Results 41 to 50 of about 635,008 (168)
Stochastic Multiplicative Processes for Financial Markets
, 2001 We study a stochastic multiplicative system composed of finite asynchronous elements to describe the wealth evolution in financial markets. We find that the wealth fluctuations or returns of this system can be described by a walk with correlated step ...
Atkinson +35 more
core +1 more source
Bridging Nature and Technology: A Perspective on Role of Machine Learning in Bioinspired Ceramics
Advanced Engineering Materials, EarlyView.Machine learning (ML) is revolutionizing the development of bioinspired ceramics. This article investigates how ML can be used to design new ceramic materials with exceptional performance, inspired by the structures found in nature. The research highlights how ML can predict material properties, optimize designs, and create advanced models to unlock a ...
Hamidreza Yazdani Sarvestani +2 more
wiley +1 more source
On Measurable Stochastic Processes [PDF]
Transactions of the American Mathematical Society, 1940 In recent years probability theory has been formulated mathematically as measure theory; in the case of stochastic processes depending upon a continuous parameter the measures considered are defined on certain subspaces of the space of all functions of a real variable.t This formulation of stochastic processes depending upon a continuous parameter ...
openaire +2 more sources
Advanced Engineering Materials, EarlyView.Developing process parameters for the laser‐based Powder Bed Fusion of metals can be a tedious task. Based on melt pool depth, the process parameters are transferable to different laser scan speeds. For this, understanding the melt pool scaling behavior is essential, particularly for materials with high thermal diffusivity, as a change in scaling ...
Markus Döring +2 more
wiley +1 more source
Point processes and stochastic displacement fields
, 2004 The effect of a stochastic displacement field on a statistically independent point process is analyzed. Stochastic displacement fields can be divided into two large classes: spatially correlated and uncorrelated.
Gabrielli, Andrea
core +1 more source
On harmonizable stochastic processes
Information and Control, 1970 This paper presents a new orthogonal series representation and a new orthogonal integral representation for harmonizable stochastic processes.
Bede Liu, Stamatis Cambanis
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Influence of Form and Structural Features of Open‐Cell Hybrid Foam on the Remanent Magnetic Scanning
Advanced Engineering Materials, EarlyView.Simulations using an equivalent model are performed to improve the understanding of remanent magnetic scanning of hybrid foam samples for coating thickness estimation. The model allows to study the influence of isolated geometrical features such as layer thickness, boundary effects, as well as effects due to the statistical nature of the foams, which ...
Bashar Ibrahim +4 more
wiley +1 more source
On convergence of stochastic processes [PDF]
Transactions of the American Mathematical Society, 1962 It is clear that for given I,un } and t, the better theorem of this kind would be the one in which (2) is proved for the larger class of functions f. In this paper we shall show that certain known "invariance principles" can under some hypotheses be improved by considerably enlarging the class of functions for which (2) holds.
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Advanced Engineering Materials, EarlyView.This study explores geometry‐driven phase evolution in gyroid shell metamaterials made via laser powder bed fusion of 17‐4 precipitation hardened stainless steel. Locally hardened regions develop along the primary loading paths in the structure, which finite element analysis and geometric considerations link to enhanced gyroid strength.
Julia T. Pürstl +8 more
wiley +1 more source
Beyond Order: Perspectives on Leveraging Machine Learning for Disordered Materials
Advanced Engineering Materials, EarlyView.This article explores how machine learning (ML) revolutionizes the study and design of disordered materials by uncovering hidden patterns, predicting properties, and optimizing multiscale structures. It highlights key advancements, including generative models, graph neural networks, and hybrid ML‐physics methods, addressing challenges like data ...
Hamidreza Yazdani Sarvestani +4 more
wiley +1 more source