English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

The walking beam furnace (WBF) is one of the most prominent process plants   often met in an alloy steel production factory and characterized by high   non-linearity, strong coupling, time delay, large time-constant and time   variation in its parameter set and structure. From another viewpoint, the   WBF is a distributed-parameter process in which the distribution of   temperature is not uniform. Hence, this process plant has complicated   non-linear dynamic equations that have not worked out yet. In this paper, we   propose one-step non-linear predictive model for a real WBF using non-linear   black-box sub-system identification based on locally linear neuro-fuzzy   (LLNF) model. Furthermore, a multi-step predictive model with a precise long   prediction horizon (i.e., ninety seconds ahead), developed with application   of the sequential one-step predictive models, is also presented for the   first time. The locally linear model tree (LOLIMOT) which is a progressive   tree-based algorithm trains these models. Comparing the performance of the   one-step LLNF predictive models with their associated models obtained   through least squares error (LSE) solution proves that all operating zones   of the WBF are of non-linear sub-systems. The recorded data from Iran Alloy   Steel factory is utilized for identification and evaluation of the proposed   neuro-fuzzy predictive models of the WBF process

Short-term and long-term thermal prediction of a walking beam furnace using neuro-fuzzy techniques