智能环境

IF 1.4 2区 哲学 Q1 HISTORY & PHILOSOPHY OF SCIENCE Social Epistemology Pub Date : 2023-11-28 DOI:10.1080/02691728.2023.2277230
T. Perković, P. Šolić, D. Čoko, Ivo Andrić, Mohan Lal Kolhe
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引用次数: 0

摘要

智能环境中联网设备的数量呈指数级增长,这些设备收集的数据也需要进行适当的分析。从这些数据中提取有意义的信息并对数据进行关联,是在智能环境场景中成功实施的关键因素。技术的巨大进步,包括低成本和大规模计算、硬件和存储,促进了机器学习的实现,为数据分析和根据过去的观测结果对给定的新测量进行精确预测带来了巨大潜力。本特刊旨在收集可用于未来智能环境架构的各种资料。
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Smart Environments
The number of connected devices in smart environments keeps increasing exponentially, as well as the data collected by these devices that need to be properly analyzed. The extraction of meaningful information and the correlation of the data from such data is a key factor in the successful implementation in smart environment scenarios. Great progress in technology, which include low-cost and massive computing, hardware, and storage facilitated Machine Learning implementations that hold a vast potential for data analysis and precise predictions made from the past observations for given new measurements. The aim of this Special issue is to gather different contributions that can be used in future smart environment architectures.
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来源期刊
CiteScore
2.60
自引率
17.60%
发文量
60
期刊介绍: Social Epistemology provides a forum for philosophical and social scientific enquiry that incorporates the work of scholars from a variety of disciplines who share a concern with the production, assessment and validation of knowledge. The journal covers both empirical research into the origination and transmission of knowledge and normative considerations which arise as such research is implemented, serving as a guide for directing contemporary knowledge enterprises. Social Epistemology publishes "exchanges" which are the collective product of several contributors and take the form of critical syntheses, open peer commentaries interviews, applications, provocations, reviews and responses
期刊最新文献
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