A  B  C  D  E  F  G  H  I  J  K  L  M  N  O  P  Q  R  S  T  U  V  W  X  Y  Z  

  Subjects -> STATISTICS (Total: 130 journals)
The end of the list has been reached or no journals were found for your choice.
Similar Journals
Journal Cover
Advances in Complex Systems
Journal Prestige (SJR): 0.25
Citation Impact (citeScore): 1
Number of Followers: 10  
 
  Hybrid Journal Hybrid journal (It can contain Open Access articles)
ISSN (Print) 0219-5259 - ISSN (Online) 1793-6802
Published by World Scientific Homepage  [120 journals]
  • ENTROPIC ANALYSIS OF PUBLIC TRANSPORT SYSTEM STRIKES

    • Free pre-print version: Loading...

      Authors: MARCOS E. GAUDIANO, CARLOS M. LUCCA, JORGE A. REVELLI
      Abstract: Advances in Complex Systems, Volume 24, Issue 06, September 2021.
      In this work, we study the hierarchical properties observed in temporal patterns of public transport strike records of Córdoba city, Argentina. We show how a previously developed entropy-based methodology can be applied here to unveil different strike regimes, to which particular political uncontrollability degrees can be naturally associated. From data analysis, a successive increment in the uncontrollability of the public transport system can be quantitatively inferred. The proposed analysis turns out to be easily generalizable to other contexts, providing a theoretical framework for contrasting the intensity of the strikes, independently of its nature, city and/or historical time.
      Citation: Advances in Complex Systems
      PubDate: 2022-03-03T08:00:00Z
      DOI: 10.1142/S0219525922500023
      Issue No: Vol. 24, No. 06 (2022)
       
  • USE OF GAUSSIAN PROCESS TO MODEL, PREDICT AND EXPLAIN HUMAN EMOTIONAL
           RESPONSE TO CHINESE TRADITIONAL MUSIC

    • Free pre-print version: Loading...

      Authors: JUN SU, PENG ZHOU
      Abstract: Advances in Complex Systems, Volume 24, Issue 06, September 2021.
      Music listening is one of the most enigmatic of human mental phenomena; it not only triggers emotions but also changes our behavior. During the music session many people are observed to exhibit varying emotional response, which can be influenced by diverse factors such as music genre and instrument as well as the personal attributes of audiences. In this study, we assume that there is an intrinsic, complex and implicit relationship between the basic sound features of music and human emotional response to the music. The response levels of 12 individuals to a representative repertoire of 36 classical/popular Chinese traditional music (CTM) are systematically analyzed using the chills as a quantitative indicator, totally resulting in 432 ([math]) CTM–individual pairs that define a systematic individual-to-music response profile (SPTMRP). Gaussian process (GP) is then employed to model the multivariate correlation of SPTMRP profile with 15 sound features (including 5 Timbres, 4 Rhythms and 6 Pitchs) and 5 individual features in a supervised manner, which is also improved by genetic algorithm (GA) feature selection and compared with other machine learning methods. It is shown that the built GP regression model possesses a strong internal fitting ability ([math]) and a good external predictive power ([math]), which performed much better than linear PLS and nonlinear SVM and RF, confirming that the human emotional response to music can be quantitatively explained by GP methodology. Statistical examination of the GP model reveals that the sound features contribute more significantly to emotional response than individual features; their importance increases in the order: [math], in which the spectral centroid (SC), relative amplitude of salient peaks (RASP), ratio of peak amplitudes (RPA), sum of all rhythm histograms (SARH) and period of unfolded maximum peak (PUMP) as well as gender are primarily responsible for the response.
      Citation: Advances in Complex Systems
      PubDate: 2022-02-25T08:00:00Z
      DOI: 10.1142/S0219525922500011
      Issue No: Vol. 24, No. 06 (2022)
       
  • PEDESTRIAN DYNAMICS IN SINGLE-FILE MOVEMENT UNDER BACKGROUND MUSIC WITH
           DIFFERENT TEMPOS

    • Free pre-print version: Loading...

      Authors: GUANG ZENG, JUN ZHANG, RUI YE, ANDREAS SCHADSCHNEIDER, SHUCHAO CAO, QIAO WANG, WEIGUO SONG
      Abstract: Advances in Complex Systems, Volume 24, Issue 06, September 2021.
      Large crowds are challenging the comfort and safety level of big cities, while music may be a potential method to improve pedestrian flow. This paper focuses on the influence of different tempos and types of background music on pedestrian dynamics. Three tempos (90[math]beats/min (BPM), 120[math]BPM and 150[math]BPM) and two types (pure music and metronome stimuli) of music are considered. It is found that more frequent stop-and-go behaviors emerge with rhythms. Compared with that under a low tempo (90[math]BPM) of rhythm condition, stopping is more frequent with a high tempo one (120[math]BPM or 150[math]BPM). The number of stopping pedestrians per unit time increases 68.57%, 376.00%, 298.29%, 224.00%, 438.29% and 393.71% with 90 BPM, 120[math]BPM and 150[math]BPM music, 90[math]BPM, 120[math]BPM and 150[math]BPM metronome, compared with that without any rhythm, respectively. The velocity and flow are lower, and higher local densities appear with background music. The step frequency at high density with rhythms ([math], [math] and [math][math]Hz for 90[math]BPM, 120[math]BPM and 150[math]BPM music; [math], [math] and [math][math]Hz for 90[math]BPM, 120[math]BPM and 150[math]BPM metronome) is lower than that without any rhythm ([math][math]Hz). Pedestrians need more time to avoid collisions and to step under background music conditions, because they are influenced by the music and not fully focusing on walking. As a result, step frequency decreases and stopping behavior is more frequent. This in turn leads to the decrease of the velocity and flow and the emergence of higher local densities. Our study will be helpful for understanding the effect of background music on pedestrian dynamics.
      Citation: Advances in Complex Systems
      PubDate: 2022-02-24T08:00:00Z
      DOI: 10.1142/S0219525921500119
      Issue No: Vol. 24, No. 06 (2022)
       
  • DETECTING AND MEASURING FINANCIAL CYCLES IN HETEROGENEOUS AGENTS MODELS:
           AN EMPIRICAL ANALYSIS

    • Free pre-print version: Loading...

      Authors: FILIPPO GUSELLA
      Abstract: Advances in Complex Systems, Ahead of Print.
      This paper proposes a macroeconometric analysis to depict and measure possible financial cycles that emerge due to the dynamic interaction between heterogeneous market participants. We consider two-type heterogeneous speculative agents: Trend followers tend to follow the price trend while contrarians go against the wind. As agents’ beliefs are unobserved variables, we construct a state-space model where heuristics are considered as unobserved state components and from which the conditions for endogenous cycles can be mathematically derived and empirically tested. Further, we specifically measure the length of endogenous financial cycles. The model is estimated using the equity price index for the 1960–2020 period for the UK, France, Germany, Italy, Ireland, and the USA. We find empirical evidence of endogenous financial cycles for all countries, with the highest frequencies in the USA and the UK.
      Citation: Advances in Complex Systems
      PubDate: 2022-06-22T07:00:00Z
      DOI: 10.1142/S0219525922400021
       
  • STRATEGICALLY BIASED LEARNING IN MARKET INTERACTIONS

    • Free pre-print version: Loading...

      Authors: GIULIO BOTTAZZI, DANIELE GIACHINI
      Abstract: Advances in Complex Systems, Ahead of Print.
      We consider a market economy where two rational agents are able to learn the distribution of future events. In this context, we study whether moving away from the standard Bayesian belief updating, in the sense of under-reaction to some degree to new information, may be strategically convenient for traders. We show that, in equilibrium, strong under-reaction occurs, thus rational agents may strategically want to bias their learning process. Our analysis points out that the underlying mechanism driving ex-ante strategical decisions is diversity seeking. Finally, we show that, even if robust with respect to strategy selection, strong under-reaction can generate low realized welfare levels because of a long transient phase in which the agent makes poor predictions.
      Citation: Advances in Complex Systems
      PubDate: 2022-06-13T07:00:00Z
      DOI: 10.1142/S0219525922500047
       
  • THE ROLE OF NETWORK EMBEDDEDNESS ON THE SELECTION OF COLLABORATION
           PARTNERS: AN AGENT-BASED MODEL WITH EMPIRICAL VALIDATION

    • Free pre-print version: Loading...

      Authors: FRANK SCHWEITZER, ANTONIOS GARAS, MARIO V. TOMASELLO, GIACOMO VACCARIO, LUCA VERGINER
      Abstract: Advances in Complex Systems, Ahead of Print.
      We use a data-driven agent-based model to study the core–periphery structure of two collaboration networks, R&D alliances between firms and co-authorship relations between scientists. To characterize the network embeddedness of agents, we introduce a coreness value obtained from a weighted [math]-core decomposition. We study the change of these coreness values when collaborations with newcomers or established agents are formed. Our agent-based model is able to reproduce the empirical coreness differences of collaboration partners and to explain why we observe a change in partner selection for agents with high network embeddedness.
      Citation: Advances in Complex Systems
      PubDate: 2022-05-25T07:00:00Z
      DOI: 10.1142/S0219525922500035
       
 
JournalTOCs
School of Mathematical and Computer Sciences
Heriot-Watt University
Edinburgh, EH14 4AS, UK
Email: journaltocs@hw.ac.uk
Tel: +00 44 (0)131 4513762
 


Your IP address: 34.239.147.7
 
Home (Search)
API
About JournalTOCs
News (blog, publications)
JournalTOCs on Twitter   JournalTOCs on Facebook

JournalTOCs © 2009-