Soft-computing techniques for time series forecasting

نویسندگان

  • Ignacio Rojas
  • Héctor Pomares
چکیده

A b s t r a c t O n e w a y t o c o n t r a s t t h e b

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

Forecasting meteorological time series using soft computing methods: an empirical study

The interest of researchers in different fields of science towards modern soft computing data driven methods for time series forecasting has grown in recent years. Modeling and forecasting hydrometeorological variables is an important step in understanding climate change. The application of modern methods instead of traditional statistical techniques has lead to great improvement in past studie...

متن کامل

Short-Term Load Forecasting Using Soft Computing Techniques

Electric load forecasting is essential for developing a power supply strategy to improve the reliability of the ac power line data network and provide optimal load scheduling for developing countries where the demand is increased with high growth rate. In this paper, a short-term load forecasting realized by a generalized neuron–wavelet method is proposed. The proposed method consists of wavele...

متن کامل

Which Methodology is Better for Combining Linear and Nonlinear Models for Time Series Forecasting?

Both theoretical and empirical findings have suggested that combining different models can be an effective way to improve the predictive performance of each individual model. It is especially occurred when the models in the ensemble are quite different. Hybrid techniques that decompose a time series into its linear and nonlinear components are one of the most important kinds of the hybrid model...

متن کامل

Analysis of seasonal time series using fuzzy approach

A new methodology for the analysis and forecasting of time series is proposed. It directly employs two soft computing techniques: the fuzzy transform and the perception-based logical deduction. Thanks to the use of both these methods, and to the innovative approach, consisting of the construction of several independent models, the methodology is successfully applicable to robust long-time predi...

متن کامل

Forecasting Financial Time Series Using Multiple Regression, Multi Layer Perception, Radial Basis Function and Adaptive Neuro Fuzzy Inference System Models: A Comparative Analysis

In the last few decades, techniques such as Artificial Neural Networks and Fuzzy Inference Systems were used for developing predictive models to estimate the required parameters. Since the recent past Soft Computing techniques are being used as alternate statistical tool. Determination of nature of financial time series data is difficult, expensive, time consuming and involves complex tests. In...

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 2004