The transition to electric vehicles (EVs) has heightened the significance of secondary noise sources, such as buzz, squeak, and rattle (BSR), which can detract from vehicle quality and customer satisfaction. Among the...
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In this paper, we develop a modelingprocess of 3D woven preform considering it's weaving mechanism. By analyzing the weaving mechanism, three design control parameters are defined. With various combinations of th...
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The proposed system integrates driver training simulations with Internet of Things (IoT) technologies to improve driver training plans by monitoring and analyzing learners' performance in real-time. The proposed s...
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With the improvement of process level and the development of intelligent technology, it becomes possible to obtain the operating parameters of the heating pipe network in real time, and the heating effect can be optim...
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The unstructured operation ticket text data generated during the operation and maintenance process of the power system has a large inventory, high value density, and strong timeliness. Studying the data information co...
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ISBN:
(纸本)9798331516086
The unstructured operation ticket text data generated during the operation and maintenance process of the power system has a large inventory, high value density, and strong timeliness. Studying the data information contained in it is of great significance for reducing the probability of operation accidents and achieving substation safety risk control. However, traditional unstructured processing models are difficult to effectively utilize it, which poses many challenges to the mining of operation ticket text data and leads to waste of operation ticket text data. At the same time, in terms of substation safety control, traditional video surveillance can only achieve post alarm and requires manual intervention, and combining video surveillance with operation ticket text mining poses certain difficulties. In response to the above issues, a method for extracting and mining operation ticket text data is proposed by combining relevant technologies of natural language processing. This method compares the segmentation effects of operation ticket text based on statistical and dictionary methods, proposes a pre-processing method for operation ticket text segmentation with dictionary method as the main method and statistical method as the auxiliary method, and then compares the operation ticket text represented by discrete representation and distributed representation. The distributed method is used to represent the operation ticket text, and the word vector is obtained through training. Finally, based on the analysis of the advantages and disadvantages of the long short-term memory network model and the conditional random field model, the BiLSTM CRF algorithm combining the two is used to achieve named entity recognition of operation ticket text, with an accuracy of over 90%. At the same time, the traditional entity relationship extraction method based on feature vectors is targeted. The recognition accuracy is low Unable to effectively utilize contextual information and other
With the increasing focus on data mining and machine learning (ML) applications in the oil and gas industry, the substantial number of well integrity logs and variety of data types represent a suitable candidate for t...
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ISBN:
(纸本)9781613998359
With the increasing focus on data mining and machine learning (ML) applications in the oil and gas industry, the substantial number of well integrity logs and variety of data types represent a suitable candidate for the implementation of automated corrosion log processing. Convolutional neural networks (CNNs) are used in many fields, especially for image processing and features recognition. On the other hand, genetic algorithms (GA) add a valuable benefit to dataprocessing in terms of global search and optimization. This paper demonstrates the integration of ML techniques with legacy well integrity log data, improving the results and leading to a tangible time and cost savings. A downhole well integrity evaluation triangle comprises three important services for comprehensive diagnosis: 1) cement evaluation, 2) corrosion inspection, and 3) leak detection. These services produce multiple datasets from a variety of logging tools. The types and sources of these datasets include synthetic data from simulation and modeling, tool calibration and lab testing, as well as raw, processed, and interpreted data. This paper describes the use of advanced ML techniques to scrutinize and improve well integrity evaluation. The new process resolves the recurrent challenges of well integrity evaluation in complex completion and downhole environments. It also maximizes value from existing well and field data. Image features recognition enables major improvements in the dataanalysis, such as the identification of concentric casings and tubing as well as their respective collar depths and types. In addition, input parameters and well schematics promote quality control of recorded data versus the model data. The new process helps to identify casing and completion accessories and provides a reliable benchmark. Another major element is the qualitative and quantitative evaluation of corrosion using deep learning algorithms combined with the GA. This evaluation is achieved using feature extr
In the process of chemical production, each subsystem is coupled with the other to form an interconnected system. On the one hand, the interconnected system has a physical correlation. On the other hand, the subsystem...
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ISBN:
(纸本)9788993215236
In the process of chemical production, each subsystem is coupled with the other to form an interconnected system. On the one hand, the interconnected system has a physical correlation. On the other hand, the subsystem also has a topological relationship in communication for consensus control. In this paper, the dynamic linearization model of a large-scale interconnected system is established, and the local adjacency error is defined. The strong robustness in the presence of external interference can be guaranteed by design. Theoretical analysis shows that the designed controller has good stability, and the effect of the controller on the interconnected system is verified by simulation.
This paper proposes an application anomaly detection and bottleneck identification system (AAD-PSC) based on cloud platform service components. The system can monitor and analyze applications on multi-layered cloud pl...
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After the recent ups and downs in cryptocurrency values, bitcoin is now more frequently seen as a valuable investment. Due to its extreme volatility, there is a stronger requirement for precise forecasts that support ...
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In the 14th Five-Year Plan, China Southern Power Grid Corporation proposed the large-scale construction of smart substations to provide support for the construction of new power systems. However, there are problems in...
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