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Titlebook: Advances in Computing and Data Sciences; Third International Mayank Singh,P.K. Gupta,Rekha Kashyap Conference proceedings 2019 Springer Na

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期刊全称Advances in Computing and Data Sciences
期刊简称Third International
影响因子2023Mayank Singh,P.K. Gupta,Rekha Kashyap
视频video
学科分类Communications in Computer and Information Science
图书封面Titlebook: Advances in Computing and Data Sciences; Third International  Mayank Singh,P.K. Gupta,Rekha Kashyap Conference proceedings 2019 Springer Na
影响因子This two-volume set (CCIS 1045 and CCIS 1046) constitutes the refereed proceedings of the Third International Conference on Advances in Computing and Data Sciences, ICACDS 2019, held in Ghaziabad, India, in April 2019..The 112 full papers were carefully reviewed and selected from 621 submissions. The papers are centered around topics like advanced computing, data sciences, distributed systems organizing principles, development frameworks and environments, software verification and validation, computational complexity and cryptography, machine learning theory, database theory, probabilistic representations. .
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Data in a concurrent environment,ch analysis, as it is prepared on (14 + 2) electrodes. In both datasets same number of electrodes are used. Experimental results confirm that accuracy of both datasets are compatible with each other. AMIGOS dataset shows 80.12% accuracy and prepared dataset shows 74.62% accuracy using SVM classifier.
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Lecture Notes in Computer Sciencee developed system works automatically and independent of component names so that manual errors can be avoided. Assembly sequence generation helps in reducing complexity to be analyzed by human expert.
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José Igreja,Filipe A. Barata,Carla Viveiros comparative study, different ML techniques are used by the proposed system to achieve better accuracy in disease prediction. Among these, Decision tree algorithm is found to be better with the accuracy of 99.46%.
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https://doi.org/10.1007/978-3-031-10047-5zy Petri net and a precedent-subsequent relation between the two fuzzy propositions of BPNs has been checked using fuzzified propositional algorithm. This relation provides an important property of BPNs based on initial marking of Petri nets and the obtained truth degree of the success node validates the belief strength of this property.
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