Developing predictive models for analysis the heat transfer in sinusoidal wavy channelsIn this work, empirical correlations were proposed to accurately estimate the heat transfer and pressure drop for water flow in sinusoidal wavy channels. The artificial intelligence techniques such as artificial neural ...
Bootstrap Methods for Developing Predictive Models in Cardiovascular Research Researchers frequently use automated model selection methods such as backwards elimination to identify variables that are independent predictors of an outcome under consideration. We propose using bootstrap resampling in conjunction ...
During this presentation, we demonstrate how you can use MATLAB to develop nonlinear predictive models from historical time-series measurements. As a working case study, a forecast model of short-term electricity loads for the Australian market using BOM and AEMO data is presented. This case ...
Here, we present a method to construct such models for these types of systems. To maximize predictive capability, we introduce a set of “don’t care” (dc) Boolean variables that must be assigned values in order to obtain a concrete model. When a dc variable is se...
The FN test is the recommended procedure for evaluating rutting resistance of AC mixtures under the AASHTO mechanistic empirical pavement design guide (MEPDG)... Apeagyei,K Alex - 《Construction & Building Materials》 被引量: 3发表: 2014年 A Study of Reliability of Predictive Models for Permanent...
Methods, systems, and computer program products for developing and using predictive models for predicting medical outcomes and for evaluating intervention strategies, and for simultaneously validating biomarker causality are disclosed. According to one method, clinical data from different sources for a ...
Unreal Engine Marketplace is Unreal Engine's Store that has a library Of Textures, Models, Animations, Tutorials, and More for creating amazing 3D projects and games. UnrealBuildTool (UBT) is a tool that manages the process of building UE4 source code across a variety of build configurations....
predictive models for DTs can find correlations between cause and effect much more efficiently and use the latest information about the state of the process to update their predictive capabilities. Such expansive and live process intelligence is particularly indispensable for a process such as AM, ...
Digital servitization business models consist of three main components: products, services, and information (Cenamor et al., 2017). For digital servitization, the information component becomes central and is, in some cases, replacing product and service components (Cenamor et al., 2017). ...
For these reasons, we applied it in developing machine-learning models with high predictive performance. 2.2.2. Linear Regression LR models are supervised learning models because they use a linear equation based on specific input values and a machine-learning-based output value [35,36]. LR ...