Application of genetic algorithms for a new approach for seismic building monitoring: integrated measurement systems with physical and virtual sensors

In measurement systems operating under various disturbances the probabilistic characteristics of measurement noises are usually known approximately. To improve the observation accuracy, a new approach to the Kalman’s filter adaptation is proposed. In this approach, the Covariance Matrix of Measurement Noises (CMMN) is estimated by accurate measurements detected irregularly by the mobile object observation system (from radiofrequency identifiers, etalon reference, fixed points etc.). The problem of adaptive estimation of the observer’s noises covariance matrix in the Kalman filter is solved analytically for two cases: mutual noises correlation, and its absence. The numerical example for adaptive filtration of complexing navigation system parameters of a mobile object using irregular accurate measurements is given to illustrate the effectiveness of the proposed algorithm. Coordinate estimating errors have changed in comparison with the traditional scheme from 100 m to 2 m in latitude, and from 200 m to 1.5 m in longitude.

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When Darwin Met Einstein: Gravitational Lens Inversion with Genetic Algorithms

Publications of the Astronomical Society of Australia ◽

10.1071/as04070 ◽

2005 ◽

Vol 22 (2) ◽

pp. 128-135 ◽

Cited By ~ 11

Author(s):

Brendon J. Brewer ◽

Geraint F. Lewis

Keyword(s):

Genetic Algorithms ◽

Gravitational Lensing ◽

Surface Brightness ◽

Initial Study ◽

Brightness Distribution ◽

Gravitational Lens ◽

Atmospheric Effects ◽

Lens Model ◽

New Approach ◽

Genetic Algorithm Approach

AbstractGravitational lensing can magnify a distant source, revealing structural detail which is normally unresolvable. Recovering this detail through an inversion of the influence of gravitational lensing, however, requires optimisation of not only lens parameters, but also of the surface brightness distribution of the source. This paper outlines a new approach to this inversion, utilising genetic algorithms to reconstruct the source profile. In this initial study, the effects of image degradation due to instrumental and atmospheric effects are neglected and it is assumed that the lens model is accurately known, but the genetic algorithm approach can be incorporated into more general optimisation techniques, allowing the optimisation of both the parameters for a lensing model and the surface brightness of the source.

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Genetic Algorithms: A New Approach to the Timetable Problem

Combinatorial Optimization ◽

10.1007/978-3-642-77489-8_14 ◽

1992 ◽

pp. 235-239 ◽

Cited By ~ 12

Author(s):

Alberto Colorni ◽

Marco Dorigo ◽

Vittorio Maniezzo

Keyword(s):

Genetic Algorithms ◽

New Approach ◽

Timetable Problem

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Optical Satellite Multiobjective Genetic Algorithms for Investigation of MH370 Debris

Genetic Algorithms and Remote Sensing Technology for Tracking Flight Debris - Advances in Mechatronics and Mechanical Engineering ◽

10.4018/978-1-7998-1920-2.ch009 ◽

2020 ◽

pp. 166-207

Keyword(s):

Genetic Algorithm ◽

Genetic Algorithms ◽

Cloud Cover ◽

Optical Remote Sensing ◽

New Approach ◽

Precise Method ◽

Spectral Signatures ◽

Remote Sensing Technique ◽

Multiobjective Genetic Algorithms ◽

Strength Constraints

At present, there is no precise method that can inform where the lost flight MH370 is. This chapter proposes a new approach to search for the missing flight MH370. To this end, multiobjective genetic algorithms are implemented. In this regard, a genetic algorithm is taken into consideration to optimize the MH370 debris that is notably based on the geometrical shapes and spectral signatures. Currently, there may be three limitations to optical remote sensing technique: (1) strength constraints of the spacecraft permit about two hours of scanning consistently within the day, (2) cloud cover prevents unique observations, and (3) moderate information from close to the ocean surface is sensed through the scanner. Needless to say that the objects that are spotted by different satellite data do not scientifically belong to the MH370 debris and could be just man-made without accurate identifications.

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