The proposed architecture is found to be accurate for real-time characterization and classification of power quality disturbances in smart grid. 展开 关键词: Smart grid distributed generation system deep power power quality disturbances deep learning classification ...
However, monotonic optimization is an\niterative algorithm and can often entail considerable computational complexity,\nmaking it not suitable for real-time applications. To address this, we propose\na learning-based approach that treats the input and output of a resource\nallocation algorithm as an...
This paper presents a visualisation method, based on deep learning, to assist power engineers in the analysis of large amounts of power-quality data. The method assists in extracting and understanding daily, weekly and seasonal variations in harmonic voltage. Measurements from 10 kV and 0.4 kV ...
In this paper, a deep learning-based method is introduced into the classification of power quality disturbances (PQDs). Stacked autoencoder, as a deep learning framework, is employed to extract high-level features of PQDs for classification. In this context, a previously unsolved issue regarding...
2. An Overview of Quality of Service and Deep Learning Algorithms for Internet of Things 2.1. Quality of Service in Internet of Things QoS is the measurement of the general performance of any service, mainly the performance seen by the users of the service [36,37,38]. Owing to the widespr...
Visualizing a deep learning workflow from data preparation to deployment. Data for Deep Learning Deep learning requires large amounts of good-quality data. You can usedatastoresto conveniently manage collections of data that are too large to fit in memory at one time. You can use low-code apps...
Fig. 3: Explainable deep learning showing saliency maps for predictive understanding with the network model representations. a, b Saliency Map for Amazon River flow prediction using Earth System Models (ESM) (a) and reanalysis (b) sea surface temperature (SST), respectively. c, d Saliency Map ...
Deep learning is a subset of machine learning that uses multilayered neural networks, to simulate the complex decision-making power of the human brain.
Deep learning has revolutionized the analysis and interpretation of satellite and aerial imagery, addressing unique challenges such as vast image sizes and a wide array of object classes. This repository provides an exhaustive overview of deep learning techniques specifically tailored for satellite and ...
2 The book tells us the core abilities for thriving in the new economy, which are the abi⁃lity to quickly master hard things and the ability to produce at a high level, in terms of both quality and speed. If you can t learn, you can t thrive. If you don t produce, you won ...