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Evaluation of Goaf Stability Based on Transfer Learning Theory of Artificial Intelligence [PDF]
IEEE Access, 2019 Current artificial intelligence models for evaluating goaf stability in underground metal mines need a large amount of sample data for training, and their accuracy declines with small sample size. With the aim of solving this problem, this paper proposes
Yaguang Qin +4 more
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Towards a Unified Theory of Learning and Information
Entropy, 2020 In this paper, we introduce the notion of “learning capacity” for algorithms that learn from data, which is analogous to the Shannon channel capacity for communication systems.
Ibrahim Alabdulmohsin
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Axioms, 2022 We show how to apply the well-known fixed-point approach in the study of the existence, uniqueness, and stability of solutions to some particular types of functional equations. Moreover, we also obtain the Ulam stability result for them.
Ali Turab, Janusz Brzdęk, Wajahat Ali
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Designing stable neural identifier based on Lyapunov method [PDF]
Journal of Artificial Intelligence and Data Mining, 2015 The stability of learning rate in neural network identifiers and controllers is one of the challenging issues which attracts great interest from researchers of neural networks.
F. Alibakhshi +3 more
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COVID-19: Data-Driven Mean-Field-Type Game Perspective
Games, 2020 In this article, a class of mean-field-type games with discrete-continuous state spaces is considered. We establish Bellman systems which provide sufficiency conditions for mean-field-type equilibria in state-and-mean-field-type feedback form.
Hamidou Tembine
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Machine learned synthesizability predictions aided by density functional theory
Communications Materials, 2022 In data-driven approaches for materials discovery, it is essential to account for phase stability when predicting synthesizability. Here, by combining density functional theory calculations and machine learning, the authors predict the synthesizability ...
Andrew Lee +6 more
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PD-Type Iterative Learning Control for Uncertain Spatially Interconnected Systems
Mathematics, 2020 This paper puts forward a PD-type iterative learning control algorithm for a class of discrete spatially interconnected systems with unstructured uncertainty.
Longhui Zhou +4 more
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Design and Implementation of Novel LMI-Based Iterative Learning Robust Nonlinear Controller
Complexity, 2021 An iterative learning robust fault-tolerant control algorithm is proposed for a class of uncertain discrete systems with repeated action with nonlinear and actuator faults. First, by defining an actuator fault coefficient matrix, we convert the iterative
Saleem Riaz +3 more
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Probability Based Stochastic Iterative Learning Control for Batch Processes With Actuator Faults
IEEE Access, 2019 This paper proposes a new stochastic composite iterative learning control for batch processes with actuator faults that happen with a certain kind of probability.
Limin Wang, Bingyun Li
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The Impact of a Construction Play on 5- to 6-Year-Old Children’s Reasoning About Stability
Frontiers in Psychology, 2020 TheoryYoung children have an understanding of basic science concepts such as stability, yet their theoretical assumptions are often not concerned with stability.
Anke Maria Weber +2 more
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