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Titlebook: Business Intelligence for Enterprise Internet of Things; Anandakumar Haldorai,Arulmurugan Ramu,Syed Abdul R Book 2020 Springer Nature Swit

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11#
發(fā)表于 2025-3-23 11:37:59 | 只看該作者
12#
發(fā)表于 2025-3-23 17:26:09 | 只看該作者
Organization Internet of Things (IoTs): Supervised, Unsupervised, and Reinforcement Learning,users have to be authenticated so as to utilize various applications and services of IoTs. Normally, IoTs services and applications are centered on information exchange over various platforms. The information obtained from IoTs devices is processed, pre-processed, and forwarded via decision-support
13#
發(fā)表于 2025-3-23 21:26:30 | 只看該作者
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發(fā)表于 2025-3-24 01:16:08 | 只看該作者
Advanced Machine Learning for Enterprise IoT Modeling,gorithms that can be employed in a different perspective of enterprise IoT and their applications are presented here. This would be a great help for the researchers and practitioners in the field of enterprise?IoT.
15#
發(fā)表于 2025-3-24 02:42:43 | 只看該作者
Enterprise Architecture for IoT: Challenges and Business Trends,overview of industrial IoTs. Moreover, the chapter evaluates the IoTs architecture, its services, and the relevant challenges, including the models that are vital for the deployment and selection of the various IoTs services in different industrial settings which will be analyzed in various case stu
16#
發(fā)表于 2025-3-24 10:16:12 | 只看該作者
On-the-Go Network Establishment of IoT Devices to Meet the Need of Processing Big Data Using Machined based on machine learning algorithms. Data distribution is made on the basis of publishing/subscribing method. For continuous connectivity of devices in wired and wireless links, standard communication protocols are essential to manage the high traffic in the network as well. Added to it, new sol
17#
發(fā)表于 2025-3-24 13:18:19 | 只看該作者
18#
發(fā)表于 2025-3-24 16:12:27 | 只看該作者
19#
發(fā)表于 2025-3-24 20:42:15 | 只看該作者
Emphasizing on Space Complexity in Enterprise Social Networks for the Investigation of Link Predicty show that this approach can reduce the space complexity for forecasting the links that will occur in future. The proposed approach significantly improves the performance of link prediction in social networks.
20#
發(fā)表于 2025-3-24 23:25:22 | 只看該作者
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