A modified genetic algorithm for precise determination the geometrical orbital elements of binary stars

Attia, Abdel-Fattah; Mahmoud, Eman A.; Shahin, H.I.; Osman, Anas

doi:10.1016/j.newast.2008.08.005

Cited by 12 publications

(14 citation statements)

References 5 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The following subsections will show the results achieved by the proposed ACDE Table 2 Comparison results (Bertiau 1957;Charbonneau 2002) approach. Whenever possible, comparisons carried out with various published techniques (Bertiau 1957;Charbonneau 2002;Attia et al 2009). Table 2 shows a comparison between the values of different parameters of the x vector …”

Section: Simulation Results and Discussionmentioning

confidence: 99%

“…Equation (12) is a transcendental in E and is solved by the bisection method for nonlinear root derived in Attia et al (2009).…”

Section: Observations and Reduction Of Datamentioning

confidence: 99%

“…For an excellent review of GAs in astronomy and astrophysics, see Charbonneau (1995), andCharbonneau (2002). Attia et al (2009) determined the orbital elements of the binary star using the modified genetic algorithm AGAPOP. Shahbaz et al (2002) used differential evolution (DE) the same phase binned outburst and decay light curves of XTE of J2123-058.…”

mentioning

confidence: 99%

See 2 more Smart Citations

Precise determination of the orbital elements of binary stars using Differential Evolution

Attia

2011

Astrophys Space Sci

Self Cite

View full text Add to dashboard Cite

This paper presents an 'adaptive probability of crossover' technique, as a variation of the differential evolution algorithm (ACDE), for optimal parameter estimation in the general curve-fitting problem. The technique is applied to the determination of orbital elements of a spectroscopic binary system (eta Bootis). In the ACDE, Varying the crossover probability rate (Cr) provides faster convergence than keeping it constant. The Cr is determined for each trial parameter vector ('individual') as a function of fit goodness. The adaptation automatically updates control parameter to an appropriate value, without requiring prior knowledge of the relationship between particular parameter settings and a given problem optimization characteristics. The presented analysis of eta Bootis derives best-fitting Keplerian and phasing curves. Error estimation of the optimal parameters is also included. Comparison of the results with previously published values suggests that the ACDE technique has a useful applicability to astrophysical data analysis.

show abstract

Section: Simulation Results and Discussionmentioning

confidence: 99%

“…Equation (12) is a transcendental in E and is solved by the bisection method for nonlinear root derived in Attia et al (2009).…”

Section: Observations and Reduction Of Datamentioning

confidence: 99%

See 1 more Smart Citation

Precise determination of the orbital elements of binary stars using Differential Evolution

Attia

2011

Astrophys Space Sci

Self Cite

View full text Add to dashboard Cite

show abstract

“…where f is the fitness value of the solution; f 0 is the larger of the fitness values of the solutions to be crossed; Downloaded by [Umeå University Library] at 11:54 18 November 2014 f is the average fitness value of the population; f max is the maximum fitness value of the population, and k 1 ; k 2 ; k 3 ; k 4 Ä 1:0; and f min is the minimum fitness value of the population The AGAPOP technique is a standard GA-based technique with modifications to reduce the huge time consumed in calculations with a relatively small improvement in accuracy [24]. As the name implies, the AGAPOP technique consists of two parts: the AGA procedure and the "POP" procedure.…”

Section: The Agapopmentioning

confidence: 99%

Optimal Power Flow Using Adapted Genetic Algorithm with Adjusting Population Size

Attia

Al‐Turki

Abusorrah

2012

Electric Power Components and Systems

Self Cite

View full text Add to dashboard Cite

In this article, a new approach for the genetic algorithm is applied to solve the optimal power flow problem based on different objective functions. The main distinction of this technique is in using the adapted genetic algorithm with adjusting population size. The objective functions are minimized using various controlled system variables (generator voltages, transformer taps, and shunt capacitors). The feasibility of the proposed method is presented on the IEEE 30-bus system and compared to other well-established techniques. A comparison with other methods shows the effectiveness of the proposed technique.

show abstract

“…EB data fitting is a highly non-linear problem that suffers from degenerate solutions: the right combination of the wrong parameters can often fit the observed data as well as the actual solution. The algorithms currently in use, namely Differential Corrections (DC), Powell (1964)'s direction set method, Nelder & Mead (1965)'s Simplex method (NMS), and genetic algorithms (Attia et al 2009), have all met with success, but cannot be run robustly without experienced human intervention, making the tools fully manual.…”

Section: Introductionmentioning

confidence: 99%

Physics of Eclipsing Binaries. Ii. Toward the Increased Model Fidelity

Prša

Conroy

Horvat

et al. 2016

ApJS

292

214

View full text Add to dashboard Cite

The precision of photometric and spectroscopic observations has been systematically improved in the last decade, mostly thanks to space-borne photometric missions and ground-based spectrographs dedicated to finding exoplanets. The field of eclipsing binary stars strongly benefited from this development. Eclipsing binaries serve as critical tools for determining fundamental stellar properties (masses, radii, temperatures and luminosities), yet the models are not capable of reproducing observed data well either because of the missing physics or because of insufficient precision. This led to a predicament where radiative and dynamical effects, insofar buried in noise, started showing up routinely in the data, but were not accounted for in the models. PHOEBE (PHysics Of Eclipsing BinariEs;http://phoebe-project.org) is an open source modeling code for computing theoretical light and radial velocity curves that addresses both problems by incorporating missing physics and by increasing the computational fidelity. In particular, we discuss triangulation as a superior surface discretization algorithm, meshing of rotating single stars, light time travel effect, advanced phase computation, volume conservation in eccentric orbits, and improved computation of local intensity across the stellar surfaces that includes photon-weighted mode, enhanced limb darkening treatment, better reflection treatment and Doppler boosting. Here we present the concepts on which PHOEBE is built on and proofs of concept that demonstrate the increased model fidelity.

show abstract

A modified genetic algorithm for precise determination the geometrical orbital elements of binary stars

Cited by 12 publications

References 5 publications

Precise determination of the orbital elements of binary stars using Differential Evolution

Precise determination of the orbital elements of binary stars using Differential Evolution

Optimal Power Flow Using Adapted Genetic Algorithm with Adjusting Population Size

Physics of Eclipsing Binaries. Ii. Toward the Increased Model Fidelity

Contact Info

Product

Resources

About