A pilot study of river flow prediction in urban area based on phase space reconstruction

Adenan, Nur Hamiza; Hamid, Nor Zila Abd; Mohamed, Zulkifley; Noorani, Mohd Salmi Md

doi:10.1063/1.4995843

Cited by 10 publications

(8 citation statements)

References 8 publications

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“…This method has its own advantages as prediction of PM10 is done simply by using time series from PM10 pollution only, without involving time series from other factors. Local approximation method has been used in Malaysia to predict O3 time series (for example, see Hamid & Noorani, 2013;Zaim & Hamid, 2017;Hamid, 2018a), temperature time series (Hamid, 2018b, Hamid, 2018c and streamflow time series (Adenan et. al., 2017).…”

Section: Dynamics Of Pm10 Time Series In Some Countries Such Asmentioning

confidence: 99%

Prediction of PM10 Time Series at Industrial Area Through an Improved Local Linear Approximation Method

2020

ASMSJ

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Section: Dynamics Of Pm10 Time Series In Some Countries Such Asmentioning

confidence: 99%

Prediction of PM10 Time Series at Industrial Area Through an Improved Local Linear Approximation Method

2020

ASMSJ

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“…The phase space reconstruction has found a wide range of applications in the field of research, such as wind speed forecasting for wind farms [ 84 ], analyzing molecular dynamics of polymers [ 85 ], river flow prediction in urban area [ 86 ], and biosignal (such as ECG and EEG) analysis [ 28 ]. Among the applications related to biosignal analysis, many extensive studies have been performed for the analysis of ECG signals [ 87 ].…”

Section: Applications Of Nonlinear Dynamical System Analysis Methomentioning

confidence: 99%

A Review on the Nonlinear Dynamical System Analysis of Electrocardiogram Signal

Nayak

Bit

Dey

et al. 2018

Journal of Healthcare Engineering

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Electrocardiogram (ECG) signal analysis has received special attention of the researchers in the recent past because of its ability to divulge crucial information about the electrophysiology of the heart and the autonomic nervous system activity in a noninvasive manner. Analysis of the ECG signals has been explored using both linear and nonlinear methods. However, the nonlinear methods of ECG signal analysis are gaining popularity because of their robustness in feature extraction and classification. The current study presents a review of the nonlinear signal analysis methods, namely, reconstructed phase space analysis, Lyapunov exponents, correlation dimension, detrended fluctuation analysis (DFA), recurrence plot, Poincaré plot, approximate entropy, and sample entropy along with their recent applications in the ECG signal analysis.

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“…From the 1990s onward, runoff time series have been assumed as responses of dynamical systems resulting from the nonlinear coupling of precipitation and the catchment state (Jayawardena & Lai, 1994; Porporato & Ridolfi, 1997; Q. Liu et al., 1998). In this context, dynamical systems theory has been applied to runoff time series (Adenan et al., 2017; Costa et al., 2012; Jayawardena & Lai, 1994, Laio et al., 2003; Q. Liu et al., 1998; Porporato & Ridolfi, 1997; Velickov, 2004). This technique has also been applied to evaporation (Baydaroglu & Kocak, 2014) or rainfall forecasts (Ouyang et al., 2016).…”

Section: Introductionmentioning

confidence: 99%

“…Liu et al, 1998). In this context, dynamical systems theory has been applied to runoff time series (Adenan et al, 2017;Costa et al, 2012;Jayawardena & Lai, 1994, Laio et al, 2003Q. Liu et al, 1998;Porporato & Ridolfi, 1997;Velickov, 2004).…”

mentioning

confidence: 99%

Practical Data‐Driven Flood Forecasting Based on Dynamical Systems Theory

Okuno

Ikeuchi²,

Aihara³

2021

Water Resources Research

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The severity of climatic natural disasters has been increasing over recent years, and repetitive flooding incidents have led to losses of numerous lives. In Japan, rapid flooding of small and steep rivers (flash floods) is an especially serious problem, and there are many rivers that may flood within several hours after heavy rainfall. For example, in the year 2016, Omoto River flooded in a few hours, leading to the loss of many lives (Nursing home operator failed to act on typhoon advisory before fatal flooding, 2016), and heavy rainfall in northern Kyushu in 2017 killed many people because of the resulting rapid floods in associated small rivers (Hazarika et al., 2020). Short-term rainfall intensity directly affects the river flow in such rivers, and the frequency of the rainfall exceeding 50 mm/h has increased by 1.4 times compared to 30 years ago in Japan (Japan Meteorological Agency, n.d.). Spurred by the flooding damage, the Japan administrative agencies launched a policy to increase inexpensive and maintenance-free water gauges for various rivers (Sato et al., 2019). Simultaneously, owing to the recent progress in "the Internet of Things," the water gauges are increasingly deployed by thousands every year, and we can monitor water levels via website (Ministry of Land, Infrastructure & Tourism, n.d.-a) in real time. Although these inexpensive water gauges have been widely used to monitor water levels in recent years, it is difficult to execute timely and properly evacuation actions using only information on the water level at a specific point in time; this is because water level increases tend to be rapid during flooding events.

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A pilot study of river flow prediction in urban area based on phase space reconstruction

Cited by 10 publications

References 8 publications

Prediction of PM10 Time Series at Industrial Area Through an Improved Local Linear Approximation Method

Prediction of PM10 Time Series at Industrial Area Through an Improved Local Linear Approximation Method

A Review on the Nonlinear Dynamical System Analysis of Electrocardiogram Signal

Practical Data‐Driven Flood Forecasting Based on Dynamical Systems Theory

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