Results 91 to 100 of about 166,225,520 (254)
Network reconfiguration is of theoretical and practical significance to guarantee safe and economical operation of distribution system. In this paper, based on all spanning trees of undirected graph, a novel genetic algorithm for electric distribution ...
Jian Zhang, Xiaodong Yuan, Yubo Yuan
doaj +1 more source
Physics‐Embedded Neural Network: A Novel Approach to Design Polymeric Materials
Traditional black‐box models for polymer mechanics rely solely on data and lack physical interpretability. This work presents a physics‐embedded neural network (PENN) that integrates constitutive equations into machine learning. The approach ensures reliable stress predictions, provides interpretable parameters, and enables performance‐driven, inverse ...
Siqi Zhan +8 more
wiley +1 more source
An Ever Closer Union? Examining The Evolution Of The Integration Of European Equity Markets Via Minimum Spanning Trees [PDF]
The concept of a minimum spanning tree (MST) is used to study the process of comovements for 21 European Union stock market indices. We show how the asset tree and its related hierarchical tree evolve over time and describe the dynamics.
Marian Boscia +2 more
core
The complexity of some families of cycle-related graphs
In this paper, we derive new formulas for the number of spanning trees of a specific family of graphs – gear graphs, flower graphs, sun graphs and sphere graphs – using techniques from linear algebra, Chebyshev polynomials and matrix theory.
S.N. Daoud, K. Mohamed
doaj +1 more source
This study presents a single‐cell atlas of pseudomyxoma peritonei spanning primary and paired metastatic lesions. Distinct epithelial substates, stromal remodeling, immune exclusion, lipid metabolic reprogramming, and a candidate angiogenic network were identified in metastatic lesions.
Xi Li +14 more
wiley +1 more source
ML Workflows for Screening Degradation‐Relevant Properties of Forever Chemicals
The environmental persistence of per‐ and polyfluoroalkyl substances (PFAS) necessitates efficient remediation strategies. This study presents physics‐informed machine learning workflows that accurately predict critical degradation properties, including bond dissociation energies and polarizability.
Pranoy Ray +3 more
wiley +1 more source
Sustainable Materials Design With Multi‐Modal Artificial Intelligence
Critical mineral scarcity, high embodied carbon, and persistent pollution from materials processing intensify the need for sustainable materials design. This review frames the problem as multi‐objective optimization under heterogeneous, high‐dimensional evidence and highlights multi‐modal AI as an enabling pathway.
Tianyi Xu +8 more
wiley +1 more source
An Approximation Scheme for the Generalized Geometric Minimum Spanning Tree Problem with Grid Clustering [PDF]
This paper is concerned with a special case of the Generalized Minimum Spanning Tree Problem. The Generalized Minimum Spanning Tree Problem is de¯ned on an undirected graph, where the vertex set is partitioned into clusters, and non-negative costs are ...
Grigoriev,Alexander, Feremans,Corinne
core
By overcoming the fixed‐path limitations of conventional machine learning, a heterogeneous graph neural network fundamentally reconstructs material data representation. Integrating variable processing sequences with intrinsic elemental features, this framework enables exploratory optimization across high‐dimensional spaces.
Jie Yin +12 more
wiley +1 more source
A Probabilistic Tabu Search Algorithm for the Generalized Minimum Spanning Tree Problem [PDF]
In this paper we present a probabilistic tabu search algorithm for the generalized minimum spanning tree problem. The basic idea behind the algorithm is to use preprocessing operations to arrive at a probability value for each vertex which roughly ...
Ghosh, Diptesh
core

