The urban wastewater system components (sewer, treatment plant, and river) are often modelled using complex mechanistic models. Mechanistic surrogate models are introduced here as simplified models that still contain some physical knowledge. Surrogate models are faster, but are less but still sufficiently accurate, and require more data to be calibrated. The possibilities of replacing actual fi...

UNLABELLED In evaluating conservation and management options for species, practitioners might consider surrogate habitats at multiple scales when estimating available habitat or modeling species' potential distributions based on suitable habitats, especially when native environments are rare. Species' dependence on surrogates likely increases as optimal habitat is degraded and lost due to anthr...

Many industrial processes are in cascade configuration in which the material being processed goes through a sequence of processing units. In many cases, direct in-process measurements of the relevant variable are not available at all but at the last processing unit. Surrogate or model based soft measurements in which the relevant inprocess variables are inferred from other measurements would be...

Surrogate-assisted, or meta-model based evolutionary computation uses efficient computational models, often known as surrogates or meta-models, for approximating the fitness function in evolutionary algorithms. Research on surrogate-assisted evolutionary computation began over a decade ago and has received considerably increasing interest in recent years. Very interestingly, surrogate-assisted ...

Computation of document image quality metrics often depends upon the availability of a ground truth image corresponding to the document. This limits the applicability of quality metrics in applications such as hyperparameter optimization of image processing algorithms that operate on-the-fly on unseen documents. This work proposes the use of surrogate models to learn the behavior of a given doc...

Computer models and simulations are essential system design tools that allow for improved decision making and cost reductions during all phases of the design process. However, the most accurate models tend to be computationally expensive and can therefore only be used sporadically. Consequently, designers are often forced to choose between exploring many design alternatives with less accurate, ...

Surrogate-assisted search-based testing (SA-SBT) aims to reduce the computational time for compute-intensive systems. Surrogates enhance techniques by improving test case generation focusing budget on most critical portions of input domain. In addition, they can serve as approximations system under (SUT) predict results instead executing tests SUTs. This article reflects existing SA-SBT techniq...

A ridge version of an ill–conditioned system is long held to “act more like an orthogonal system” than the system itself. Surrogate models exist also having smaller expected mean square than OLS, and surrogate solutions are seen to have uniformly smaller residual sums of squares than ridge. Ridge and surrogate solutions are compared on several hallmarks of orthogonality, to include conditioning...

This paper proposes a novel surrogate-model-based multiobjective evolutionary algorithm called Differential Evolution for Multiobjective Optimization Based on Gaussian Process Models (GP-DEMO). The algorithm is based on the newly defined relations for comparing solutions under uncertainty. These relations minimize the possibility of wrongly performed comparisons of solutions due to inaccurate s...