Self-Organized Criticality in Time Series of Power Systems Fault, Its Mechanism, and Potential Application

2010 ◽  
Vol 25 (4) ◽  
pp. 1857-1864 ◽  
Author(s):  
Duan Xianzhong ◽  
Su Sheng
Keyword(s):  
Time Series ◽  
Power Systems ◽  
Potential Application ◽  
Self Organized ◽  
Self Organized Criticality

scholarly journals Self-Organized Criticality on Twitter: Phenomenological Theory and Empirical Investigation Based on Data Analysis Results

Complexity ◽  
2019 ◽  
Vol 2019 ◽  
pp. 1-16 ◽  
Author(s):  
Andrey Dmitriev ◽  
Victor Dmitriev ◽  
Stepan Balybin
Keyword(s):  
Time Series ◽  
Critical State ◽  
Empirical Investigation ◽  
Phenomenological Theory ◽  
Self Organization ◽  
Protest Movements ◽  
Self Organized ◽  
Self Organized Criticality ◽  
Stochastic Sources ◽  
Adiabatic Mode

Recently, there has been an increasing number of empirical evidence supporting the hypothesis that spread of avalanches of microposts on social networks, such as Twitter, is associated with some sociopolitical events. Typical examples of such events are political elections and protest movements. Inspired by this phenomenon, we built a phenomenological model that describes Twitter’s self-organization in a critical state. An external manifestation of this condition is the spread of avalanches of microposts on the network. The model is based on a fractional three-parameter self-organization scheme with stochastic sources. It is shown that the adiabatic mode of self-organization in a critical state is determined by the intensive coordinated action of a relatively small number of network users. To identify the critical states of the network and to verify the model, we have proposed a spectrum of three scaling indicators of the observed time series of microposts.

scholarly journals Self-Organized Criticality: Emergent Complex Behavior in PM10 Pollution

2013 ◽  
Vol 2013 ◽  
pp. 1-7 ◽  
Author(s):  
Shi Kai ◽  
Liu Chun-Qiong ◽  
Li Si-Chuan
Keyword(s):  
Time Series ◽  
Complex Dynamics ◽  
Distribution Functions ◽  
Fluctuation Analysis ◽  
Good Prediction ◽  
Scale Invariant ◽  
Invariant Structure ◽  
Dynamical Characteristics ◽  
Self Organized ◽  
Self Organized Criticality

We analyze long-term time series of daily average PM10 concentrations in Chengdu city. Detrended fluctuation analysis of the time series shows long range correlation at one-year temporal scale. Spectral analysis of the time series indicates 1/f noise behavior. The probability distribution functions of PM10 concentrations fluctuation have a scale-invariant structure. Why do the complex structures of PM10 concentrations evolution exhibit scale-invariant? We consider that these complex dynamical characteristics can be recognized as the footprint of self-organized criticality (SOC). Based on the theory of self-organized criticality, a simplified sandpile model for PM10 pollution with a nondimensional formalism is put forward. Our model can give a good prediction of scale-invariant in PM10 evolution. A qualitative explanation of the complex dynamics observed in PM10 evolution is suggested. The work supports the proposal that PM10 evolution acts as a SOC process on calm weather. New theory suggests one way to understand the origin of complex dynamical characteristics in PM10 pollution.

Industry Trends

2012 ◽  
Vol 54 (1) ◽  
pp. 6-9 ◽  
Author(s):  
James Houran ◽  
Rense Lange ◽  
Keith Kefgen
Keyword(s):  
Time Series ◽  
Executive Coaching ◽  
Neural Nets ◽  
Noise Distribution ◽  
Pink Noise ◽  
Self Organized ◽  
Self Organized Criticality ◽  
Traditional Organization ◽  
Career Moves ◽  
Industry Trends

We explored the idea that the timing of executives’ career moves was consistent with Bak’s notion of self-organized criticality. Consistent with predictions, time series analysis of job changes for 43 hospitality executives obeyed a power law and revealed a mixture of predictable and unpredictable patterns with a musical nature (pink noise distribution). The data showed better fit for traditional ‘organization men’ versus opportunistic ‘trailblazers.’ These differences in career patterns (rhythms) could be used to reliably distinguish between these two executive-types using neural nets. Potential implications for executive coaching and development are discussed.

Subtle nonlinearity in popular album charts

1999 ◽  
Vol 02 (03) ◽  
pp. 197-208 ◽  
Author(s):  
R. Alexander Bentley ◽  
Herbert D. G. Maschner
Keyword(s):  
Time Series ◽  
Popular Music ◽  
Power Law ◽  
Large Scale ◽  
Selective Sampling ◽  
Self Organized ◽  
Self Organized Criticality ◽  
Critical Model ◽  
Power Law Distributions ◽  
Multiplicative Processes

Large-scale patterns of culture change may be explained by models of self organized criticality, or alternatively, by multiplicative processes. We speculate that popular album activity may be similar to critical models of extinction in that interconnected agents compete to survive within a limited space. Here we investigate whether popular music albums as listed on popular album charts display evidence of self-organized criticality, including a self-affine time series of activity and power-law distributions of lifetimes and exit activity in the chart. We find it difficult to distinguish between multiplicative growth and critical model hypotheses for these data. However, aspects of criticality may be masked by the selective sampling that a "Top 200" listing necessarily implies.

scholarly journals APPLICATION OF THE THEORY OF SELF-ORGANIZED CRITICALITY TO THE STUDY OF ELECTORAL BEHAVIOR

2019 ◽  
pp. 123-131
Author(s):  
D.S. Zhukov
Keyword(s):  
United States ◽  
Time Series ◽  
The United States ◽  
Electoral Behavior ◽  
The Political ◽  
Pink Noise ◽  
Political Processes ◽  
Self Organized ◽  
Self Organized Criticality ◽  
Methodological Problems

The article is devoted to methodological problems associated with the application of the theory of self-organized criticality (SOC) to political processes. The author considers the dynamics of electoral preferences in the elections of US representatives in different states from 1958 to 2016. The purpose of the study is to verify whether the hypothesis of Japanese researchers I. Shimada and T. Koyama can be extended to the United States. The hypothesis is that the detection of pink noise (an attribute of SOC) in the time series of electoral activity can be a good indicator to identify the political and transformational potential of the society. The author shows that voters’ preferences changed in pink noise mode in some states. This gives reason to build assumptions about possible avalanche-like jumps in electoral behavior in the future.

scholarly journals Self-Organized Criticality and Trend Analysis in Time Series of Blackouts for the China Power Grid

2020 ◽  
Vol 2020 ◽  
pp. 1-8
Author(s):  
Qun Yu ◽  
Na Cao ◽  
Qilin Liu ◽  
Yuqing Qu ◽  
Yumin Zhang
Keyword(s):  
Time Series ◽  
Trend Analysis ◽  
Power Grid ◽  
Data Series ◽  
Power Outage ◽  
Power Failure ◽  
Self Organized ◽  
Time Correlations ◽  
Long Time ◽  
Self Organized Criticality

This paper proposes effective evidence on the correlation between trend and self-organized criticality (SOC) of the power outage sequence in China. Taking the data series of blackouts from 1981 to 2014 in the China power grid as the research object, the method of V/S is introduced into the analysis of the power system blackout sequence to demonstrate their prominent long-time correlations. It also verifies the probability distribution of load loss about blackout size in the China power grid has a tail feature, which shows that the time series of blackouts in the China power grid is consistent with SOC. Meanwhile, a kind of mathematical statistics analysis is presented to prove that there is a seasonal trend of blackouts, and the blackout frequency and blackout size have not decreased over time but have an upward trend in the China power grid, thereby indicating that blackout risk may be increasing with time. The last 34 years’ data samples of power failure accidents in the China power grid are used to test the proposed method, and the numerical results show that the proposed self-organized criticality and trend analysis method can pave the way for further exploration of the mechanism of power failure in the China power grid.

Self-Organized Criticality in Wildfire Time Series from China

2017 ◽  
Vol 18 (4) ◽  
pp. 04017014 ◽  
Author(s):  
Jiazheng Lu ◽  
Tejun Zhou ◽  
Bo Li ◽  
Hongxian Zhang ◽  
Chuanping Wu
Keyword(s):  
Time Series ◽  
Self Organized ◽  
Self Organized Criticality

scholarly journals ANALYSIS OF RAINFALL RECORDS IN INDIA: SELF-ORGANIZED CRITICALITY AND SCALING

Fractals ◽  
2006 ◽  
Vol 14 (04) ◽  
pp. 289-293 ◽  
Author(s):  
A. SARKAR ◽  
P. BARAT
Keyword(s):  
Time Series ◽  
Power Law ◽  
Rainfall Intensity ◽  
Time Series Data ◽  
Series Data ◽  
Scaling Analysis ◽  
Rainfall Time Series ◽  
Self Organized ◽  
Time Period ◽  
Self Organized Criticality

The time series data of the monthly rainfall records (for the time period 1871–2002) in All India and different regions of India are analyzed. It is found that the distributions of the rainfall intensity exhibit perfect power law behavior. The scaling analysis revealed two distinct scaling regions in the rainfall time series.

Sign in / Sign up

Export Citation Format

Share Document