Zobrazeno 1 - 10
of 380
pro vyhledávání: '"grid data"'
Publikováno v:
Journal of Intelligent Systems, Vol 33, Iss 1, Pp 17-8 (2024)
At present, the amount of information on power grid operation and maintenance monitoring image data is increasing, and the requirements for data compression are higher and higher. Based on the improved SPIHT image compression algorithm, this study pr
Externí odkaz:
https://doaj.org/article/71649a8f89354a57ab03a9baf9c11c43
Publikováno v:
IEEE Access, Vol 12, Pp 4523-4531 (2024)
To identify the compressed power grid fault data quickly and effectively, this paper presents a spatiotemporal location fault diagnosis method for the data compressed with set partitioning in hierarchical trees (SPIHT) algorithm. Firstly, the data fr
Externí odkaz:
https://doaj.org/article/af1c414ed5e542a79aac4600632d75fa
Publikováno v:
International Journal of Digital Earth, Vol 16, Iss 2, Pp 4446-4470 (2023)
Accurate fractional crop-planting area (FCPA) mapping is a challenging task as it requires leveraging the advantages of geographic data in detailed spatial expression and agricultural statistics in the description of crop types and quantitative chara
Externí odkaz:
https://doaj.org/article/b8c02cc765944f2b91c1a96ba33a84de
Publikováno v:
Heliyon, Vol 10, Iss 6, Pp e27116- (2024)
Climate change is an intricate global environmental concern. However, its impact is more pervasive in developing nations such as Ethiopia. Hence, this manuscript examines temperature variability and the magnitude of change over 38 years in the specif
Externí odkaz:
https://doaj.org/article/23a3e3104f3441bfab1ccf20d0cf15aa
Flood risk assessment of the naeseongcheon stream basin, Korea using the grid-based flood risk index
Publikováno v:
Journal of Hydrology: Regional Studies, Vol 51, Iss , Pp 101619- (2024)
Study Region: Naeseongcheon Stream Basin, Korea Study focus: We conducted a flood risk assessment using grid data for each indicator and a flood risk map. Using a grid-based flood risk map, grid data for the nine indicators included in the Hazard, Ex
Externí odkaz:
https://doaj.org/article/930431ebbaac4b198199a79c2705cdb3
Publikováno v:
Energies, Vol 17, Iss 15, p 3747 (2024)
With the rapid development of artificial intelligence (AI), AI has been widely applied in anomaly analysis detection and fault location in power grid data and has made significant research progress. Through looking back on traditional methods and dee
Externí odkaz:
https://doaj.org/article/7d49e77512b54cb6aa857e11b6060e1a
Publikováno v:
Remote Sensing, Vol 16, Iss 13, p 2350 (2024)
In this study, 10 min and 2 km high-resolution blended fog data (HRBFD) were generated using grid visibility data (GVD) and data from a GK2A (GEO-KOMPSAT-2A) fog product (GKFP) in Korea. As the blending method, the decision tree method (DTM) was used
Externí odkaz:
https://doaj.org/article/263f591117344774aecd9ad936cf394e
Publikováno v:
Applied Mathematics and Nonlinear Sciences, Vol 9, Iss 1 (2024)
With the development of smart grids, power grids have accumulated massive amounts of data in various links such as power generation, transmission, substation, distribution, power consumption, and dispatch. More and more big data applications are begi
Externí odkaz:
https://doaj.org/article/30be9824d40d40ed95f6c398843df555
Autor:
GUO Jun
Publikováno v:
Gong-kuang zidonghua, Vol 49, Iss 1, Pp 153-161 (2023)
The realization of multi-resolution expression and multi-parameter fusion of coal mine geological environment by using true 3D gridded geological model is one of the key contents of coal mine geological big data research. The core issues are the orga
Externí odkaz:
https://doaj.org/article/2a5349cd617e440b9a6a359f73672064
Publikováno v:
Applied Mathematics and Nonlinear Sciences, Vol 8, Iss 1, Pp 2729-2738 (2023)
Problems exist in power grid data management that have unclear relationships, weak security and low accuracy. By analysing the knowledge graph construction characteristics of smart grid data information and knowledge extraction, the grid data managem
Externí odkaz:
https://doaj.org/article/fe488b52ea36421d8ef46ea330433071