Search · four archives
Search · four archives
12 papers · ranked by Valyu relevance
Luping Wang, Xiaolong Liu, Zhihui Lai
Accurate fault diagnosis of power transformers is critical for maintaining grid reliability, yet conventional dissolved gas analysis (DGA) methods face challenges in feature representation and high-dimensional data processing. This paper presents an intelligent diagnostic framework that synergistically integrates…
Peiwen Zhang, Yunan Luo, Qian Yu, Zhifeng Zhou + 1 more
To address the challenges of increasing carbon dioxide (CO2) emissions and climate change caused by the growth of air traffic, accurate prediction of CO2 emissions in civil aviation has become crucial. This study proposes a CO2 emission prediction method based on an improved back propagation (BP) neural network, where…
Qingqing Tian, Hongyu Yang, Yu Tian, Lei Guo + 1 more
Highlights What are the main findings? 1. The proposed tSSA-Informer model achieves 90.85% diagnostic accuracy under strong noise (SNR = −9 dB) and 61.32% accuracy with only 10% labeled samples, outperforming SSA-Informer, GA-Informer, and other comparative models. 2. The tSSA algorithm optimizes Informer…
Ying Qian, Bing Liu, Beibei Su, Chunyan Zhang + 1 more
The relentless scaling of integrated circuits (ICs) into the nanoscale regime has intensified critical reliability challenges, such as Negative Bias Temperature Instability (NBTI), which manifests primarily as a progressive shift in the transistor threshold voltage (Δ V t h). This study focuses on the prognostics of…
Hongzhi Su, Pengtao Mu, Shenglin Xu, Lingrao Wang + 2 more
With the widespread application of renewable energy in microgrids, collaborative optimization scheduling of microgrid clusters has become a key issue in improving energy utilization efficiency and operational economy. To solve this problem, this paper proposes a microgrid cluster optimization scheduling method based on…
Fuqiuxuan Liu, Xiaofeng Yue, Xiang Li
This paper proposes a novel rolling bearing fault diagnosis method to address the difficulty of accurate feature extraction from nonlinear and non-stationary vibration signals. First, a Levy-Cauchy Optimized Sparrow Search Algorithm (LOCSSA) is developed to optimize the two core parameters (decomposition level and…
Bingwen Zhao, Luchan Xu, Zhenhai Zheng, Yanqi Wu + 2 more
Against global dual-carbon targets, urban residential central heating dominates building energy use and carbon emissions. Conventional LSTM forecasting requires manual hyperparameter adjustment and easily falls into local optima; micro-community carbon prediction also lacks accurate energy models and policy-based…
Edouard R. Dufour, Pascal Fua
Black-box optimization is a fundamental science and engineering tool that makes it possible to optimize objectives without gradient information. Unfortunately, as it often requires many function evaluations, it can be challenging when each one is costly. This is especially true when the evaluation function is noisy or…
Mingxuan Du, Tingzhang Luo, Ziyang Wang, Chengjun Li
In the field of artificial intelligence, real parameter singl e objective optimization is an important direction. Both the Differential Evolution (DE) and the Covariance Matrix Adaptation Evolution Strategy (CMA-ES) demonstrate good performance for real parameter single objective optimization. Nevertheless, there exist…
Junhao Wei, Wenxuan Zhu, Qingyang Xu, Yanxiao Li + 10 more
Metaheuristic algorithms have been widely applied to complex optimization problems due to their independence from gradient information, strong global search capability, and robust performance. The Sparrow Search Algorithm (SSA), characterized by its simple structure and ease of implementation, nevertheless suffers from…
Craig Reynolds
This paper describes an automatic method for adjusting or tuning models of multi-agent motion. Simulating the motion of bird flocks, human crowds, vehicle traffic, and other multi-agent systems is a widely used technique. These simulations model the behavior of a single group member (bird, human, or vehicle). The group…
Ben Kenward, Nick Casey, Perline Bastid, Francis Buner + 3 more
1. Environmental Decision Support systems provide model-based predictions, tailored to user-inputted information about local ecosystems, which can support management decisions by citizens. Citizen Science systems accept user input to improve models. Thus, each system type emphasises automatic data transfer in one…