کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
6466965 1423247 2017 14 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Adaptive just-in-time and relevant vector machine based soft-sensors with adaptive differential evolution algorithms for parameter optimization
ترجمه فارسی عنوان
حسگرهای نرم افزاری مبتنی بر بردار ماشین سازگار با زمان واقعی و با استفاده از الگوریتم های تکاملی تطبیقی ​​برای بهینه سازی پارامتر
کلمات کلیدی
سنسورهای نرم فقط در زمان، ماشین بردار مربوطه، تکامل دیفرانسیل، مولفه های،
موضوعات مرتبط
مهندسی و علوم پایه مهندسی شیمی مهندسی شیمی (عمومی)
چکیده انگلیسی


- 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.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Chemical Engineering Science - Volume 172, 23 November 2017, Pages 571-584
نویسندگان
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