Results 71 to 80 of about 67,931 (252)
We develop a full randomization of the classical hyper‐logistic growth model by obtaining closed‐form expressions for relevant quantities of interest, such as the first probability density function of its solution, the time until a given fixed population is reached, and the population at the inflection point.
Juan Carlos Cortés +2 more
wiley +1 more source
ABSTRACT Modern engineering systems require advanced uncertainty‐aware model updating methods that address parameter correlations beyond conventional interval analysis. This paper proposes a novel framework integrating Riemannian manifold theory with Gaussian Process Regression (GPR) for systems governed by Symmetric Positive‐Definite (SPD) matrix ...
Yanhe Tao +3 more
wiley +1 more source
A Novel Two‐Stage Flexible Flow Shop Batch Scheduling Model for Grinding Workshops
ABSTRACT The growing need for data storage in data centers has increased the demand for mechanical hard disks due to their low cost and high reliability. Aluminum substrates are the most popular base plates for mechanical hard disks because of their high hardness and low cost.
Jun Xu +4 more
wiley +1 more source
SEMI-MARKOV DECISION PROCESSES AND THEIR APPLICATIONS IN REPLACEMENT MODELS
We consider the problem of minimizing the long-run average expected cost per unit time in a semi-Markov decision process with arbitrary state and action space. Using the idea of successive approximations, sufficient conditions for the existence of an optimal stationary policy are given.
openaire +3 more sources
Semi-Markov decision processes with limiting ratio average rewards
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Sagnik Sinha, Prasenjit Mondal
openaire +1 more source
GraphReco: Probabilistic Structure Recognition for Chemical Molecules
Molecule structure images are unfriendly for machine understanding, blocking productivity improvements in chemical data mining, drug discovery, and many other fields. We present a rule‐based probabilistic Optical Chemical Structure Recognition model to explain and tackle the ambiguity challenges in graph assembly.
Haidong Wang +2 more
wiley +1 more source
Mechanistic Learning for Predicting Survival Outcomes in Head and Neck Squamous Cell Carcinoma
ABSTRACT We employed a mechanistic learning approach, integrating on‐treatment tumor kinetics (TK) modeling with various machine learning (ML) models to address the challenge of predicting post‐progression survival (PPS)—the duration from the time of documented disease progression to death—and overall survival (OS) in Head and Neck Squamous Cell ...
Kevin Atsou +4 more
wiley +1 more source
ABSTRACT Personal autonomous vehicles can sense their surrounding environment, plan their route, and drive with little or no involvement of human drivers. Despite the latest technological advancements and the hopeful announcements made by leading entrepreneurs, to date no personal vehicle is approved for road circulation in a “fully” or “semi ...
Xingshuai Dong +13 more
wiley +1 more source
Abstract Our generation inherits this cultural heritage of historic material and historic reinforced concrete structures and thus bears a certain responsibility to preserve these historic buildings with the help of the new technologies of lifetime management, conservation concepts and the new digitalization as well as the emerging safety concepts of ...
A. Strauss
wiley +1 more source
Unsupervised Work Behavior Pattern Extraction Based on Hierarchical Probabilistic Model
In this study, we address the challenge of analyzing worker behaviors in high‐mix, low‐volume production environments, where traditional supervised learning methods struggle owing to the lack of labeled data and task variability among workers. To overcome these issues, we propose a novel hierarchical approach for unsupervised behavior pattern ...
Issei Saito +5 more
wiley +1 more source

