Mazhar Javed Awan^1,2,*, Mohd Shafry Mohd Rahim², Haitham Nobanee^3,4,5, Awais Yasin⁶, Osamah Ibrahim Khalaf⁷, Umer Ishfaq²

Intelligent Automation & Soft Computing, Vol.27, No.3, pp. 785-797, 2021, DOI:10.32604/iasc.2021.014216

Abstract Retail companies recognize the need to analyze and predict their sales and customer behavior against their products and product categories. Our study aims to help retail companies create personalized deals and promotions for their customers, even during the COVID-19 pandemic, through a big data framework that allows them to handle massive sales volumes with more efficient models. In this paper, we used Black Friday sales data taken from a dataset on the Kaggle website, which contains nearly 550,000 observations analyzed with 10 features: qualitative and quantitative. The class label is purchases and sales (in U.S. dollars). Because the predictor label… More >

G. Formica¹, F. Milicchio²

CMES-Computer Modeling in Engineering & Sciences, Vol.60, No.3, pp. 199-220, 2010, DOI:10.3970/cmes.2010.060.199

Abstract This manuscript introduces a novel sufficient condition for the unconditionally stable convergence of the general class of trapezoidal integrators. Contrary to standard energy-based approaches, this convergence criterion is derived from the power principles, in terms of both balance and dissipation. This result improves the well-known condition of stable convergence based on the energy method, extending its applicative spectrum to a variety of physical problems, whose constitutive prescriptions may be more appropriately characterized by means of evolving field equations. Our treatment, tailored for generalized trapezoidal integrators, addresses both linear and nonlinear problems, extending its applicability to contexts where standard energy-based schemes… More >