Quan Xie & Liang Zhao 
Advances in Natural Computation, Fuzzy Systems and Knowledge Discovery [PDF ebook] 
Proceedings of the ICNC-FSKD 2021

Wsparcie

This book consists of papers on the recent progresses in the state of the art in natural computation, fuzzy systems and knowledge discovery. The book can be useful for researchers, including professors, graduate students, as well as R & D staff in the industry, with a general interest in natural computation, fuzzy systems and knowledge discovery. The work printed in this book was presented at the 2021 17th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery (ICNC-FSKD 2021, 24–26 July 2021, Guiyang, China). All papers were rigorously peer-reviewed by experts in the areas.

€255.73
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Spis treści

RRS:An Explainable Model Scale Search Strategy.- Detection of Small Targets in Aerial Images based on Feature Fusion.- Intrusion Detection Based on LSTM and Random Forests.- Research and Hardware Implementation of Binocular Vision Obstacle Avoidance for UAV.- Parameter Estimation of Equivalent Circuit Model for Lithium Batteries.- Improved U-Net Network for Segmentation on Femur Images.- A 14-bit 2MS/s Digital Self-Calibrating SAR ADC Design and Simulation.- A Windowed Interpolation Algorithm for High-precision ADC Spectrum Testing.- Temperature Compensation Algorithms Based on Digital Infrared Thermopile Sensors Systems.- Optimizing Deep-Learning Inference Operations.- An Efficient MRI Impulse Noise Multi-Stage Hybrid Filter Based on Cartesian Genetic Programming.- Multi-Objective Strategy Based on Rational Particle Swarm Optimization for Environmental/Economic Dispatch.- Express Service Composition Optimization Based on Improved Ant Colony Algorithm.
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Język Angielski ● Format PDF ● Strony 1439 ● ISBN 9783030896980 ● Rozmiar pliku 133.8 MB ● Redaktor Quan Xie & Liang Zhao ● Wydawca Springer International Publishing ● Miasto Cham ● Kraj CH ● Opublikowany 2022 ● Do pobrania 24 miesięcy ● Waluta EUR ● ID 8262766 ● Ochrona przed kopiowaniem Społeczny DRM

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