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Titlebook: Evaluation Platform of Sustainability for Global Systems; Statistical Approach Aki-Hiro Sato,Hiroe Tsubaki Book 2024 The Editor(s) (if appl

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11#
發(fā)表于 2025-3-23 10:39:48 | 只看該作者
https://doi.org/10.1007/978-3-540-33259-6tics have been developed since the 1960s for both industrial and government usage in Japan. Finally, we show the definition of the World Grid Squares as an extension of JIS X0410:2002 for worldwide usage.
12#
發(fā)表于 2025-3-23 16:40:22 | 只看該作者
13#
發(fā)表于 2025-3-23 21:30:33 | 只看該作者
,Grid Squares and?Grid Square Statistics,tics have been developed since the 1960s for both industrial and government usage in Japan. Finally, we show the definition of the World Grid Squares as an extension of JIS X0410:2002 for worldwide usage.
14#
發(fā)表于 2025-3-24 01:29:15 | 只看該作者
15#
發(fā)表于 2025-3-24 03:36:36 | 只看該作者
Distributed Architecture for Grid Square Statistics,-conquer methods. We mention Amdahl’s law and Gustafson’s law. Moreover, we find an implementation of Web API a useful method to exchange data among elements of a distributed system. Finally, we propose a parallelization and distributed architecture for Grid Square statistics.
16#
發(fā)表于 2025-3-24 09:39:11 | 只看該作者
Book 2024olution to approach geospatial data for big data integration. Grid Square statistics is a technique that allows us to collect and analyze data based on Grids and makes it easier to understand patterns and trends. Sustainability, a key concern for the future of our society, often involves balancing m
17#
發(fā)表于 2025-3-24 11:25:40 | 只看該作者
Aki-Hiro Sato,Hiroe TsubakiExplains how to compute Grid Square statistics from datasets with geospatial information and system architecture.Provides exemplary studies for combining Grid Square statistics and data for measuring
18#
發(fā)表于 2025-3-24 18:40:36 | 只看該作者
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19#
發(fā)表于 2025-3-24 19:56:16 | 只看該作者
The Fallacy of Sustainable Change,ioeconomic-environmental systems and is formalized as multi-dimensional optimization problems containing several key performance indicators. Big data has enabled us to analyze and improve our world from a holistic point of view. Moreover, geospatial big data enhances the understanding of sustainabil
20#
發(fā)表于 2025-3-25 01:14:02 | 只看該作者
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