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On computing the range of a rational function of n variables over a bounded region
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What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
inferredcites →https://doi.org/10.1002/zamm.19770571215openalex-snapshot
Alefeld, G. / Herzberger, J. , Einführung in die Intervallrechnung, Zürich. B. I.‐Wissenschaftsverlag. 1974. 398 S., DM 22,‐. (Reihe Informatik 12).
inferredcites →https://doi.org/10.1007/bf01933121openalex-snapshot
Computation of rational interval functions
inferredcites →https://doi.org/10.1007/bf01939221openalex-snapshot
The accuracy of floating point computers
inferredcites →https://doi.org/10.1007/bf02234767openalex-snapshot
Newton-Algorithmen zur Bestimmung von Nullstellen mit Fehlerschranken
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Die Berechnung von Schranken für den Wertebereich eines Polynoms in einem Intervall
inferredcites →https://doi.org/10.1016/0024-3795(69)90024-xopenalex-snapshot
On the solution of linear algebraic equations with interval coefficients
inferredcites →https://doi.org/10.1137/0704001openalex-snapshot
Interval Arithmetic in Matrix Computations, Part II
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
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αBB algorithm; Automatic differentiation: Point and interval; Automatic differentiation: Point and interval Taylor operators; Bounding derivative ranges; Continuous global optimization: Applications; Continuous global optimization: Models, algorithms and software; Global optimization: Application…
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Non-linear Global Optimization Using Interval Arithmetic and Constraint Propagation
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Interval Global Optimization
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Hybridization of Interval CP and Evolutionary Algorithms for Optimizing Difficult Problems
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Global optimization using interval analysis: The one-dimensional case
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Computation complexity of the range of a polynomial in several variables
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A branch and bound algorithm for bound constrained optimization problems without derivatives
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Global optimization using interval analysis ? the multi-dimensional case
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On Underestimating in Interval Computations
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Centered forms for functions in several variables
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Modified interval mean-value forms
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Verified solution of large systems and global optimization problems
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LP-form inclusion functions for global optimization
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SOME RECENT ASPECTS OF INTERVAL ALGORITHMS FOR GLOBAL OPTIMIZATION
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Analysis of distance metrics in content-based image retrieval using statistical quantized histogram texture features in the DCT domain
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Inversion error, condition number, and approximate inverses of uncertain matrices
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État de l'art des méthodes “d'optimisation globale”
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Computer-generated interval extensions of factorable functions and their derivatives
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Application of Interval, Statistical, and Fuzzy Methods to the Evaluation of Measurements
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The use of interval mathematics in electromagnetic design
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The computational complexity of problems to compute intervals wrappers for random variables uniform, Exponential and Pareto
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A New Interval Contractor Based on Optimality Conditions for Bound Constrained Global Optimization
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Nonlinear Dynamic Systems Parameterization Using Interval-Based Global Optimization: Computing Lipschitz Constants and Beyond
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True worst-case analysis of linear electrical circuits by interval arithmetic
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Algorithms for worst-case tolerance optimization
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The Computational Complexity of Random Variables with Uniform, Exponential and Pareto Distributions in Real and Interval Forms
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Computer-Based Design Synthesis Research: An Overview
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Polynomial Curve Fitting for Data with Interval Uncertainty
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Safe Starting Regions for Iterative Methods
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A Posteriori Error Bounds for Two-Point Boundary Value Problems
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Bounding Sets in Function Spaces with Applications to Nonlinear Operator Equations
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Interval Tests and Contractors Based on Optimality Conditions for Bound-Constrained Global Optimization
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Definição intervalar e análise de qualidade da função densidade de probabilidade da variável aleatória contínua com distribuição Beta
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Global optimization: theory versus practice
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Hybridation d’algorithmes évolutionnaires et de méthodes d’intervalles pour l’optimisation de problèmes difficiles
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