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Numerical Computations: Theory and Algorithms: 4th International Conference, NUMTA 2023, Pizzo Calabro, Italy, June 1420, 2023, Revised Selected Papers, Part I [Mīkstie vāki]

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  • Formāts: Paperback / softback, 412 pages, height x width: 235x155 mm, 75 Illustrations, color; 16 Illustrations, black and white; XXIV, 412 p. 91 illus., 75 illus. in color., 1 Paperback / softback
  • Sērija : Lecture Notes in Computer Science 14476
  • Izdošanas datums: 01-Jan-2025
  • Izdevniecība: Springer International Publishing AG
  • ISBN-10: 3031812409
  • ISBN-13: 9783031812408
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Numerical Computations: Theory and Algorithms: 4th International Conference, NUMTA 2023, Pizzo Calabro, Italy, June 1420, 2023, Revised Selected Papers, Part IPalielināt
  • Formāts: Paperback / softback, 412 pages, height x width: 235x155 mm, 75 Illustrations, color; 16 Illustrations, black and white; XXIV, 412 p. 91 illus., 75 illus. in color., 1 Paperback / softback
  • Sērija : Lecture Notes in Computer Science 14476
  • Izdošanas datums: 01-Jan-2025
  • Izdevniecība: Springer International Publishing AG
  • ISBN-10: 3031812409
  • ISBN-13: 9783031812408
Citas grāmatas par šo tēmu:
Permanent link: https://www.kriso.lv/db/9783031812408.html
Keywords:
The three-volume set LNCS 14476-14478 constitutes the post conference proceedings of the 4th International Conference on Numerical Computations: Theory and Algorithms, NUMTA 2023, held in Pizzo Calabro, Italy, during June 1420, 2023.

The 45 full papers presented in this book together with 60 short papers were carefully reviewed and selected from 170 submissions.

The papers focus on topics such as: continuous and discrete single- and multi-objective problems, local, global and large-scale optimization, classification in machine learning, optimal control, and applications; computational and applied mathematics (such as approximation theory, computational geometry, computational fluid dynamics, dynamical systems and differential equations, numerical algebra, etc.) and applications in engineering and science; numerical models, methods and software using traditional and emerging high-performance computational tools and paradigms (including the infinity and quantum computing) and their application in artificial intelligence and data science, bioinformatics, economics and management, engineering and technology, mathematical education, number theory and foundations of mathematics, etc.
Application of Machine Learning to Increase the Efficiency of the Global
Search Algorithm for Solving Multicriterial Problems.- Sequential Decision
Modeling for Dynamic Pricing and Revenue Management in Hotels.- Resource
Allocation via Bayesian Optimization: An Efficient Alternative to Semi-Bandit
Feedback.- Multi-Objective and Multiple Information Source Optimization for
Fair & Green Machine Learning.- Extended Optimal Control Problem for
Practical Application.- Explainable Process Deviance Discovery with
Data-Efficient Deep Learning.- Line Search Stochastic Gradient Algorithm with
a-Priori Rule for Monitoring the Control of the Variance.- A Machine Learning
Approach to Speed up the Solution of the Distributors Pallet Loading
Problem.- Combined First- and Second-Order Directions for Deep Neural
Networks Training.- Constrained Global Optimization by Smoothing.- The
Unreasonable Effectiveness of Optimal Transport Distance in the Design of
Multi-Objective Evolutionary Optimization Algorithms.- An Improved Modified
Jaya Optimization Algorithm: Application to the Solution of Nonlinear
Equation Systems.- GPU Acceleration of the Enhanced Jaya Optimization
Algorithm for Solving Large Systems of Nonlinear Equations.- Effective
Resistance Based Community Detection in Complex Networks.- A Comparison of
Formulations for Aircraft Deconfliction.- Optimal Recombination Problem in
Genetic Programming for Boolean Functions.- Heuristics with Local
Improvements for Two-Processor Scheduling Problem with Energy Constraint and
Parallelization.- Numerical Analysis of Optimal Control of Assets and
Liabilities by a Bank.- Optimal Control for Stochastic Multi-Agent Systems
with the Use of Parallel Hybrid Genetic Algorithm.- DC Optimization in
Adversarial Support Vector Machine.- A First-Order Optimality Condition in
Nonsmooth Generalized Semi-Infinite Programming (GSIP).- Miniaturisation of
Binary Classifiers through Sparse Neural Networks.- Price Forecasting for
Bitcoin: Linear Regression and SVM Approaches.- Inside the Box: 0-1 Linear
Programming under Interval Uncertainty.- Machine Learning Techniques for
Branch-and-Cut Methods: The Selection of Cutting Planes.- The Critical Cone
and Second-Order Optimality Conditions for a State-Constrained Optimal
Control Problem.- Local Information in Global Optimization with
Dimensionality Reduction Schemes.- A Heuristic Solution Approach for Bulk
Port Routing Optimization.- A Genetic Algorithm to Optimize the Dispatch of
Firefighting Resources.- Robust Non-Convex Model-Based Approach for Deep
Learning-Based Image Processing.- A DCA-Like Based Algorithm for the Merkle
Tree Construction Problem in Ethereum Cryptocurrency System.- Numerical
Optimization in Hyperbolic Space - Applications to Drug-Target Interaction
Prediction.- Improving Feasibility of Optimal Control via Obtaining
High-precision Model.- Dimensionality Reduction for Quadratic Convex
Maximization.- Population Local Search for Single Processor Energy Efficient
Scheduling Problem.