Advances in Natural Computation, Fuzzy Systems and Knowledge Discovery

ISBN-13: 9783030706647 / Angielski / Miękka / 2021 / 1925 str.

Hongying Meng; Tao Lei; Maozhen Li

Spis treści

A medical image segmentation method based on pixel-to-pixel threshold.- Radar Tasks Scheduling Based on Adaptive Neuro Fuzzy Inference and Time-Interval Planning.- Ranking  Spatiotemporal RDF Properties Using Machine-Learning.- Controllability For Nonlocal Evolution Inclusions With Clarke's Subdifferential On Semi-Infinite Intervals.- Improved Parallel RSA Cryptosystem with GPU for Network Information Security.- The Recommendation Model of Personalized English Learning Resources Based on Intelligent Education.- Binaural Blind Source Separation Based on Deep Clustering.- The Approximation Of Fuzzy Number Value, Ambiguity And Expected Interval.- Machine learning based approach for Weed Detection in Chilli field using RGB images.- Disparity Estimation From Holoscopic Elemental Images.- Multi-agents Based Architecture of Remote Monitoring and Intelligent Diagnosis of Faults in Large-scale Petrochemical Systems.- An improved tracking learning detection method based on AKAZE feature points.- The Influence of Intelligent Capital on the Difference of Enterprise's Net Value and Value from the Perspective of Value Chain.- Research on hybrid algorithm based on particle swarm optimization and cuckoo search algorithm.- Application of Two-stage Sampling in Sampling Inspection.

Blurb

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 is 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 2020 16th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery (ICNC-FSKD 2020), held in Xi'an, China, from 19 to 21 December 2020. All papers were rigorously peer-reviewed by experts in the areas.