Zobrazeno 1 - 10
of 951
pro vyhledávání: '"Ma Jianwei"'
Publikováno v:
Applied Mathematics and Nonlinear Sciences, Vol 9, Iss 1 (2024)
Electricity is a matter of national livelihood, and monitoring the operation status of the distribution network is an effective means to improve the quality of electricity service. In this paper, we design a distribution network intelligent monitorin
Externí odkaz:
https://doaj.org/article/e0c6d94b5a9043c4b81b7b4aadd8fa2c
Publikováno v:
Applied Mathematics and Nonlinear Sciences, Vol 9, Iss 1 (2024)
Transparent grid, as an advanced form of “Internet + smart energy”, is of great value in supporting energy transformation and promoting the development of new power systems. Based on the grid connection requirements of high-density distributed po
Externí odkaz:
https://doaj.org/article/3aea53d291ca41c7ba4dbd1b4b6f2ae0
Publikováno v:
Applied Mathematics and Nonlinear Sciences, Vol 9, Iss 1 (2024)
In this paper, we preprocess the equipment data using by exponential smoothing method, fit the fault information by using the distribution model, and evaluate the fitting degree of the function with the help of the K-S test to derive the equipment fa
Externí odkaz:
https://doaj.org/article/1d148d4cd8094f0d9d667ba94de6beda
Publikováno v:
Applied Mathematics and Nonlinear Sciences, Vol 9, Iss 1 (2024)
In this study, we evaluate the enhanced carrying capacity of the modified IEEE 33-node distribution system, which incorporates a high percentage of distributed resource (DR) integration, utilizing the whale optimization algorithm. The evaluation empl
Externí odkaz:
https://doaj.org/article/e2c7d763250648b0834f7420a78833da
Recently, large models, or foundation models, have exhibited remarkable performance, profoundly impacting research paradigms in diverse domains. Foundation models, trained on extensive and diverse datasets, provide exceptional generalization abilitie
Externí odkaz:
http://arxiv.org/abs/2406.03163
Biologically, the brain does not rely on a single type of neuron that universally functions in all aspects. Instead, it acts as a sophisticated designer of task-based neurons. In this study, we address the following question: since the human brain is
Externí odkaz:
http://arxiv.org/abs/2405.02369
Identifying objects in given data is a task frequently encountered in many applications. Finding vehicles or persons in video data, tracking seismic waves in geophysical exploration data, or predicting a storm front movement from meteorological measu
Externí odkaz:
http://arxiv.org/abs/2402.02395
Frequency-domain simulation of seismic waves plays an important role in seismic inversion, but it remains challenging in large models. The recently proposed physics-informed neural network (PINN), as an effective deep learning method, has achieved su
Externí odkaz:
http://arxiv.org/abs/2208.08276
Autor:
Qiu, Kun, Chang, Harry, Wang, Ying, Yu, Xiahui, Zhu, Wenjun, Liu, Yingqi, Ma, Jianwei, Li, Weigang, Liu, Xiaobo, Dai, Shuo
Sophisticated traffic analytics, such as the encrypted traffic analytics and unknown malware detection, emphasizes the need for advanced methods to analyze the network traffic. Traditional methods of using fixed patterns, signature matching, and rule
Externí odkaz:
http://arxiv.org/abs/2208.07558
Autor:
Bossmann, Florian, Ma, Jianwei
Publikováno v:
Inverse Problems 38 125009, 2022
Data processing has to deal with many practical difficulties. Data is often corrupted by artifacts or noise and acquiring data can be expensive and difficult. Thus, the given data is often incomplete and inaccurate. To overcome these problems, it is
Externí odkaz:
http://arxiv.org/abs/2206.00365