System identificationSystem identification strategies applied to aircraft gas turbine engines
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Cited by (34)
Development of models for surface tension of alcohols through symbolic regression
2020, Journal of Molecular LiquidsCitation Excerpt :The objective of genetic programming is to find the best solution for a particular problem, by genetically recombining a population of individuals that portray candidate solutions. Developed originally to automatically generate computer programs, genetic programming has been used to solve a wide range of practical problems in a variety of fields, e.g. finance [50], electronic design [51], signal processing [52], system identification [53], modeling of chemical systems [54], thermal engineering [55], among others. In genetic programming we work with a population of individuals (mathematical expressions) which evolve as the search proceeds, and the objective is to find the most qualified one.
Estimation of mass matrix in machine tool's weak components research by using symbolic regression
2019, Computers and Industrial EngineeringCitation Excerpt :The process of genetic programming is an adaptive nonlinear search process under the guidance of fitness, and also a generalized hierarchical computer program to describe the problem (Huang & Li, 2001). Originally developed for the automatic generation of computer programs, it has been used in various applications, such as finance (Chen & Yeh, 1996), electronic design (Miller, Job, & Vassilev, 2000), signal processing (Uesaka & Kawamata, 2000) and system identification (Arkov et al., 2000). GP is discussed in detail in Koza's monograph (Koza, 1992).
Data-driven fault detection, isolation and estimation of aircraft gas turbine engine actuator and sensors
2018, Mechanical Systems and Signal ProcessingCitation Excerpt :Therefore, in the literature frequency-domain techniques have been reported to provide a “great potential” for tackling the gas turbine engine parameters estimation problem [25]. Evans and his colleagues [23,25–28] have comprehensively studied these methods for the gas turbine engine dynamic identification and have applied them to a Rolls-Royce engine. Although our method requires the estimation of the Markov parameters that could otherwise have been obtained through a standard non-parametric identification method (correlation analysis), our simulations reveal that this approach will not be robust for our FDI&E problem and gas turbine engine application when the harmonic input contains a limited number of frequencies.
Performance and emission characteristics of a CI engine using nano particles additives in biodiesel-diesel blends and modeling with GP approach
2017, FuelCitation Excerpt :Numerous studies have been under taken by using GA for optimization of engine characteristics [31–41]. Numerous studies have been undertaken by using genetic programming (GP) [42–46]. GP has been utilized to construct prediction model for diagnosing the engine valve faults.
Heat transfer correlations by symbolic regression
2006, International Journal of Heat and Mass Transfer