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Titlebook: Artificial Intelligence and Environmental Sustainability; Challenges and Solut Hui Lin Ong,Ruey-an Doong,Atulya K. Nagar Book 2022 The Edit

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41#
發(fā)表于 2025-3-28 14:49:11 | 只看該作者
Oluwayemi-Oniya Aderibigbe,Trynos Gumbore seeking solutions to this problem and have set objectives in achieving digital transformation and Sustainable Development Goals by various means. Artificial intelligence is machine intelligence founded in 1950s and has been successfully applied to many areas not only in academia but also in indus
42#
發(fā)表于 2025-3-28 20:52:45 | 只看該作者
43#
發(fā)表于 2025-3-29 01:26:27 | 只看該作者
Lecture Notes in Networks and Systems, including hydrology. Understanding and simulating the rainfall-runoff (R-R) process is perhaps the most important problem in water resources engineering due to its significant role in the hydrologic cycle of water. Several climate and land-based parameters are involved in this process and are vary
44#
發(fā)表于 2025-3-29 06:36:42 | 只看該作者
Lecture Notes in Networks and Systemsr treatment technology. In the case of tableting plants, strict product quality standards also preclude the possibility of recycling mechanically defective tablets. Such waste must be handled carefully to ensure that traces of active pharmaceutical ingredients do not end up in ecosystems. In additio
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發(fā)表于 2025-3-29 08:06:02 | 只看該作者
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發(fā)表于 2025-3-29 14:20:23 | 只看該作者
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發(fā)表于 2025-3-29 16:40:59 | 只看該作者
48#
發(fā)表于 2025-3-29 21:47:49 | 只看該作者
Lecture Notes in Networks and Systemsa analysis, advanced classification algorithms, storage, etc. Cloud-based AI and remote sensing services allow users (with little technical background) to analyse imagery with high precision. This research has been conducted using Remote Ecosystem Monitoring Assessment Pipeline (remap) cloud service
49#
發(fā)表于 2025-3-30 00:08:39 | 只看該作者
https://doi.org/10.1007/978-981-97-3991-2tions and use to benefit society, it is crucial to provide a monitoring mechanism to these pipeline systems not to be detrimental to the environment. This study focused on a machine learning approach to provide a framework for monitoring oil pipeline spills that often result in explosions and fire o
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發(fā)表于 2025-3-30 04:48:16 | 只看該作者
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