Results 31 to 40 of about 150,984 (329)
IET Collaborative Intelligent Manufacturing, 2021 Predictive models are increasingly deployed within smart manufacturing for the control of industrial plants. With this arises, the need for long‐term monitoring of model performance and adaptation of models if surrounding conditions change and the ...
Florian Bachinger +2 more
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Interaction–Transformation Evolutionary Algorithm for Symbolic Regression [PDF]
Evolutionary Computation, 2021 AbstractInteraction–Transformation (IT) is a new representation for Symbolic Regression that reduces the space of solutions to a set of expressions that follow a specific structure. The potential of this representation was illustrated in prior work with the algorithm called SymTree.
de Franca, Fabricio Olivetti +1 more
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The Lookup Table Regression Model for Histogram-Valued Symbolic Data
Stats, 2022 This paper presents the Lookup Table Regression Model (LTRM) for histogram-valued symbolic data. We first transform the given symbolic data to a numerical data table by the quantile method.
Manabu Ichino
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Hybrid Symbolic Regression with the Bison Seeker Algorithm
Mendel, 2019 This paper focuses on the use of the Bison Seeker Algorithm (BSA) in a hybrid genetic programming approach for the supervised machine learning method called symbolic regression.
Jan Merta
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Constructing Parsimonious Analytic Models for Dynamic Systems via Symbolic Regression
, 2020 Developing mathematical models of dynamic systems is central to many disciplines of engineering and science. Models facilitate simulations, analysis of the system's behavior, decision making and design of automatic control algorithms.
Ancona, Nicola +3 more
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Exhaustive Symbolic Regression
IEEE Transactions on Evolutionary Computation15 pages, 7 figures, 2 tables.
Deaglan J. Bartlett +2 more
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Algorithms, 2021 Air quality modelling that relates meteorological, car traffic, and pollution data is a fundamental problem, approached in several different ways in the recent literature.
Estrella Lucena-Sánchez +2 more
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Elite Bases Regression: A Real-time Algorithm for Symbolic Regression
, 2017 Symbolic regression is an important but challenging research topic in data mining. It can detect the underlying mathematical models. Genetic programming (GP) is one of the most popular methods for symbolic regression. However, its convergence speed might
Chen, Chen +2 more
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Control Synthesis as Machine Learning Control by Symbolic Regression Methods
Applied Sciences, 2021 The problem of control synthesis is considered as machine learning control. The paper proposes a mathematical formulation of machine learning control, discusses approaches of supervised and unsupervised learning by symbolic regression methods.
Elizaveta Shmalko, Askhat Diveev
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Constructing a no-reference H.264/AVC bitstream-based video quality metric using genetic programming-based symbolic regression [PDF]
, 2013 In order to ensure optimal quality of experience toward end users during video streaming, automatic video quality assessment becomes an important field-of-interest to video service providers.
Demeester, Piet +5 more
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