Fractional order Lorenz based physics informed SARFIMA-NARX model to monitor and mitigate megacities air pollution

Bukhari, Ayaz Hussain; Raja, Muhammad Asif Zahoor; Shoaib, Mohammed; Kiani, Adiqa Kausar

doi:10.1016/j.chaos.2022.112375

Cited by 23 publications

(3 citation statements)

References 66 publications

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“…Since the 19th century, when Poincaré found chaos of the conservative systems and introduced the concept of chaos correlation, until the meteorologist Lorenz wrote that beautiful masterpiece by studying chaos in the atmosphere [1,2]. So far, the theoretical knowledge of chaos has been rapidly developed and has an abundant theoretical background, and its chaos models exist widely in biology, physics, electronic circuits, and engineering [3][4][5][6]. The building of a chaotic system with better and stronger chaotic properties has been the direction of many researchers for a long time.…”

Section: Introductionmentioning

confidence: 99%

“…The system is affected by changes in parameters When the initial values are (0.1,0.1,0.1), b = 4, c = 2, d = 1.01, and q = 0.9, in figure6(a), the bifurcation phenomenon of the system (5) varying with the parameter a in the interval[4,8] is depicted, the transformation process of the motion state of the system from one steady state to multiple steady states or chaotic states.…”

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confidence: 99%

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Finite-time synchronization of fractional-order chaotic system based on hidden attractors

Yan,

Zhang,

Jiang

et al. 2023

Phys. Scr.

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A new 3D fractional-order chaotic system is obtained by improving the Sprott-A system and introducing the definition of fractional calculus to it. Then the new system is certified to be chaotic by studying and analyzing the phase diagram, Lyapunov exponents, and smaller alignment index tests. Then the analysis of equilibrium points finds that the new system has virtually no equilibrium points and hidden attractors. The new system is dynamically analyzed by bifurcation diagram, time-domain waveform and complexity, it is indicated that the system is susceptible to initial conditions, and with the changes of different parameters the system produced different scroll types of attractors. In addition, to verify the feasibility of the system, a simulation circuit design based on Multisim is therefore carried out. Finally, the finite-time synchronization of the fractional-order system is successfully achieved by taking advantage of the high security of the hidden attractors.

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Section: Introductionmentioning

confidence: 99%

mentioning

confidence: 99%

Finite-time synchronization of fractional-order chaotic system based on hidden attractors

Yan,

Zhang,

Jiang

et al. 2023

Phys. Scr.

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“…This work explored and adapted the skills of nonlinear self-regressive networks with exogenous input (NARX) in the predicting of particle matter PM 10 and PM 2.5 measured at the Polytechnic Institute of Beja, located in the city of Beja, in the Alentejo Region, Portugal. This NARX network was successfully applied for the prediction of the PM 10 particle material collected in the city of São Carlos (state of São Paulo, Brazil [4] and Agadir, Morocco [20]) and PM 10 /PM in the city of Punjab, Pakistan [21].…”

Section: Introductionmentioning

confidence: 99%

Monitoring and Prediction of Particulate Matter (PM2.5 and PM10) around the Ipbeja Campus

et al. 2022

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Nowadays, most of the world’s population lives in urban centres, where air quality levels are not strictly checked; citizens are exposed to air quality levels over the limits of the World Health Organization. The interaction between the issuing and atmospheric sources influences the air quality or level. The local climate conditions (temperature, humidity, winds, rainfall) determine a greater or less dispersion of the pollutants present in the atmosphere. In this sense, this work aimed to build a math modelling prediction to control the air quality around the campus of IPBeja, which is in the vicinity of a car traffic zone. The researchers have been analysing the data from the last months, particle matter (PM10 and PM2.5), and meteorological parameters for prediction using NARX. The results show a considerable increase in particles in occasional periods, reaching average values of 135 μg/m3 for PM10 and 52 μg/m3 for PM2.5. Thus, the monitoring and prediction serve as a warning to perceive these changes and be able to relate them to natural phenomena or issuing sources in specific cases.

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Hyper-chaos control synchronization for a fractional-order Cattaneo-Christov heat flux hybrid model with an optimal control approach

Surendar,

Muthtamilselvan,

Al-Mdallal

2024

Nonlinear Dyn

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Fractional order Lorenz based physics informed SARFIMA-NARX model to monitor and mitigate megacities air pollution

Cited by 23 publications

References 66 publications

Finite-time synchronization of fractional-order chaotic system based on hidden attractors

Finite-time synchronization of fractional-order chaotic system based on hidden attractors

Monitoring and Prediction of Particulate Matter (PM2.5 and PM10) around the Ipbeja Campus

Hyper-chaos control synchronization for a fractional-order Cattaneo-Christov heat flux hybrid model with an optimal control approach

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