Titlebook: Digital Transformation; Industry 4.0 to Soci Avadhesh Kumar,Shrddha Sagar,B. Balamurugan Book 2024 The Editor(s) (if applicable) and The Au

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Md-Mizanur Rahoman,Ryutaro Ichise this chapter, we have discussed various deep learning models that are specifically used for the prediction of traffic flow. The utilization of Deep Learning (DL) frameworks in transportation is yet to be explored more in detail and there is a lot of problems for DL models to be implemented in the t

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A Lightweight Treatment of Inexact Dates making the system smart and reliable, as well as improving the efficiency and cost-effectiveness of functionality and improvements. This work presents a new cost-effective and adaptive clustering algorithm that can enhance computing efficiency while maintaining clustering accuracy. In this system c

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Semantic Under-determinacy and Communication in decision-making process, rather than replacing us with smart algorithms. The past Society 4.0 was encountering a threat when AI and machine learning boomed up in routine walks of life. Individuals believed that they would be replaced by robots and smart systems in near future. However, it was re

Munificent

Bernd Wohlkinger,Tassilo Pellegrinit who can readily get huge data from the public domain may misuse it due to the increased threat of cyber-attacks. To ensure data security, data collecting organisations and enterprises must state the goal of obtaining data and maintain all data management regulations as routine safety measures. To

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