Fitting Rectangular Signals to Time Series Data by Metaheuristic Algorithms

نویسندگان

  • Andreas M. Chwatal
  • Günther R. Raidl
چکیده

In this work we consider the application of two metaheuristics, namely evolution strategies and scatter search, to the problem of fitting rectangular signals to time-data series. The application background is to search for exoplanet-transit signals in stellar photometric observation data.

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Fitting of Count Time Series Models on the Number of Patients Referred to Addiction Treatment Centers in Semnan County

Abstract. Count data over time are observed in many application areas. Many researchers use time series patterns to analyze this data. In this paper, the poisson count time series linear models and negative binomials on this type of data with the explanatory variables are studied. The Likelihood analysis and the evaluation of count time series model based on generalized linear models are pres...

متن کامل

Algorithms for Segmenting Time Series

As with most computer science problems, representation of the data is the key to ecient and eective solutions. Piecewise linear representation has been used for the representation of the data. This representation has been used by various researchers to support clustering, classication, indexing and association rule mining of time series data. A variety of algorithms have been proposed to obtain...

متن کامل

THE EFFECTS OF INITIAL SAMPLING AND PENALTY FUNCTIONS IN OPTIMAL DESIGN OF TRUSSES USING METAHEURISTIC ALGORITHMS

Although Genetic algorithm (GA), Ant colony (AC) and Particle swarm optimization algorithm (PSO) have already been extended to various types of engineering problems, the effects of initial sampling beside constraints in the efficiency of algorithms, is still an interesting field. In this paper we show that, initial sampling with a special series of constraints play an important role in the conv...

متن کامل

Rainfall-runoff process modeling using time series transfer function

Extended Abstract 1- Introduction Nowadays, forecasting and modeling the rainfall-runoff process is essential for planning and managing water resources. Rainfall-Runoff hydrologic models provide simplified characterizations of the real-world system. A wide range of rainfall-runoff models is currently used by researchers and experts. These models are mainly developed and applied for simulation...

متن کامل

Using Wavelets and Splines to Forecast Non-Stationary Time Series

 This paper deals with a short term forecasting non-stationary time series using wavelets and splines. Wavelets can decompose the series as the sum of two low and high frequency components. Aminghafari and Poggi (2007) proposed to predict high frequency component by wavelets and extrapolate low frequency component by local polynomial fitting. We propose to forecast non-stationary process u...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 2009