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Three-dimensional time history analysis has become a demand for the majority of updated building codes. A vast literature has addressed the selecting and scaling of horizontal component of earthquake ground motion. Meanwhile, the scaling of vertical component has been less of a concern. This paper investigates the suggestion of using the same scaling factor of horizontal component of ground motion to scale its vertical counterpart. A data set consists of 6409 mainshock records with vertical and orientation independent geometric rotated (GMRotD 50) response spectra with 5 % damping is used. Even though ASCE 7 - 16 among other international codes recommends to use the same scaling factor for horizontal component and its vertical counterpart, this paper shows that scaling factor of vertical component trends an extreme variation from its horizontal counterpart for various soil classes, different magnitudes and over a wide range of Joyner-Boore distances. Results illustrate that the ratio of vertical to horizontal scaling factors has a strong negative relationship with the ratio of vertical to horizontal peak ground acceleration. Earthquake magnitude has no significant role on the ratio of vertical to horizontal scaling factors. A gradual increase is observed in the studied ratio over a wide range of Joyner-Boore distances. The paper ends up with simplified equations to calculate the scaling factor of vertical component in regards with the scaling factor of its GMRotD50 horizontal counterpart based on the (V / H) PGA ratio of the recorded components. Robust statistics manifest the goodness of the developed equations. [ABSTRACT FROM AUTHOR]

Differential Evolution (DE) is a state-of-the art evolutionary algorithm that solves global optimization problems in a real domain. The algorithm adapts the mutation range and direction by basing these on the differences between individuals in the current population. In this paper, we provide formulas for the expectation vectors and covariance matrices of the mutants' distribution for several operators of differential mutation. The covariance matrices are proportional to each other, which means that the main difference between the analyzed DE operators is the mutation range. This can be conveniently described using a generalized scaling factor g ( F ) , introduced in this paper. Next, we propose transformations of the scaling factors that make the expectation vectors and covariance matrices of the expected mutants' distributions equal to the respective statistics of DE/best/1 or DE/rand/1. These transformations establish a framework for a synthetic investigation of various differential mutation operators and for generalizing the results of parameter tuning. A simulation study based on the CEC ′ 13 benchmark in 10, 30 and 50 dimensions confirms that the transformations do not influence the performance much, especially in the case of DE operators with two difference vectors. [ABSTRACT FROM AUTHOR]

We confirmed how well the exchange–correlation functional vdW-DF2, with its non-local correlation part, describes the adsorption of CO on close-packed surfaces and clusters of Co, Ni, Cu, Ru, Rh, Pd, and Pt. The calculated adsorption energies are fairly close to the experimental values. The carbonyl vibrational frequencies, calculated within the harmonic approximation, systematically underestimate the experimental results. To amend this deficiency, we explored multiplicative and additive correction schemes. Scaling the calculated harmonic CO frequencies by a uniform factor of 1.030 yields results with a mean absolute deviation of ∼13 cm −1 from experiment. With this correction scheme we were able to clarify some controversial structures for CO adsorption on the surfaces Pd(1 1 1) and Co(0 0 0 1). [ABSTRACT FROM AUTHOR]

• In the Success-History based adaptive DE (SHADE) algorithmic framework, we propose a very basic, yet successful, nearest spatial neighborhood-based adjustment to the adaptation process of the parameters. • Our proposed modifications can be extended to any SHADE-based DE algorithm like L-SHADE (SHADE with linear population size reduction), jSO (L-SHADE with modified mutation) etc. • The effectiveness of the proposed spatial neighborhood based parameter adaptation scheme is showcased on the IEEE Congress on Evolutionary Computation (CEC) 2013, 2014, 2015, and 2017 benchmark suites. • Furthermore, the IEEE CEC 2011 competition on testing evolutionary algorithms on real-world numerical optimization problem benchmark suite is considered. Differential Evolution (DE) has been widely appraised as a simple yet robust population-based, non-convex optimization algorithm primarily designed for continuous optimization. Two important control parameters of DE are the scale factor F , which controls the amplitude of a perturbation step on the current solutions and the crossover rate C r , which limits the mixing of components of the parent and the mutant individuals during recombination. We propose a very simple, yet effective, nearest spatial neighborhood-based modification to the adaptation process of the aforesaid parameters in the Success-History based adaptive DE (SHADE) algorithm. SHADE uses a historical archive of the successful F and C r values to update these parameters and stands out as a very competitive DE variant of current interest. Our proposed modifications can be extended to any SHADE-based DE algorithm like L-SHADE (SHADE with linear population size reduction), jSO (L-SHADE with modified mutation) etc. The enhanced performance of the modified SHADE algorithm is showcased on the IEEE CEC (Congress on Evolutionary Computation) 2013, 2014, 2015, and 2017 benchmark suites by comparing against the DE-based winners of the corresponding competitions. Furthermore, the effectiveness of the proposed neighborhood-based parameter adaptation strategy is demonstrated by using the real-life problems from the IEEE CEC 2011 competition on testing evolutionary algorithms on real-world numerical optimization problems. [ABSTRACT FROM AUTHOR]

In this paper a numerical method for solving generalized three-dimensional magnetohydrodynamic (MHD) flow of an incompressible viscous fluid over a porous stretching sheet is proposed. This approach is based on Legendre pseudo-spectral method with a positive scaling factor and extrapolation. The present method solves the problem on the semi-infinite domain without truncating it to a finite domain. In addition, this method reduces the solution of the problem to solution of a system of algebraic equations. The obtained numerical results are compared with some well-known results to confirm the accuracy and efficiency of the proposed scheme. [ABSTRACT FROM AUTHOR]

• We propose a new measure of model risk in Basel credit capital requirement. • We observe that parameter dependency between LGD and PD raises substantially the tail risk in capital requirements. • The results are striking with a required increase in regulatory capital in the range 38%-66%. • A clear policy implication: we suggest to reintroduce the scaling factor in credit capital requirements. Credit capital requirements in Internal Rating Based approaches require the calibration of two key parameters: the probability of default and the loss-given-default. This letter considers the uncertainty about these two parameters and models this uncertainty in an elementary way: it shows how this estimation risk can be computed and properly taken into account in regulatory capital. We analyse two standard real datasets: one composed by all corporates rated by Moody's and one limited only to the speculative grade ones. We statistically test model hypotheses on the two key parameters and we observe that parameter dependency raises substantially the tail risk in capital requirements. The results are striking with a required increase in regulatory capital in the range 38 % − 66 %. This study draws also a clear policy implication: we suggest to reintroduce the scaling factor in credit capital requirements – factor that has been removed in Basel III Accord – to take into account model risk. [ABSTRACT FROM AUTHOR]

This paper proposes a simple, yet effective, modification to scaling factor and crossover rate adaptation in Success-History based Adaptive Differential Evolution (SHADE), which can be used as a framework to all SHADE-based algorithms. The performance impact of the proposed method is shown on the real-parameter single objective optimization (CEC2015 and CEC2017) benchmark sets in 10, 30, 50, and 100 dimensions for all SHADE, L-SHADE (SHADE with linear decrease of population size), and jSO algorithms. The proposed distance based parameter adaptation is designed to address the premature convergence of SHADE–based algorithms in higher dimensional search spaces to maintain a longer exploration phase. This design effectiveness is supported by presenting a population clustering analysis, along with a population diversity measure. Also, the new distance based algorithm versions (Db_SHADE, DbL_SHADE, and DISH) have obtained significantly better optimization results than their canonical counterparts (SHADE, L_SHADE, and jSO) in 30, 50, and 100 dimensional functions. [ABSTRACT FROM AUTHOR]