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Titlebook: Sustainable Energy for Smart Cities; Third EAI Internatio Joao L. Afonso,Vitor Monteiro,José Gabriel Pinto Conference proceedings 2022 ICST

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perturbations ∆. and ∆. respectively. The problem then becomes . and we are mainly concerned with studying the deviation ∆. of the solution with the perturbation. Such an exercise is called ., for the extent of the deviation ∆. relative to ∆. and ∆. defines the . of the system. A highly sensitive s
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Catia F. Oliveira,Joao L. Afonso,Vitor Monteiroique, . is necessarily nonsingular and . is expressed as .. (. = .). The situation in which there is more than one solution occurs when . can be expressed linearly in some few column vectors of . having rank equal to .(.) < .. The equations are said to be consistent yet indeterminate. The solution c
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João Rego,Fábio Lúcio Pereira,Luis A. M. Barros,António P. Martins,J. G. Pintoision makers often provide only partial and/or doubtful information. We unify and expand results to deal with those cases introducing a general framework for sensitivity analysis in multi-objective decision making. We study first decision making problems under partial information. We provide axioms
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Lucélio M. da Costa,Paulo G. Pereirinhaplications to humans, other animals, and plants. The analyses are based on matrix formulations of age-classified, stage-classified, and multistate population models. Methods are presented for linear and nonlinear, deterministic and stochastic, and time-invariant and time-varying cases.  Readers will
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Paula Ferreira,Ana Rocha,Madalena Araújoplications to humans, other animals, and plants. The analyses are based on matrix formulations of age-classified, stage-classified, and multistate population models. Methods are presented for linear and nonlinear, deterministic and stochastic, and time-invariant and time-varying cases.  Readers will
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Benjamin Völker,Philipp M. Scholl,Bernd Beckerplications to humans, other animals, and plants. The analyses are based on matrix formulations of age-classified, stage-classified, and multistate population models. Methods are presented for linear and nonlinear, deterministic and stochastic, and time-invariant and time-varying cases.  Readers will
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