Zhang / Chen / Chu | Neural Computing for Advanced Applications | Buch | 978-981-19-6134-2 | sack.de

Buch, Englisch, Band 1638, 512 Seiten, Format (B × H): 155 mm x 235 mm, Gewicht: 797 g

Reihe: Communications in Computer and Information Science

Zhang / Chen / Chu

Neural Computing for Advanced Applications

Third International Conference, NCAA 2022, Jinan, China, July 8-10, 2022, Proceedings, Part II
1. Auflage 2022
ISBN: 978-981-19-6134-2
Verlag: Springer Nature Singapore

Third International Conference, NCAA 2022, Jinan, China, July 8-10, 2022, Proceedings, Part II

Buch, Englisch, Band 1638, 512 Seiten, Format (B × H): 155 mm x 235 mm, Gewicht: 797 g

Reihe: Communications in Computer and Information Science

ISBN: 978-981-19-6134-2
Verlag: Springer Nature Singapore


The two-volume Proceedings set CCIS 1637 and 1638 constitutes the refereed proceedings of the Third International Conference on Neural Computing for Advanced Applications, NCAA 2022, held in Jinan, China, during July 8–10, 2022.

The 77 papers included in these proceedings were carefully reviewed and selected from 205 submissions. These papers were categorized into 10 technical tracks, i.e., neural network theory, and cognitive sciences, machine learning, data mining, data security & privacy protection, and data-driven applications, computational intelligence, nature-inspired optimizers, and their engineering applications, cloud/edge/fog computing, the Internet of Things/Vehicles (IoT/IoV), and their system optimization, control systems, network synchronization, system integration, and industrial artificial intelligence, fuzzy logic, neuro-fuzzy systems, decision making, and their applications in management sciences, computer vision, image processing, and theirindustrial applications, natural language processing, machine translation, knowledge graphs, and their applications, Neural computing-based fault diagnosis, fault forecasting, prognostic management, and system modeling, and Spreading dynamics, forecasting, and other intelligent techniques against coronavirus disease (COVID-19).

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Weitere Infos & Material


Dynamic Community Detection via Adversarial Temporal Graph Representation Learning.- Research on Non-intrusive Household Load Identification Method Applying LightGBM.- Master Multiple Real-Time Strategy Games with a Unified Learning Model Using Multi-Agent Reinforcement Learning.- Research on Visual Servo Control System of Substation Insulator Washing Robot.- A Dual-size Convolutional Kernel CNN-based Approach to EEG Signal Classification.- Research and Simulation of Fuzzy Adaptive PID Control for Upper Limb Exoskeleton Robot.- Short-Term Wind Power Prediction Based on Convolutional Neural Network-Bidirectional Long Short-Term Memory Network.- Fault Arc Detection Method Based on Multi Feature Analysis and PNN.



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