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Numerical simulation models are used in all engineering disciplines for modeling physical phenomena to learn how the phenomena work, and to identify problems and optimize behavior. …
The use of metaheuristic algorithms (MA) has been increasing in recent years, and the image processing field is not the exempted of their application. In the last two years a big …
Project Managers leading massive IT projects--defined as projects rolling out deliverables across geographic boundaries with budgets ranging well into the millions--need a unique …
Drawing on the authors' more than six years of R&D in location-based information systems (LBIS) as well as their participation in defining the Java ME Location API 2.0, …
Governments around the world use machine learning in automated decision-making systems for a broad range of functions. However, algorithmic bias in machine learning can result in …
For companies to be successful, the management of an organization needs to understand how competence evolves and how it can be utilized and linked to the organization's goals. When …
By deploying time series analysis, Fourier transform, functional analysis, min-plus convolution, and fractional order systems and noise, this book proposes fractal traffic modeling …
The sequential quadratic hamiltonian (SQH) method is a novel numerical optimization procedure for solving optimal control problems governed by differential models. It is based on …
This book discusses various artificial intelligence and machine learning applications concerning smart buildings. It includes how renewable energy sources are integrated into smart …
In placing these questions at the heart of their book, the authors set out to stimulate and contribute to the great debate: despite the enormous growth in the acquistion of GIS …