chaos theory

Predictive modeling of haze using chaos theory and deep learning algorithms

With the swift growth of urbanization and industrialization, fine particulate matter (PM10) has escalated into a major global environmental crisis.  PM10 is often used as a haze indicator, severely affecting human health and ecosystem stability.  Accurate prediction of PM10 levels is crucial, but existing models face challenges in handling vast data and achieving high accuracy.  This study investigates four years of PM10 time series in industrial area in Malaysia.  Paper aims to develop and compare haze predicting models using chaos theory, including

Color image encryption using chaotic-based cryptosystem

This paper presents research on a proposed project involving image encryption using a chaotic-based cryptosystem.  The purpose is to create an image encryption environment with additional features derived from chaos theory.  This cryptosystem applies the element of uncertainty and sensitivity to initial conditions.  The encryption uses a symmetric key; generating a key is based on a chaotic map — a nonlinear mathematical function that exhibits uncertainty and randomness based on initial values.