4.7 Article

Dynamic soft sensor modeling method fusing process feature information based on an improved intelligent optimization algorithm

相关参考文献

注意:仅列出部分参考文献,下载原文获取全部文献信息。
Article Automation & Control Systems

Novel competing evolutionary membrane algorithm based on multiple reference points for multi-objective optimization of ethylene cracking processes

Di Cong et al.

Summary: The research on multiobjective optimization focuses on proposing a reference point based competing evolutionary membrane algorithm to help chemical processes achieve objectives such as product amount improvement, energy saving, and emission reduction. The algorithm shows promising results in achieving energy and emission reductions in the ethylene cracking process, indicating great potential for future applications.

CHEMOMETRICS AND INTELLIGENT LABORATORY SYSTEMS (2021)

Article Green & Sustainable Science & Technology

Input-output networks considering graphlet-based analysis for production optimization: Application in ethylene plants

Zun Wang et al.

Summary: This study proposes a production optimization methodology using I-O network and graphlets to consider production relationships in complex systems. By statistical analysis and hierarchical clustering, more effective optimization can be achieved.

JOURNAL OF CLEANER PRODUCTION (2021)

Article Thermodynamics

Resource optimization model using novel extreme learning machine with t-distributed stochastic neighbor embedding: Application to complex industrial processes

Yongming Han et al.

Summary: A novel extreme learning machine method based on t-distributed stochastic neighbor embedding is proposed in this paper to optimize energy and reduce carbon emissions. Experimental results demonstrate that this method can improve the prediction accuracy of resource optimization models for complex industrial processes, realizing energy-saving and emissions reduction.

ENERGY (2021)

Article Automation & Control Systems

Deep Learning With Spatiotemporal Attention-Based LSTM for Industrial Soft Sensor Model Development

Xiaofeng Yuan et al.

Summary: An LSTM network with spatiotemporal attention is proposed for soft sensor modeling in industrial processes, improving prediction performance by identifying important input variables related to the quality variable and discovering quality-related hidden states adaptively.

IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS (2021)

Article Engineering, Chemical

Novel Deep Learning Based on Data Fusion Integrating Correlation Analysis for Soft Sensor Modeling

Hao Wu et al.

Summary: The study proposes a novel soft sensing method based on DCNN, combining data fusion and correlation analysis. By applying this method, significant improvements in prediction accuracy and generalization ability have been achieved, which can enhance production efficiency.

INDUSTRIAL & ENGINEERING CHEMISTRY RESEARCH (2021)

Article Computer Science, Artificial Intelligence

A Layer-Wise Data Augmentation Strategy for Deep Learning Networks and Its Soft Sensor Application in an Industrial Hydrocracking Process

Xiaofeng Yuan et al.

Summary: A layer-wise data augmentation strategy is proposed for pretraining deep learning networks and soft sensor modeling, showing superior performance compared to other methods.

IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS (2021)

Article Automation & Control Systems

Novel soft sensor development using echo state network integrated with singular value decomposition: Application to complex chemical processes

Yan-Lin He et al.

CHEMOMETRICS AND INTELLIGENT LABORATORY SYSTEMS (2020)

Review Automation & Control Systems

Differential Evolution: A review of more than two decades of research

Bilal et al.

ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE (2020)

Article Automation & Control Systems

Hierarchical Quality-Relevant Feature Representation for Soft Sensor Modeling: A Novel Deep Learning Strategy

Xiaofeng Yuan et al.

IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS (2020)

Article Engineering, Chemical

Novel Nonlinear Autoregression with External Input Integrating PCA-WD and Its Application to a Dynamic Soft Sensor

Bailun Zhang et al.

INDUSTRIAL & ENGINEERING CHEMISTRY RESEARCH (2020)

Article Computer Science, Artificial Intelligence

Self-adaptive differential evolution with global neighborhood search

Zhaolu Guo et al.

SOFT COMPUTING (2017)

Article Computer Science, Artificial Intelligence

An enhanced particle swarm optimization with levy flight for global optimization

R. Jensi et al.

APPLIED SOFT COMPUTING (2016)

Article Computer Science, Information Systems

Modeling deterministic echo state network with loop reservoir

Xiao-chuan Sun et al.

JOURNAL OF ZHEJIANG UNIVERSITY-SCIENCE C-COMPUTERS & ELECTRONICS (2012)

Article Computer Science, Artificial Intelligence

A novel particle swarm optimization algorithm with adaptive inertia weight

Ahmad Nickabadi et al.

APPLIED SOFT COMPUTING (2011)

Article Computer Science, Artificial Intelligence

Differential Evolution: A Survey of the State-of-the-Art

Swagatam Das et al.

IEEE TRANSACTIONS ON EVOLUTIONARY COMPUTATION (2011)

Article Computer Science, Artificial Intelligence

Differential Evolution Algorithm With Strategy Adaptation for Global Numerical Optimization

A. K. Qin et al.

IEEE TRANSACTIONS ON EVOLUTIONARY COMPUTATION (2009)

Article Management

A numerical study of some modified differential evolution algorithms

P Kaelo et al.

EUROPEAN JOURNAL OF OPERATIONAL RESEARCH (2006)