The Bidirectional Information Fusion Using an Improved LSTM Model

Abstract

The information fusion technology is of great significance in intelligent systems. At present, the modern coal-fired power plant has the fully functional sensor network. However, many data that are important for the operation of a power plant, such as the coal quality, cannot be directly obtained. Therefore, the information fusion technology needs to be introduced to obtain the implied information of the power plant. As a practical application, the soft measurement of coal quality is taken as the research object. This paper proposes an improved LSTM model combined with the bidirectional deep fusion, alertness mechanism, and parameter self-learning (DFAS-LSTM) to realize online soft computing for the coal quality analyses of industries and elements. First, a latent structure model is established to preprocess the noisy and redundant sensor network data. Second, an alertness mechanism is proposed and the self-learning method of the activation function parameters is used for the data feature extraction. Third, a deeply bidirectional fusion layer is added to the long short-term memory neural network model to solve the problem of the insufficient accuracy and the weak generalization. Using the historical data of the sensor network, the DFAS-LSTM model is established. Then, the online data of the sensor network is input to the DFAS-LSTM model to implement the online coal quality analyses. Experiment shows that the accuracy of the coal quality analyses is increased by 1%–2.42% compared to the traditionally bidirectional LSTM.

Architecture, Technologies, and Applications of Location-Based Services

“…This special issue includes five papers on LBS for industry which are listed as follows. LSB techniques were applied on enterprise management systems [51], improved LSTM models for industry system [52], human-machine interfaces [53], e-commerce services [54], and public safety evaluation system [55] for providing industry applications. Detailed information of each article related to LBS for industry could be found in [51][52][53][54][55].…”

Surgical Striking SQL Injection Attacks Using LSTM

“…An updated LSTM model with bidirectional deep fusion, alertness mechanisms, and parameter self-learning has been presented by Tianwei Zheng et al [10] to accomplish online soft computing for industries and elements' coal quality evaluations. To begin, a model of latent structure was constructed to help with the preprocessing of the noisy and redundant sensor network data.…”