Design of Experiments and machine learning for product innovation: A systematic literature review
The recent increase in digitalization of industrial systems has resulted in a boost in data
availability in the industrial environment. This has favored the adoption of machine learning …
availability in the industrial environment. This has favored the adoption of machine learning …
Likelihood analysis and stochastic EM algorithm for left truncated right censored data and associated model selection from the Lehmann family of life distributions
The Lehmann family of distributions includes Weibull, Gompertz, and Lomax models as
special cases, all of which are quite useful for modeling lifetime data. Analyses of left …
special cases, all of which are quite useful for modeling lifetime data. Analyses of left …
Self‐supervised cross validation using data generation structure
Modern statistics and machine learning typically involve large amounts of data coupled with
computationally intensive methods. In a predictive modeling context, one seeks models that …
computationally intensive methods. In a predictive modeling context, one seeks models that …
Data augmentation using improved conditional GAN under extremely limited fault samples and its application in fault diagnosis of electric submersible pump
Electric submersible pump (ESP) in offshore oilfields is one of the important artificial lifting
methods to achieve high and stable production. The complexity of the ESP system and the …
methods to achieve high and stable production. The complexity of the ESP system and the …
Developing a prediction model for low-temperature fracture energy of asphalt mixtures using machine learning approach
D Mirzaiyanrajeh, EV Dave, JE Sias… - International Journal of …, 2023 - Taylor & Francis
This paper presents an augmented full quadratic model (AFQM), artificial neural network
(ANN) and an innovative machine learning technique called self-validated ensemble …
(ANN) and an innovative machine learning technique called self-validated ensemble …
[图书][B] Survival Analysis
J O'Quigley - 2021 - Springer
In common with most scientific texts this one is the result of several iterations. The seed for
the iterations was the 2008 text Proportional Hazards Regression and the first step was in …
the iterations was the 2008 text Proportional Hazards Regression and the first step was in …
A reliability demonstration test plan derivation method based on subsystem test data
P Jiang, Q Zhao, H Xiao, B Wang, Y Xing - Computers & Industrial …, 2022 - Elsevier
A reliability demonstration test (RDT) has been used to determine whether a product meets
pre-specified reliability requirements and to decide whether a batch of products should be …
pre-specified reliability requirements and to decide whether a batch of products should be …
Product reliability analysis based on heavily censored interval data with batch effects
In many industries including engineering, biology, and medical science, etc, interval failure
data commonly exist. Utilizing the data to estimate product lifetime is often confounded with …
data commonly exist. Utilizing the data to estimate product lifetime is often confounded with …
A workflow for lipid nanoparticle (LNP) formulation optimization using designed mixture-process experiments and self-validated ensemble models (SVEM)
We present a Quality by Design (QbD) styled approach for optimizing lipid nanoparticle
(LNP) formulations, aiming to offer scientists an accessible workflow. The inherent restriction …
(LNP) formulations, aiming to offer scientists an accessible workflow. The inherent restriction …
Self-validated ensemble models for design of experiments
One of the possible objectives when designing experiments is to build or formulate a model
for predicting future observations. When the primary objective is prediction, some typical …
for predicting future observations. When the primary objective is prediction, some typical …