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Titlebook: International Conference on Intelligent and Smart Computing in Data Analytics; ISCDA 2020 Siddhartha Bhattacharyya,Janmenjoy Nayak,Ajith Ab

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發(fā)表于 2025-3-21 17:14:12 | 只看該作者 |倒序瀏覽 |閱讀模式
書目名稱International Conference on Intelligent and Smart Computing in Data Analytics
副標(biāo)題ISCDA 2020
編輯Siddhartha Bhattacharyya,Janmenjoy Nayak,Ajith Abr
視頻videohttp://file.papertrans.cn/472/471408/471408.mp4
概述Presents recent research in the field of intelligent computing and data analytics.Discusses the outcomes of ISCDA 2020, held in Andhra Pradesh, India.Serves as a reference resource for researchers and
叢書名稱Advances in Intelligent Systems and Computing
圖書封面Titlebook: International Conference on Intelligent and Smart Computing in Data Analytics; ISCDA 2020 Siddhartha Bhattacharyya,Janmenjoy Nayak,Ajith Ab
描述.This book is a collection of best selected research papers presented at International Conference on Intelligent and Smart Computing in Data Analytics (ISCDA 2020), held at K L University, Guntur, Andhra Pradesh, India. The primary focus is to address issues and developments in advanced computing, intelligent models and applications, smart technologies and applications. It includes topics such as artificial intelligence and machine learning, pattern recognition and analysis, computational intelligence, signal and image processing, bioinformatics, ubiquitous computing, genetic fuzzy systems, hybrid evolutionary algorithms, nature-inspired smart hybrid systems, Internet of things, industrial IoT, health informatics, human–computer interaction and social network analysis. The book presents innovative work by leading academics, researchers and experts from industry.?.
出版日期Conference proceedings 2021
關(guān)鍵詞Intelligent Computing; Data Analytics; Signal and Image Processing; Ubiquitous Computing; Hybrid Evoluti
版次1
doihttps://doi.org/10.1007/978-981-33-6176-8
isbn_softcover978-981-33-6175-1
isbn_ebook978-981-33-6176-8Series ISSN 2194-5357 Series E-ISSN 2194-5365
issn_series 2194-5357
copyrightThe Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapor
The information of publication is updating

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,Binary PSO-Based Feature Selection and Neural Network for Parkinson’s Disease Prediction,on. A classification accuracy of 89.74% is achieved using PSO-NN, while this rate is 87.69% in PSO-SGD, 86.67% in PSO-LR, and 81.54% in PSO-SVM. Thus, application of neural networks gave the best accurate prediction of disease.
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Conference proceedings 2021 (ISCDA 2020), held at K L University, Guntur, Andhra Pradesh, India. The primary focus is to address issues and developments in advanced computing, intelligent models and applications, smart technologies and applications. It includes topics such as artificial intelligence and machine learning, patt
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Novel Defense Framework for Cross-layer Attacks in Cognitive Radio Networks,d small backoff window (SBW) attack in MAC layer. Simulation results shows that our proposed solutions perform in reducing these two attacks and significantly reduce the attack probability and increase channel utilization by primary users.
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Facial Expression Detection Model of Seven Expression Types Using Hybrid Feature Selection and Deep540 images. We proposed a hybrid model of feature selection that is used before feeding to the proposed computing model of CNN architecture. We claim through the use of both the models one after the other the emotions is correctly recognized with high accuracy during both training and testing phases, which the conventional method doesn’t have.
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