The chaos theory emerged at the end of the 19th century, and it has given birth to a deep mathematical theory in the 20th century, with a strong practical impact (e.g., weather forecast, turbulence analysis). Periodic orbits play a key role in understanding chaotic systems. Their rigorous computation provides some insights on the chaotic behavior of the system and it enables computer assisted p...

Transformatör sistemlerinde kısa devreler, yanmalar, patlamalar, çeşitli arızalar, tehlikeli olaylar ve ekipman kayıpları gibi bir çok istenmeyen riskli durumlar meydana gelebilmektedir. Bu tip arızalar dış kaynaklı hususlardan dolayı oluşabilirken bazı durumlarda ise devreye bağlı elektriksel yükün karakteristiğinden kaynaklanabilmektedir. Yük arızaların en önemli nedenlerinden biri de transfo...

With the analysis of the technology of phase space reconstruction, a modeling and forecasting technique based on the Radial Basis Function (RBF) neural network for chaotic time series is presented in this paper. The predictive model of chaotic time series is established with the adaptive RBF neural networks and the steps of the chaotic learning algorithm with adaptive RBF neural networks are ex...

We investigate the effects of temperature on complexity features of chaotic electrochemical oscillations using the anodic electrodissolution of nickel in sulfuric acid. The precision of the "period" of chaotic oscillation is characterized by phase diffusion coefficient (D). It is shown that reduced phase diffusion coefficient (D/frequency) exhibits Arrhenius-type dependency on temperature with ...

This paper introduces a novel algorithm for determining the structure of a radial basis function (RBF) network (the number of hidden units) while it is used for dynamic modeling of chaotic time series. It can be seen that the hidden units in the RBF network can form hyperplanes to partition the input space into various regions in each of which it is possible to approximate the dynamics with a b...

Abstract. It is well known that an alone linear controller is difficult to control a chaotic system, because intensive nonlinearities exist in such system. Meanwhile, depending closely on a precise mathematical modeling of the system and high computational complexity, model predictive control has its inherent drawback in controlling nonlinear systems. In this paper, a unified linear timeinvaria...

Analysis of nonlinear autonomous systems has been a popular field of study in recent decades. As an interesting nonlinear behavior, chaotic dynamics has been intensively investigated since Lorenz discovered the first physical evidence of chaos in his famous equations. Although many chaotic systems have been ever reported in the literature, a systematic and qualitative approach for chaos generat...

Chaotic time-delay systems are attractive candidates to generate chaotic dynamics because of their relatively simple system model. Circuit realization of the time-delay part is the main drawback of these systems. In order to overcome this drawback, a chaotic time-delay system which features a binary feedback function is presented. The use of binary feedback function results in a considerably si...

Energy forecasting plays a dominant role in the sustainable development economic optimization, resource planning and secure operation of electric power systems. The variation in energy demand is a major source of uncertainty in planning for future capacity enhancement, resource needs and operation of existing generation resources. Electric utilities need monthly peak and yearly demand forecasti...