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Titlebook: Machine Learning for Environmental Noise Classification in Smart Cities; Ali Othman Albaji Book 2024 The Editor(s) (if applicable) and The

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發(fā)表于 2025-3-21 19:05:46 | 只看該作者 |倒序?yàn)g覽 |閱讀模式
書目名稱Machine Learning for Environmental Noise Classification in Smart Cities
編輯Ali Othman Albaji
視頻videohttp://file.papertrans.cn/621/620620/620620.mp4
概述Machine learning-based sound classifier for environmental noise.Qualitative analysis of community perceptions based on a noise pollution survey.Create an interactive web dashboard and data warehousing
叢書名稱Synthesis Lectures on Engineering, Science, and Technology
圖書封面Titlebook: Machine Learning for Environmental Noise Classification in Smart Cities;  Ali Othman Albaji Book 2024 The Editor(s) (if applicable) and The
描述.We present a Machine Learning (ML) approach to monitoring and classifying noise pollution. Both methods of monitoring and classificationhave been proven successful. MATLAB and Python code was generated to monitor alltypes of noise pollution from the collected data, while ML was trained to classify these data. ML algorithms showed promising performance in monitoring the different sound classes such as highways, railways, trains and birds, airports and many more. It is observed that all the data obtained by both methods can be used to control noise pollution levels and for data analytics. They can help decision making and policy making by stakeholders such as municipalities, housing authorities and urban planners in smart cities. The findings indicate that ML can be used effectively in monitoring and measurement. Improvements can be obtained by enhancing the data collection methods. The intention is to develop more ML platforms from which to construct a less noisy. The second objective of this study was to visualize and analyze the data of 18 types of noise pollution that have been collected from 16 different locations in Malaysia. All the collected datawere stored in Tableau softwa
出版日期Book 2024
關(guān)鍵詞MATLAB; Machine Learning; PYTHON; Artificial Intelligence; Smart cities; Noise pollution; Urbanity
版次1
doihttps://doi.org/10.1007/978-3-031-54667-9
isbn_softcover978-3-031-54669-3
isbn_ebook978-3-031-54667-9Series ISSN 2690-0300 Series E-ISSN 2690-0327
issn_series 2690-0300
copyrightThe Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerl
The information of publication is updating

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沙發(fā)
發(fā)表于 2025-3-21 20:34:27 | 只看該作者
板凳
發(fā)表于 2025-3-22 01:30:55 | 只看該作者
978-3-031-54669-3The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerl
地板
發(fā)表于 2025-3-22 07:05:25 | 只看該作者
Machine Learning for Environmental Noise Classification in Smart Cities978-3-031-54667-9Series ISSN 2690-0300 Series E-ISSN 2690-0327
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Synthesis Lectures on Engineering, Science, and Technologyhttp://image.papertrans.cn/m/image/620620.jpg
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發(fā)表于 2025-3-22 20:24:08 | 只看該作者
Introduction,People‘s duties have had a significant impact on engineering and scientific careers in the last several decades.
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發(fā)表于 2025-3-23 02:29:43 | 只看該作者
Results and Discussion,This chapter discusses the findings of the project. The results will be divided into two parts for better explanations.
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發(fā)表于 2025-3-23 06:15:22 | 只看該作者
https://doi.org/10.1007/978-3-031-54667-9MATLAB; Machine Learning; PYTHON; Artificial Intelligence; Smart cities; Noise pollution; Urbanity
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