of the next step by using the predicted variables of the previous step. The method is applied to a dynamic industrial furnace with several deeply-intertwined physical phenomena; practical effectiveness of the method is verified. As a result, the method has predicted the process variables with satisfactory accuracy.",
keywords = "ESP, Industrial furnace, JIT modeling, LOM, Operation support, Sequential Prediction",
author = "Masatoshi Ogawa and Yichun Yeh and Syou Kawanari and Harutoshi Ogai",
year = "2010",
month = jan,
day = "1",
language = "English",
isbn = "9784907764364",
series = "Proceedings of the SICE Annual Conference",
publisher = "Society of Instrument and Control Engineers (SICE)",
pages = "1490--1493",
booktitle = "Proceedings of SICE Annual Conference 2010, SICE 2010 - Final Program and Papers",
}