Data-driven modeling decadal-to-centennial ENSO variability and its response to external forcing

2021 ◽  
Author(s):  
Aleksei Seleznev ◽  
Dmitry Mukhin ◽  
Andrey Gavrilov ◽  
Alexander Feigin
Keyword(s):  
Co2 Concentration ◽  
Data Driven ◽  
Time Interval ◽  
Solar Forcing ◽  
Russian Science ◽  
Dynamical Mechanism ◽  
Enso Variability ◽  
The Past ◽  
Sst Variability ◽  
Data Driven Modeling

<p>We investigate the decadal-to-centennial ENSO variability based on nonlinear data-driven stochastic modeling. We construct data-driven model of yearly Niño-3.4 indices reconstructed from paleoclimate proxies based on three different sea-surface temperature (SST) databases at the time interval from 1150 to 1995 [1]. The data-driven model is forced by the solar activity and CO2 concentration signals. We find the persistent antiphasing relationship between the solar forcing and Niño-3.4 SST on the bicentennial time scale. The dynamical mechanism of such a response is discussed.</p><p>The work was supported by the Russian Science Foundation (Grant No. 20-62-46056)</p><p>1. Emile-Geay, J., Cobb, K. M., Mann, M. E., & Wittenberg, A. T. (2013). Estimating Central Equatorial Pacific SST Variability over the Past Millennium. Part II: Reconstructions and Implications, Journal of Climate, 26(7), 2329-2352.</p>

Data-driven Crowd Modeling Techniques: A Survey

2022 ◽  
Vol 32 (1) ◽  
pp. 1-33
Author(s):  
Jinghui Zhong ◽  
Dongrui Li ◽  
Zhixing Huang ◽  
Chengyu Lu ◽  
Wentong Cai
Keyword(s):  
Game Design ◽  
State Of The Art ◽  
Crowd Simulation ◽  
Data Driven ◽  
Future Research ◽  
Crowd Modeling ◽  
The Past ◽  
Modeling Techniques ◽  
Comprehensive Survey ◽  
Data Driven Modeling

Data-driven crowd modeling has now become a popular and effective approach for generating realistic crowd simulation and has been applied to a range of applications, such as anomaly detection and game design. In the past decades, a number of data-driven crowd modeling techniques have been proposed, providing many options for people to generate virtual crowd simulation. This article provides a comprehensive survey of these state-of-the-art data-driven modeling techniques. We first describe the commonly used datasets for crowd modeling. Then, we categorize and discuss the state-of-the-art data-driven crowd modeling methods. After that, data-driven crowd model validation techniques are discussed. Finally, six promising future research topics of data-driven crowd modeling are discussed.

scholarly journals On the influence of climatic factors on the ratio between the cosmogenic isotope 14C and total carbon in the atmosphere in the past

2014 ◽  
Vol 41 (3) ◽  
pp. 216-222 ◽  
Author(s):  
Igor Koudriavtsev ◽  
Valentin Dergachev ◽  
Yury Nagovitsyn ◽  
Maxim Ogurtsov ◽  
Högne Jungner
Keyword(s):  
Solar Activity ◽  
Co2 Concentration ◽  
Galactic Cosmic Rays ◽  
Activity Level ◽  
Total Carbon ◽  
Solar Modulation ◽  
Time Interval ◽  
Model Calculations ◽  
Cosmogenic Isotope ◽  
The Past

Abstract Radiocarbon 14C is a cosmogenic isotope, which is most extensively used by scientists from a wide variety of fields. Its rate of generation in the atmosphere depends on solar modulation and thus, studying 14C concentration in natural archives, one can reconstruct solar activity level in the past. The paper shows results of box-model calculations of generation of the 14C isotope in the atmosphere and its relative abundance during the time interval 1389–1800 AD, taking into account influence of changing climate. This interval includes the deep minimum of solar activity and period of significant change in atmospheric concentration of CO2 and global temperature. The performed analysis showed that concentration of 14C in the atmosphere reflects not only variations of the galactic cosmic rays intensity but as well changes of temperature and atmospheric CO2 concentration. It is shown that the decrease in CO2 concentration in the atmosphere during 1550–1600 can be connected with absorption of CO2 by the ocean surface layer. Thus, taking into account the climatic changes is an important condition for the reconstruction of solar activity in the past using data based on cosmogenic isotopes.

scholarly journals Are college campuses superspreaders? A data-driven modeling study

2021 ◽  
pp. 1-11
Author(s):  
Hannah Lu ◽  
Cortney Weintz ◽  
Joseph Pace ◽  
Dhiraj Indana ◽  
Kevin Linka ◽  
...  
Keyword(s):  
College Campuses ◽  
Data Driven ◽  
Data Driven Modeling ◽  
Modeling Study

scholarly journals Gain-Preserving Data-Driven Approximation of the Koopman Operator and Its Application in Robust Controller Design

Mathematics ◽  
2021 ◽  
Vol 9 (9) ◽  
pp. 949
Author(s):  
Keita Hara ◽  
Masaki Inoue
Keyword(s):  
Controller Design ◽  
Internal Model Control ◽  
Feedback Controller ◽  
Data Driven ◽  
Koopman Operator ◽  
Plant System ◽  
Dimensional Approximation ◽  
Model Control ◽  
Data Driven Modeling ◽  
L2 Gain

In this paper, we address the data-driven modeling of a nonlinear dynamical system while incorporating a priori information. The nonlinear system is described using the Koopman operator, which is a linear operator defined on a lifted infinite-dimensional state-space. Assuming that the L2 gain of the system is known, the data-driven finite-dimensional approximation of the operator while preserving information about the gain, namely L2 gain-preserving data-driven modeling, is formulated. Then, its computationally efficient solution method is presented. An application of the modeling method to feedback controller design is also presented. Aiming for robust stabilization using data-driven control under a poor training dataset, we address the following two modeling problems: (1) Forward modeling: the data-driven modeling is applied to the operating data of a plant system to derive the plant model; (2) Backward modeling: L2 gain-preserving data-driven modeling is applied to the same data to derive an inverse model of the plant system. Then, a feedback controller composed of the plant and inverse models is created based on internal model control, and it robustly stabilizes the plant system. A design demonstration of the data-driven controller is provided using a numerical experiment.

Data-Driven Modeling Approach to Predict the Recovery Performance of Low-Salinity Waterfloods

2021 ◽  
Author(s):  
Shams Kalam ◽  
Rizwan Ahmed Khan ◽  
Shahnawaz Khan ◽  
Muhammad Faizan ◽  
Muhammad Amin ◽  
...  
Keyword(s):  
Data Driven ◽  
Low Salinity ◽  
Modeling Approach ◽  
Recovery Performance ◽  
Data Driven Modeling

scholarly journals Significant increase in quantity and quality of knee arthroplasty related research in KSSTA over the past 15 years

2021 ◽  
Author(s):  
Stephanie Kirschbaum ◽  
Thilo Kakzhad ◽  
Fabian Granrath ◽  
Andrzej Jasina ◽  
Jakub Oronowicz ◽  
...  
Keyword(s):  
Knee Arthroplasty ◽  
Special Topic ◽  
Computer Assisted ◽  
Time Interval ◽  
Search Term ◽  
Level Of Evidence ◽  
The Past ◽  
Patient Reported ◽  
Over Time ◽  
Number Of Authors

Abstract Purpose This study aimed to evaluate both publication and authorship characteristics in Knee Surgery, Sports Traumatology, Arthroscopy journal (KSSTA) regarding knee arthroplasty over the past 15 years. Methods PubMed was searched for articles published in KSSTA between January 1, 2006, and December 31st, 2020, utilising the search term ‘knee arthroplasty’. 1288 articles met the inclusion criteria. The articles were evaluated using the following criteria: type of article, type of study, main topic and special topic, use of patient-reported outcome scores, number of references and citations, level of evidence (LOE), number of authors, gender of the first author and continent of origin. Three time intervals were compared: 2006–2010, 2011–2015 and 2016–2020. Results Between 2016 and 2020, publications peaked at 670 articles (52%) compared with 465 (36%) published between 2011 and 2016 and 153 articles (12%) between 2006 and 2010. While percentage of reviews (2006–2010: 0% vs. 2011–2015: 5% vs. 2016–2020: 5%) and meta-analyses (1% vs. 6% vs. 5%) increased, fewer case reports were published (13% vs. 3% vs. 1%) (p < 0.001). Interest in navigation and computer-assisted surgery decreased, whereas interest in perioperative management, robotic and individualized surgery increased over time (p < 0.001). There was an increasing number of references [26 (2–73) vs. 30 (2–158) vs. 31 (1–143), p < 0.001] while number of citations decreased [30 (0–188) vs. 22 (0–264) vs. 6 (0–106), p < 0.001]. LOE showed no significant changes (p = 0.439). The number of authors increased between each time interval (p < 0.001), while the percentage of female authors was comparable between first and last interval (p = 0.252). Europe published significantly fewer articles over time (56% vs. 47% vs. 52%), whereas the number of articles from Asia increased (35% vs. 45% vs. 37%, p = 0.005). Conclusion Increasing interest in the field of knee arthroplasty-related surgery arose within the last 15 years in KSSTA. The investigated topics showed a significant trend towards the latest techniques at each time interval. With rising number of authors, the part of female first authors also increased—but not significantly. Furthermore, publishing characteristics showed an increasing number of publications from Asia and a slightly decreasing number in Europe. Level of evidence IV.

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