Soft Sensor Modeling Method for Sulfur Recovery Process Based on Long Short-Term Memory Artificial Neural Network (LSTM)

نویسندگان

چکیده

In the process of sulfur recovery, H 2 S and SO concentrations reflect effectiveness reliability recovery process. However, concentration in is difficult to be measured by online analysis instrument, so soft sensing modeling method often used analyze system. Because SRU system has strong nonlinear characteristics dynamic characteristics,traditional methods are limited use. Long Short-Term Memory (LSTM)Artificial neural networks show ability processing data data. Therefore, LSTM this paper systematically

برای دانلود باید عضویت طلایی داشته باشید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Gating Artificial Neural Network Based Soft Sensor

This work proposes a novel approach to Soft Sensor modelling, where the Soft Sensor is built by a set of experts which are artificial neural networks with randomly generated topology. For each of the experts a meta neural network is trained, the gating Artificial Neural Network. The role of the gating network is to learn the performance of the experts in dependency on the input data samples. Th...

متن کامل

A novel soft sensor model based on artificial neural network in the fermentation process

Some crucial process variables in fermentation process could not be measured directly. Soft sensor technology provided an effective way to solve the problem. There has been considerable interest in modeling a soft sensor by using artificial neural network (ANN) in bioprocess. To generate a more efficient soft sensor model, we proposed a novel soft sensor model based on artificial neural network...

متن کامل

Language Identification in Short Utterances Using Long Short-Term Memory (LSTM) Recurrent Neural Networks

Long Short Term Memory (LSTM) Recurrent Neural Networks (RNNs) have recently outperformed other state-of-the-art approaches, such as i-vector and Deep Neural Networks (DNNs), in automatic Language Identification (LID), particularly when dealing with very short utterances (∼3s). In this contribution we present an open-source, end-to-end, LSTM RNN system running on limited computational resources...

متن کامل

scour modeling piles of kambuzia industrial city bridge using hec-ras and artificial neural network

today, scouring is one of the important topics in the river and coastal engineering so that the most destruction in the bridges is occurred due to this phenomenon. whereas the bridges are assumed as the most important connecting structures in the communications roads in the country and their importance is doubled while floodwater, thus exact design and maintenance thereof is very crucial. f...

A New Approach for Investigating the Complexity of Short Term EEG Signal Based on Neural Network

 Background and purpose: The nonlinear quality of electroencephalography (EEG), like other irregular signals, can be quantified. Some of these values, such as Lyapunovchr('39')s representative, study the signal path divergence and some quantifiers need to reconstruct the signal path but some do not. However, all of these quantifiers require a long signal to quantify the signal complexity. Mate...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

ژورنال

عنوان ژورنال: E3S web of conferences

سال: 2023

ISSN: ['2555-0403', '2267-1242']

DOI: https://doi.org/10.1051/e3sconf/202340604028