کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
6466965 | 1423247 | 2017 | 14 صفحه PDF | دانلود رایگان |
- A Just-in-time (JIT) and Relevant-vector-machine (RVM) to perform perditions.
- Nature-inspired optimized algorithm that ensures optimal parameters selection for JIT and RVM.
- A JADE evolution algorithm to optimize parameters for JIT and RVM without hyper-parameter setting.
- A moving window methodology for improvement of the JIT and RVM model.
- Proposed method is efficiently attractive in a wastewater plant monitoring.
Just-in-time (JIT) and Relevant vector machine (RVM) are two of commonly used models for soft-sensors modeling, the efficiency of which is governed by few critical parameters and hyper-parameters significantly. These parameters are routinely selected by trial and error or experience, thus leading to over- or under-fitting for the prediction. Adaptive differential evolution with optional external archive (JADE) has been used to optimize the parameters of JIT and RVM in this paper. The resulted JADE-JIT and JADE-RVM based soft-sensors are further enhanced into an adaptive format by the moving window (WM) technique. The proposed methodologies are applied to prediction of hard-to-measured variables in the wastewater treatment plants (WWTPs) and successful results are obtained.
Journal: Chemical Engineering Science - Volume 172, 23 November 2017, Pages 571-584