Results 11 to 20 of about 84,108 (247)
Large-scale bound constrained optimization based on hybrid teaching learning optimization algorithm
Evolutionary computing is an exciting sub-field of soft computing. Many evolutionary algorithm based on the Darwinian principles of natural selection are developed under the umbrella of EC in the last two decades.
Wali Khan Mashwani +4 more
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New observer-based control design for mismatched uncertain systems with time-delay
In this paper, the state estimation problem for a class of mismatched uncertain time-delay systems is addressed. The estimation uses observer-based control techniques.
Huynh Van Van
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Predictive models are increasingly deployed within smart manufacturing for the control of industrial plants. With this arises, the need for longāterm monitoring of model performance and adaptation of models if surrounding conditions change and the ...
Florian Bachinger +2 more
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Autonomous Evolutionary Algorithm [PDF]
Evolutionary algorithms (EA) are randomized heuristic search methods based on the principles of natural evolution (Banzhaf et al., 1998; Goldberg, 1989; Holland, 1975; Back, 1996; Koza, 1992). If we know how to describe the problem using the terminology of artificial evolution, the EAs are quite easy to apply.
openaire +3 more sources
Bias and Variance Analysis of Contemporary Symbolic Regression Methods
Symbolic regression is commonly used in domains where both high accuracy and interpretability of models is required. While symbolic regression is capable to produce highly accurate models, small changes in the training data might cause highly dissimilar ...
Lukas Kammerer +2 more
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Chaos-Based Optimization - A Review
This paper discusses the utilization of the complex chaotic dynamics given by the selected time-continuous chaotic systems as well as by the discrete chaotic maps, as the chaotic pseudo-random number generators and driving maps for the chaos based ...
Roman Senkerik +2 more
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Population Dynamics in Genetic Programming for Dynamic Symbolic Regression
This paper investigates the application of genetic programming (GP) for dynamic symbolic regression (SR), addressing the challenge of adapting machine learning models to evolving data in practical applications.
Philipp Fleck +2 more
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This paper introduces a novel sliding mode control (SMC) design utilizing a Proportional-Integral-Derivative (PID) Sliding Surface (SS) for frequency regulation in multi-area electrical power systems (EPSs) with hydropower turbines, accounting for random
Dao Trong Tran +3 more
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This paper proposes a novel load frequency control (LFC) scheme for multi-area thermal-hydro power systems (MATHPS) subject to multiple communication delays.
Anh-Tuan Tran +4 more
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Chaos in a System with an Absolute Nonlinearity and Chaos Synchronization
A system with an absolute nonlinearity is studied in this work. It is noted that the system is chaotic and has an adjustable amplitude variable, which is suitable for practical uses.
Victor Kamdoum Tamba +3 more
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