Bravura 发表于 2025-3-26 23:12:28
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Stochastic Processes, Optimization, and Control Theory: Applications in Financial Engineering, Queue978-0-387-33815-6Series ISSN 0884-8289 Series E-ISSN 2214-7934摸索 发表于 2025-3-27 09:34:56
Linear Stochastic Equations in a Hilbert Space with a Fractional Brownian Motion,A solution is obtained for a linear stochastic equation in a Hilbert space with a fractional Brownian motion. The Hurst parameter for the fractional Brownian motion is not restricted. Sample path properties of the solution are obtained that depend on the Hurst parameter. An example of a stochastic partial differential equation is given.ILEUM 发表于 2025-3-27 17:28:13
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https://doi.org/10.1007/0-387-33815-2Manufacturing; Manufacturing System; Optimization Methods; Stochastic Optimization; Stochastic ProcessesAGONY 发表于 2025-3-28 04:30:15
Characterization of Just in Time Sequencing via Apportionment, renders supply chains more stable and carrying less inventories of final products and components but at the same time it ensures less shortages. A number of algorithms have been proposed in the literature to optimize just in time sequencing. This paper characterizes these algorithms via characteristics developed by the apportionment theory.安抚 发表于 2025-3-28 10:20:16
ed on a brain -inspired spiking neural network (SNN) architecture. A STAM-SNN is a machine learning model that is trained on a full set of spatio-temporal variables, but can be successfully recalled on only a subset of the variables measured in different time intervals. In addition, a STAM-SNN modelEthics 发表于 2025-3-28 13:51:59
K. E. Avrachenkov,L. D. Finlay,V. G. Gaitsgoryl practices, planning, execution and patient care. This chapter delves into the core aspects of SDS, encompassing phase recognition, image segmentation, Surgical Process Modeling (SPM), and surgical skill assessment, presenting a systematic exploration of the key components: datasets, data acquisiti