Chaotic Time Series Prediction Using Immune Optimization Theory
نویسندگان
چکیده
To solve chaotic time series prediction problem, a novel Prediction approach for chaotic time series based on Immune Optimization Theory (PIOT) is proposed. In PIOT, the concepts and formal definitions of antigen, antibody and affinity being used for time series prediction are given, and the mathematical models of immune optimization operators being used for establishing time series prediction model are exhibited. Chaotic time series is analyzed and corresponding sample space is reconstructed by phase space reconstruction method; then, the prediction model of chaotic time series is constructed by immune optimization theory; finally, using this prediction model to forecast chaotic time series. To demonstrate the effectiveness of PIOT, the three typical chaotic nonlinear time series are generated by nonlinear dynamics systems that are Lorenz, Mackey-Glass and Henon, respectively, and are used for simulating prediction. The simulation results show that PIOT is a feasible and effective prediction method, and meanwhile provides a novel prediction approach for chaotic time series.
منابع مشابه
Chaotic Analysis and Prediction of River Flows
Analyses and investigations on river flow behavior are major issues in design, operation and studies related to water engineering. Thus, recently the application of chaos theory and new techniques, such as chaos theory, has been considered in hydrology and water resources due to relevant innovations and ability. This paper compares the performance of chaos theory with Anfis model and discusses ...
متن کاملRiver Discharge Time Series Prediction by Chaos Theory
The application of chaos theory in hydrology has been gaining considerable interest in recent years.Based on the chaos theory, the random seemingly series can be attributed to deterministic rules. Thedynamic structures of the seemingly complex processes, such as river flow variations, might be betterunderstood using nonlinear deterministic chaotic models than the stochastic ones. In this paper,...
متن کاملInvestigating the Chaotic Nature of Flow the Upstream and Downstream of Zayandehrud-Dam Reservoir Using Chaotic Systems’ Criteria
River discharge is among the influential factors on the operation of water resources systems and the design of hydraulic structures, such as dams; so the study of it is of great importance. Several effective factors on this non-linear phenomenon have caused the discharge to be assumed as being accidental. According to the basics the chaos theory, the seemingly random and chaotic systems have re...
متن کاملModel Based Method for Determining the Minimum Embedding Dimension from Solar Activity Chaotic Time Series
Predicting future behavior of chaotic time series system is a challenging area in the literature of nonlinear systems. The prediction's accuracy of chaotic time series is extremely dependent on the model and the learning algorithm. On the other hand the cyclic solar activity as one of the natural chaotic systems has significant effects on earth, climate, satellites and space missions. Several m...
متن کاملChaotic Time Series Prediction for Rock-Paper-Scissors using Adaptive Social Behaviour Optimization (ASBO)
Time series prediction involves analyzing a set of data from past and current occurrences in order to predict the future set of data. In dynamic systems, chaotic behaviour is intrinsically observable and the resulting chaotic time series have nonlinear characteristics. Nevertheless, such data can be optimized to make sense out of the chaos. Multiple algorithms exist to this end, which have vari...
متن کاملذخیره 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 ناماگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید
ورودعنوان ژورنال:
- Int. J. Computational Intelligence Systems
دوره 3 شماره
صفحات -
تاریخ انتشار 2010