4.7 Article

Dynamic pollution emission prediction method of a combined heat and power system based on the hybrid CNN-LSTM model and attention mechanism

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 Engineering, Civil

Application of the collision mathematical model based on a BP neural network in railway vehicles

Yu-Ru Li et al.

Summary: A collision mathematical model (VCMM) based on the back-propagation neural network was developed to predict collision response data, showing good agreement with finite element simulation results and significantly improving calculation efficiency. This model has the potential to partially replace experimental and simulation results for crashworthiness and safety design studies of vehicle structures in the future.

PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART F-JOURNAL OF RAIL AND RAPID TRANSIT (2021)

Article Environmental Sciences

Determinants of technical inefficiency in China's coal-fired power plants and policy recommendations for CO2 mitigation

Tomoaki Nakaishi et al.

Summary: This study found that Chinese coal-fired power plants have significant potential to reduce coal consumption and mitigate CO2 emissions through technological improvement. The study suggests the Chinese government create a power distribution structure that generates electricity using technologically efficient equipment in areas rich in coal resources and distributes the generated electricity to other areas of the country.

ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH (2021)

Article Chemistry, Physical

Mutual information analysis of the dynamic correlation between side chains in proteins

Naoyuki Miyashita et al.

Summary: Protein dynamics play a crucial role in function regulation, with changes in protein fluctuations in the backbone and side chains impacting amino acid mutations, chemical modifications, and ligand binding. A new method utilizing mutual information and molecular dynamics simulations has been developed to evaluate dynamic correlations between protein side chains, showing potential for analyzing allosteric communication in proteins.

JOURNAL OF CHEMICAL PHYSICS (2021)

Review Environmental Sciences

Effect of Attention Mechanism in Deep Learning-Based Remote Sensing Image Processing: A Systematic Literature Review

Saman Ghaffarian et al.

Summary: Machine learning, especially deep learning, has become a key method in computer vision and remote sensing image processing. Researchers are exploring the use of attention mechanisms to enhance the performance of deep learning methods in remote sensing applications.

REMOTE SENSING (2021)

Article Environmental Sciences

A water quality prediction method based on the multi-time scale bidirectional long short-term memory network

Qinghong Zou et al.

ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH (2020)

Article Engineering, Electrical & Electronic

A Novel Method for Hourly Electricity Demand Forecasting

Guoqiang Zhang et al.

IEEE TRANSACTIONS ON POWER SYSTEMS (2020)

Article Computer Science, Interdisciplinary Applications

An optimized model using LSTM network for demand forecasting

Hossein Abbasimehr et al.

COMPUTERS & INDUSTRIAL ENGINEERING (2020)

Article Environmental Sciences

An ensemble learning based hybrid model and framework for air pollution forecasting

Yue-Shan Chang et al.

ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH (2020)

Article Engineering, Electrical & Electronic

Bi-directional long short-term memory method based on attention mechanism and rolling update for short-term load forecasting

Shouxiang Wang et al.

INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS (2019)

Article Energy & Fuels

Asymmetric GARCH type models for asymmetric volatility characteristics analysis and wind power forecasting

Hao Chen et al.

PROTECTION AND CONTROL OF MODERN POWER SYSTEMS (2019)

Article Computer Science, Artificial Intelligence

Fine-grained attention mechanism for neural machine translation

Heeyoul Choi et al.

NEUROCOMPUTING (2018)

Article Computer Science, Artificial Intelligence

Feature selection based on mutual information: Criteria of max-dependency, max-relevance, and min-redundancy

HC Peng et al.

IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE (2005)

Article Computer Science, Artificial Intelligence

Learning to forget: Continual prediction with LSTM

FA Gers et al.

NEURAL COMPUTATION (2000)