Control, Optimization, and Mathematical Modeling of Complex Systems

• Muut tekijät: Posypkin, Mikhail (Toimittaja), Gorshenin, Andrey (Toimittaja), Titarev, Vladimir (Toimittaja)
• Aineistotyyppi: Elektroninen Kirjan osa
• Kieli: englanti
• Julkaistu: Basel MDPI - Multidisciplinary Digital Publishing Institute 2023
• Aiheet: Information technology industries; Computer science; optimal control problem; evolutionary computation; robotics applications; optimal control; Lyapunov stability; equilibrium point; symbolic regression; Pontryagin's maximum principle; continuous-time Markov chains; ergodicity bounds; discrete state space; rate of convergence; logarithmic norm; interval analysis; function approximation; global optimization; convexity evaluation; overestimators; underestimators; machine learning control; general synthesis problem; evolutionary algorithm; adaptive interpolation algorithm; interval ordinary differential equations (ODEs); sparse grids; hierarchical basis; multidimensional interpolation; high dimensions; molecular dynamics modeling; randomized maximum entropy estimation; probability density functions; Lagrange multipliers; Lyapunov-type problems; implicit function; rotation of vector field; asymptotic efficiency; thermokarst lakes; forecasting; dynamical tracking target; ship towing system; relative curvature; adaptive control; discrete velocity method; lattice Boltzmann method; computational fluid dynamics; mathematical modeling; estimation; minimax techniques; pareto optimization; regression analysis; statistical uncertainty; proton exchange membrane; proton electrolyte membrane; PEM; fuel cell; PEMFC; power electronic converter; DC-DC boost converter; model predictive control; MPC; self-scalable robots; modular robots; origami structures; complex system; synergistic effect; performance indicator; structure change; soft robotics; continuum mechanisms; modeling of complex systems; kinematic model of soft robots; mathematical modeling of complex systems; non-linear models; soft robotic neck; tendon-driven actuators; mathematical modelling; modelling in economics; impact of the COVID-19; logistics businesses; fractional-order virus models; stuxnet virus; numerical computing; supervisory control and data acquisition systems; computer networks; lyapunov analysis; image segmentation; remote sensing; terrain identification; data synthesis; transfer learning; controllability; observability; stochastic linear systems in finite and infinite dimensional spaces; stochastic singular linear systems in finite and infinite dimensional spaces; semigroup; evolution operator; GE-semigroup; GE-evolution operator; stochastic GE-evolution operator; feature selection; finite normal mixtures; moving separation of mixtures; deep LSTM; neural network architectures; deep learning; turbulent plasma; air-sea fluxes; n/a
• Linkit: DOAB: download the publication; DOAB: description of the publication

Complex systems have long been an integral part of modern life and can be encountered everywhere. Undertaking a comprehensive study of such systems is a challenging problem, one which is impossible to solve without the use of contemporary mathematical modeling techniques. Mathematical models form th...