Zobrazeno 1 - 10
of 502
pro vyhledávání: '"abnormal data"'
Autor:
Nan Liu
Publikováno v:
Systems Science & Control Engineering, Vol 12, Iss 1 (2024)
The internal simulation market system can stimulate employee initiative, reduce costs and improve information processing efficiency. However, the complexity of the internal simulation market poses a challenge to computing resources. Efficient data pr
Externí odkaz:
https://doaj.org/article/0486f5503b9a4e53805e3618dad5d851
Publikováno v:
Global Energy Interconnection, Vol 7, Iss 3, Pp 293-312 (2024)
Current methodologies for cleaning wind power anomaly data exhibit limited capabilities in identifying abnormal data within extensive datasets and struggle to accommodate the considerable variability and intricacy of wind farm data. Consequently, a m
Externí odkaz:
https://doaj.org/article/9dcc92e69cb44e8ca9d274b152a99952
Publikováno v:
应用气象学报, Vol 34, Iss 6, Pp 694-705 (2023)
The world's largest weather radar observation network which consists of 236 weather radars is built up in China. The quality control of weather radar data becomes an indispensable part in operation as data grow. In real-time operation of CMA Meterolo
Externí odkaz:
https://doaj.org/article/1fd2a3501f4b44fda4ebc4339301f5f8
Publikováno v:
电力工程技术, Vol 42, Iss 4, Pp 167-174 (2023)
In order to ensure the accurate application of the data collected by the phasor measurement unit (PMU), it is necessary to eliminate the abnormal data in its measured values. The existing PMU abnormal data identification algorithm has the disadvantag
Externí odkaz:
https://doaj.org/article/09c45965f7a34f22af624c9f628b56be
Publikováno v:
Developments in the Built Environment, Vol 17, Iss , Pp 100337- (2024)
Structural health monitoring (SHM) is widely used to monitor and assess the condition and performance of engineering structures such as, buildings, bridges, dams, and tunnels. Owing to sensor defects, data acquisition errors, and environmental interf
Externí odkaz:
https://doaj.org/article/71460e0600fe47239e436e26e921b92d
Publikováno v:
Energy Reports, Vol 9, Iss , Pp 226-233 (2023)
On the basis of YOLO deep network detection method, a new abnormal data detection method is proposed to meet the needs of gas boiler abnormal data detection. In the feature extraction layer, the SENet structure is embedded between DBL and Pooling. Th
Externí odkaz:
https://doaj.org/article/bea58c97941e4c2c9ccce88d190b4d97
Publikováno v:
Journal of Safety Science and Resilience, Vol 4, Iss 1, Pp 61-74 (2023)
Grain security guarantees national security. China has many widely distributed grain depots to supervise grain storage security. However, this has led to a lack of regulatory capacity and manpower. Amid the development of reserve-level information te
Externí odkaz:
https://doaj.org/article/081a84d39a9e4ba9ade747e06bf6321d
Autor:
Dai Jingyi, Ke Dandan
Publikováno v:
Applied Mathematics and Nonlinear Sciences, Vol 8, Iss 1, Pp 2567-2580 (2023)
Projects of engineering construction have the characteristics of large investment and long cycle, which makes the cost management difficult and the data are often abnormal. Therefore, it is necessary to strengthen the detection of abnormal data in en
Externí odkaz:
https://doaj.org/article/818cb5d240524e14bcf0b57bbddbbbb8
Autor:
Hien Van LE
Publikováno v:
Journal of Materials and Engineering Structures, Vol 9, Iss 4, Pp 421-426 (2022)
Global Positioning System (GPS) or currently upgraded to Global Navigation Satellite System (GNSS) has been applied in many SHM systems of the super-structures, especially in the long-span bridges. A GNSS system has the ability in monitoring the glob
Externí odkaz:
https://doaj.org/article/caee6ba8fc984ced88f228396964bf30
Publikováno v:
Haiyang Kaifa yu guanli, Vol 39, Iss 12, Pp 29-36 (2022)
Accurate data is the basis for all marine scientific research. Different from the traditional sampling monitoring process, it is fully automated for marine buoy monitoring from sample collection to data results, and the focus of data quality control
Externí odkaz:
https://doaj.org/article/50836c4937f9489a9b39ac180ea9c082