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LU-Optimality Conditions in Optimization Problems With Mechanical Work Objective Functionals
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DOI：10.1109/TNNLS.2021.3066196.png)
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摘要
En 中文
In this article, we introduce interval-valued Kuhn-Tucker (KT)-pseudoinvex optimization problems governed by interval-valued path-independent curvilinear integral objective functionals. Concretely, it is proven that an interval-valued KT-pseudoinvex variational control problem is described such that every KT point is an LU-optimal solution. In addition, the main results are highlighted by two illustrative applications describing the controlled behavior of an artificial neural system.
Keyword:
Optimization
Learning systems
Programming
Neural networks
Mathematical model
Physics
Biological system modeling
Kuhn-Tucker (KT)-pseudoinvexity
interval-valued variational control problem
KT point
LU-optimality conditions
neural networks
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