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Empowering Distributed Solutions in Renewable Energy Systems and Grid Optimization
This study delves into the shift from centralized to decentralized approaches in the electricity industry, with a particular focus on how machine learning (ML) advancements play a crucial role in empowering renewable energy sources and improving grid management.
Deep neural operator for learning transient response of interpenetrating phase composites subject to dynamic loading
After an offline training, the DNO model can act as surrogate of physics-based FEA to predict the transient mechanical response in terms of reaction force and stress distribution of the IPCs to various strain loads in one second at an accuracy of 98%.
TM-vector: A Novel Forecasting Approach for Market stock movement with a Rich Representation of Twitter and Market data
Various factors have been used for the effectiveness of the proposed forecasting approach, including the characteristics of each individual user, their impact on each other, and their impact on the market, to predict market direction more accurately.
Low-energy decomposition results over finite fields
We prove various low-energy decomposition results, showing that we can decompose a finite set $A\subset \mathbb{F}_p$ satisfying $|A|<p^{5/8}$, into $A = S\sqcup T$ so that, for a non-degenerate quadratic $f\in \mathbb{F}_p[x, y]$, we have \[ |\{(s_1, s_2, s_3, s_4)\in S^4 : s_1 + s_2 = s_3 + s_4\}| \ll |A|^{3 - \frac15 + \varepsilon} \] and \[ |\{(t_1, t_2, t_3, t_4)\in T^4 : f(t_1, t_2) = f(t_3, t_4)\}|\ll |A|^{3 - \frac15 + \varepsilon}\,.
Combinatorics Number Theory 11B75
