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Journal articles on the topic 'Individual model'

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Author: Grafiati

Published: 10 December 2022

Last updated: 29 January 2023

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1

Zhang, X., and Y. Lei. "A linkage among whole-stand model, individual-tree model and diameter-distribution model." Journal of Forest Science 56, No. 12 (December 17, 2010): 600–608. http://dx.doi.org/10.17221/102/2009-jfs.

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Stand growth and yield models include whole-stand models, individual-tree models and diameter-distribution models. In this study, the three models were linked by forecast combination and parameter recovery methods one after another. Individual-tree models combine with whole-stand models through forecast combination. Forecast combination method combines information from different models, disperses errors generated from different models, and then improves forecast accuracy. And then the forecast combination model was linked to diameter-distribution models via parameter recovery methods. During the moment estimation, two methods were used, arithmetic mean diameter and quadratic mean diameter method (A-Q method), and arithmetic mean diameter and diameter variance method (A-V method). Results showed that the forecast combination for predicting stand variables outperformed over the stand-level and tree-level models respectively; A-V method was superior to A-Q method on estimating Weibull parameters; these three different models could be linked very well via forecast combination and parameter recovery.

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2

Song, Eungyeol, Kyoungtae Kim, Sang-hoon Kim, and Sangyoun Lee. "Individual customized insole model." Journal of Korea Institute of Information, Electronics, and Communication Technology 9, no. 4 (August 30, 2016): 323–29. http://dx.doi.org/10.17661/jkiiect.2016.9.4.323.

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3

Asano, Yuta, Mark D. Fairchild, and Laurent Blondé. "Individual Colorimetric Observer Model." PLOS ONE 11, no. 2 (February 10, 2016): e0145671. http://dx.doi.org/10.1371/journal.pone.0145671.

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4

Uchmański, Janusz. "Individual variability and population regulation: an individual-based model." Oikos 90, no. 3 (September 2000): 539–48. http://dx.doi.org/10.1034/j.1600-0706.2000.900312.x.

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5

Uchmański, Janusz. "Individual variability and metapopulation dynamics: An individual-based model." Ecological Modelling 334 (August 2016): 8–18. http://dx.doi.org/10.1016/j.ecolmodel.2016.04.019.

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6

Veingerl Cic, Z., N. Vujica Herzog, and A. Macek. "Individual Work Performance Management Model." International Journal of Simulation Modelling 19, no. 1 (March 15, 2020): 112–22. http://dx.doi.org/10.2507/ijsimm19-1-507.

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7

Nasreddine, Elissar. "Two-dimensional individual clustering model." Discrete & Continuous Dynamical Systems - S 7, no. 2 (2014): 307–16. http://dx.doi.org/10.3934/dcdss.2014.7.307.

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8

Sterba, Sonya K., and Jolynn Pek. "Individual influence on model selection." Psychological Methods 17, no. 4 (2012): 582–99. http://dx.doi.org/10.1037/a0029253.

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9

Dhaene, Jan, and Martina Vandebroek. "Recursions for the individual model." Insurance: Mathematics and Economics 16, no. 1 (April 1995): 31–38. http://dx.doi.org/10.1016/0167-6687(94)00029-e.

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10

Heggie, Douglas C., and Mirek Giersz. "Modelling Individual Globular Clusters." Proceedings of the International Astronomical Union 3, S246 (September 2007): 121–30. http://dx.doi.org/10.1017/s1743921308015469.

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AbstractAstronomers have constructed models of globular clusters for over 100 years. These models mainly fall into two categories: (i) static models, such as King's model and its variants, and (ii) evolutionary models. Most attention has been given to static models, which are used to estimate mass-to-light ratios and mass segregation, and to combine data from proper motions and radial velocities. Evolutionary models have been developed for a few objects using the gaseous model, the Fokker-Planck model, Monte Carlo models and N-body models. These models have had a significant role in the search for massive black holes in globular clusters, for example.In this presentation the problems associated with these various techniques will be summarised, and then we shall describe new work with Giersz's Monte Carlo code, which has been enhanced recently to include the stellar evolution of single and binary stars. We describe in particular recent attempts to model the nearby globular cluster M4, including predictions on the spatial distribution of binary stars and their semi-major axis distribution, to illustrate the effects of about 12 Gyr of dynamical evolution. We also discuss work on an approximate way of predicting the “initial” conditions for such modelling.

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11

Uchmański, Janusz. "Resource partitioning among competing individuals and population persistence: an individual-based model." Ecological Modelling 131, no. 1 (June 2000): 21–32. http://dx.doi.org/10.1016/s0304-3800(00)00242-8.

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12

Otaki, Masayuki. "The Aggregation Problem in the Employment Theory: The Representative Individual Model or Individual Employees Model?" Theoretical Economics Letters 02, no. 05 (2012): 530–33. http://dx.doi.org/10.4236/tel.2012.25098.

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13

Jakimiuk, Beata. "Career Realization Model: Perspective of Individual Values and Attitudes." Annales Universitatis Mariae Curie-Skłodowska, sectio J, Paedagogia-Psychologia 30, no. 2 (November 22, 2017): 83. http://dx.doi.org/10.17951/j.2017.30.2.83.

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14

Siregar, Hotma Tiolina. "PENERAPAN MODEL PEMBELAJARAN KOOPERATIF DAN MODEL PEMBELAJARAN INDIVIDUAL DENGAN MENGGUNAKAN MINI LAB UNTUK MENINGKATKAN HASIL BELAJAR SMA SWASTA MEDAN." SCHOOL EDUCATION JOURNAL PGSD FIP UNIMED 7, no. 4 (December 25, 2017): 429–33. http://dx.doi.org/10.24114/sejpgsd.v7i4.8117.

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15

TANGO, Toshiro, Kazuhiro ABE, and Noriaki KANO. "A Markov Model Incorporating Individual Differences." Japanese Journal of Biometrics 9, no. 2 (1988): 123–34. http://dx.doi.org/10.5691/jjb.9.123.

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16

KINOSHITA, Minoru, Hiroaki YOSHIDA, Kenji AGUI, Yoshio ISHIKAWA, and Katsura SUGIURA. "Microcosm Simulation by Individual Based Model." Proceedings of The Computational Mechanics Conference 2000.13 (2000): 191–92. http://dx.doi.org/10.1299/jsmecmd.2000.13.191.

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17

DeHowitt, Mitzi Constance. "King's Conceptual Model and Individual Psychotherapy." Perspectives in Psychiatric Care 28, no. 4 (January 16, 2009): 11–14. http://dx.doi.org/10.1111/j.1744-6163.1992.tb00385.x.

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18

Corsini, Raymond. "Corsini's individual education: A democratic model." Group Dynamics: Theory, Research, and Practice 11, no. 4 (2007): 247–52. http://dx.doi.org/10.1037/1089-2699.11.4.247.

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19

Lambrecht, J. T., B. Hammer, A. L. Jacob, H. Schiel, M. Hunziker, T. Kreusch, and U. Kliegis. "Individual model fabrication in maxillofacial radiology." Dentomaxillofacial Radiology 24, no. 3 (August 1995): 147–54. http://dx.doi.org/10.1259/dmfr.24.3.8617386.

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20

Libai, Barak, Das Narayandas, and Clive Humby. "Toward an Individual Customer Profitability Model." Journal of Service Research 5, no. 1 (August 2002): 69–76. http://dx.doi.org/10.1177/1094670502005001007.

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21

Kornya, Peter S. "On Approximating the Individual Risk Model." North American Actuarial Journal 11, no. 2 (April 2007): 77–98. http://dx.doi.org/10.1080/10920277.2007.10597449.

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22

Ben Miled, Slimane, Amira Kebir, and Moulay Lhassan Hbid. "Individual Based Model for Grouper Populations." Acta Biotheoretica 58, no. 2-3 (July 24, 2010): 247–64. http://dx.doi.org/10.1007/s10441-010-9105-x.

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23

Dhaene*, Jan, Carmen Ribas, and Raluca Vernic***. "Recursions for the Individual Risk Model." Acta Mathematicae Applicatae Sinica, English Series 22, no. 4 (October 2006): 543–64. http://dx.doi.org/10.1007/s10255-006-0329-0.

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24

Link, William A., Evan G. Cooch, and Emmanuelle Cam. "Model-based estimation of individual fitness." Journal of Applied Statistics 29, no. 1-4 (January 2002): 207–24. http://dx.doi.org/10.1080/02664760120108700a.

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25

Gregory, R., J. R. Saunders, and V. A. Saunders. "The Paton individual-based model legacy." Biosystems 85, no. 1 (July 2006): 46–54. http://dx.doi.org/10.1016/j.biosystems.2006.02.009.

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26

TANGO, Toshiro, Kazuhiro ABE, and Noriaki KANO. "A Markov Model Incorporating Individual Differences." Japanese journal of applied statistics 19, no. 1 (1990): 1–18. http://dx.doi.org/10.5023/jappstat.19.1.

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27

Kaas, R., and H. U. Gerber. "Some alternatives for the individual model." Insurance: Mathematics and Economics 15, no. 2-3 (December 1994): 127–32. http://dx.doi.org/10.1016/0167-6687(94)90788-9.

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28

Kubo, Masao, Tatsuro Yoshimura, Akihiro Yamaguchi, and Hiroshi Sato. "Individual recognition-free target enclosure model." Artificial Life and Robotics 17, no. 1 (July 11, 2012): 11–16. http://dx.doi.org/10.1007/s10015-012-0010-z.

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29

AMUNDSON, NORMAN E. "A Model for Individual Career Counseling." Journal of Employment Counseling 26, no. 3 (September 1989): 132–38. http://dx.doi.org/10.1002/j.2161-1920.1989.tb00943.x.

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30

BIECEK, PRZEMYSŁAW, and STANISŁAW CEBRAT. "IMMUNITY IN THE NOISY PENNA MODEL." International Journal of Modern Physics C 17, no. 12 (December 2006): 1823–29. http://dx.doi.org/10.1142/s0129183106010133.

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We have modified the Penna standard sexual model in such a way, that the state of each individual has been determined by the individual fluctuation and the fluctuation of the environment. If the sum of both fluctuations is higher than the assumed limit, the organism dies. Additionally, the individuals can learn the trends of the environment's fluctuations, diminishing their deleterious effects. This mechanism leads to the higher mortality of the youngest individuals and the lowest mortality of individuals just before reaching the minimum reproduction age. These phenomena are observed in any mortality curve describing the age structures of human populations.

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31

Caloca Osorio, Oscar, and Luis Moisés Yáñez López. "Individual and Strategy: a Geometric-Mathematical Model of Negotiation." Gestión y Estrategia 47 (January 1, 2015): 37–48. http://dx.doi.org/10.24275/uam/azc/dcsh/gye/2015n47/caloca.

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32

Verrall, R. J. "The individual risk model: a compound distribution." Journal of the Institute of Actuaries 116, no. 1 (June 1989): 101–7. http://dx.doi.org/10.1017/s0020268100036465.

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The two approaches to modelling aggregate claims—the individual and the collective models—have been regarded as arising by considering a portfolio of policies in different ways. The individual risk model (IRM) is derived by considering the claims on individual policies and summing over all policies in the portfolio, while the collective risk model (CRM) is derived from the portfolio as a whole. This is sometimes held to be the main difference between the IRM and the CRM. In fact the IRM can be derived in exactly the same way as the CRM and can be regarded as a compound binomial distribution. This makes a unified treatment of risk models possible, simplifies the calculation of the mean and variance of the IRM, and facilitates the calculation of higher moments.

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33

Zhang, Ruiqi, Yuting Cao, and Yuzhang Li. "Modeling and simulation: social force model modified by Helbing model in fast pass system." MATEC Web of Conferences 355 (2022): 02041. http://dx.doi.org/10.1051/matecconf/202235502041.

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This paper introduced Helbing’s social force model, modified it with game theory. Then how individuals in the space behave in dynamic non-cooperative games was described, different macro grouping characteristics were obtained. Individual behaviours at the micro level were simulated. Setting different parameters and conditions of the model, the macro effects of individual behaviours were observed. The overall behaviour of the system was studied. It could be used to guide the allocation of public resources.

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34

Miftahurrohmah, Brina, Nur Iriawan, Catur Wulandari, and Yogantara Setya Dharmawan. "Individual Control Optimization of Drug Dosage Using Individual Bayesian Pharmacokinetics Model Approach." Procedia Computer Science 161 (2019): 593–600. http://dx.doi.org/10.1016/j.procs.2019.11.161.

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35

ÅMO, BJØRN WILLY, and LARS KOLVEREID. "ORGANIZATIONAL STRATEGY, INDIVIDUAL PERSONALITY AND INNOVATION BEHAVIOR." Journal of Enterprising Culture 13, no. 01 (March 2005): 7–19. http://dx.doi.org/10.1142/s0218495805000033.

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Two competing models of innovation behavior in organizations are tested. The first model is derived from the corporate entrepreneurship literature, suggesting that the extent to which the organization has a deliberate entrepreneurship strategy determine employees' involvement in innovation and change (Kanter, 1984). The competing model is derived from the intrapreneurship literature, primarily Pinchot (1985) and Pinchot and Pellman (1999), where the emphasis is on the employee's individual personality measured by items derived from Pinchot's (1985) test: "Are you an intrapreneur?" Both models are compared to a base model that contains relevant control variables. Finally, a fourth model, which combines all variables are compared to the other three. The models are tested using a sample of 634 business graduates employed in a diverse set of occupations and organizations. The results indicate that both the strategy and personality models outperform the base model. Moreover, the model that combines the personality of the individual and the strategy of the organization performs even better than the each of the two models separately.

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36

Baranov, Analoly N., Dmitrij O. Dobrovol’skij, and Natalia A. Fateeva. "Individual Style of Dostoevsky: Dimensions of Investigation." RUDN Journal of Language Studies, Semiotics and Semantics 12, no. 2 (December 15, 2021): 374–89. http://dx.doi.org/10.22363/2313-2299-2021-12-2-374-389.

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The article examines the existing approaches to the study of the individual style of the writer. We call these approaches models of individual style. We distinguish lexical model, syntactical model, narrative model and the model of intertextual relations. Specific features of the lexical model consist of the frequency distribution of certain words in text formation. The frequency distribution of lexical items reflects the importance of certain meanings and conceptual areas for a given author. The syntactic model of individual style is based on identifying characteristic syntactic constructions that have a high frequency rank for a particular author. The narrative model characterizes the way the story is organized. The units of the narrative model are the components of the plot and the operations that are performed on these components (moving, eliminating fragments of the narrative, combining episodes and scenes, introducing some components of the plot into others). Intertextual relations, that is, a set of semantic and formal references to other texts of the same or other authors, form an intertextual model, which also is unique for every writer. The above mentioned models complement each other and, taken together, make it possible to describe the specific features of the unique speech practices of the writer. Models of individual style are illustrated by the examples from Dostoevskys works. Modern corpus data technologies make it possible to more strictly develop the models of individual style, enhancing their objectivity by the implementation of quantitative methods. This article is a part of a project, initiated by Yu.N. Karaulov and E.L. Ginzburg.

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37

Lambrecht, J. Thomas, and Fred Brix. "Individual Skull Model Fabrication for Craniofacial Surgery." Cleft Palate-Craniofacial Journal 27, no. 4 (October 1990): 382–87. http://dx.doi.org/10.1597/1545-1569(1990)027<0382:ismffc>2.3.co;2.

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38

Lambrecht, J. Thomas, and Fred Brix. "Individual Skull Model Fabrication for Craniofacial Surgery." Cleft Palate Journal 27, no. 4 (October 1990): 382–87. http://dx.doi.org/10.1597/1545-1569_1990_027_0382_ismffc_2.3.co_2.

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39

Liu, Xiao, Zhaohui Zhang, Ziming Wei, and Pengwei Wang. "Smooth Intervention Model of Individual Interactive Behavior." International Journal of Software and Informatics 11, no. 4 (2021): 453–72. http://dx.doi.org/10.21655/ijsi.1673-7288.00256.

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40

Almer, Elizabeth Dreike, Michelle Bertolini, and Julia L. Higgs. "A Model of Individual Accounting Faculty Salaries." Issues in Accounting Education 28, no. 3 (March 1, 2013): 411–33. http://dx.doi.org/10.2308/iace-50467.

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ABSTRACT: While much has been written about how to successfully manage an academic accounting career, to date, research has not considered how accounting academics can manage their career to impact their salary. The current study utilizes publicly available individual salary information for over 1,200 tenure-track faculty at over 100 of the largest accounting programs in U.S. public universities. Using this salary data, we create a model of accounting faculty salary using individual and institutional variables for top-ranked doctoral, other doctoral, and non-doctoral programs. Our results offer additional insights into accredited public university accounting faculty salaries beyond the Association to Advance Collegiate Schools of Business (AACSB) publications, which aggregate by public/private schools and accredited/non-accredited programs. We find that Brigham Young University (BYU) 20 faculty research ranking, a financial teaching/research emphasis, being a department chair, and having a named business school can be positively associated with salary, although the specific influence varies by type of program. There is generally a U-shaped relationship between salary and academic rank, but a negative relationship with length of employment at an institution and cost of living. A systems teaching/research emphasis is negatively associated with salary at other doctoral programs. We do not find that salary is associated with gender.

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41

Courtney, Steven P., Glenn K. Chen, and Alex Gardner. "A General Model for Individual Host Selection." Oikos 55, no. 1 (May 1989): 55. http://dx.doi.org/10.2307/3565872.

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42

Cohen, Andrew L., Adam N. Sanborn, and Richard M. Shiffrin. "Model evaluation using grouped or individual data." Psychonomic Bulletin & Review 15, no. 4 (August 2008): 692–712. http://dx.doi.org/10.3758/pbr.15.4.692.

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43

Begon, M., and R. Wall. "Individual Variation and Competitor Coexistence: A Model." Functional Ecology 1, no. 3 (1987): 237. http://dx.doi.org/10.2307/2389426.

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44

Petrova, S. A. "A Propagation Model for Individual Pulse Polarization." Chinese Journal of Astronomy and Astrophysics 6, S2 (October 2006): 126–28. http://dx.doi.org/10.1088/1009-9271/6/s2/24.

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45

Lin, Lawrence, A. S. Hedayat, and Yuqing Tang. "A Comparison Model for Measuring Individual Agreement." Journal of Biopharmaceutical Statistics 23, no. 2 (February 25, 2013): 322–45. http://dx.doi.org/10.1080/10543406.2011.616970.

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46

Phillips, Kem F. "A log-normal model for individual bioequivalence." Journal of Biopharmaceutical Statistics 3, no. 2 (January 1, 1993): 185–201. http://dx.doi.org/10.1080/10543409308835059.

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47

Gauyacq, J. P., and N. Lorente. "A model for individual quantal nano-skyrmions." Journal of Physics: Condensed Matter 31, no. 33 (May 29, 2019): 335001. http://dx.doi.org/10.1088/1361-648x/ab1f3a.

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48

Gutierrez-Milla, A., F. Borges, R. Suppi, and E. Luque. "Individual-oriented Model Crowd Evacuations Distributed Simulation." Procedia Computer Science 29 (2014): 1600–1609. http://dx.doi.org/10.1016/j.procs.2014.05.145.

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49

Bousquet, Alain, and Marc Ivaldi. "An individual choice model of energy mix." Resource and Energy Economics 20, no. 3 (September 1998): 263–86. http://dx.doi.org/10.1016/s0928-7655(97)00037-7.

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50

Charret, I. C., J. N. C. Louzada, and A. T. Costa. "Individual-based model for coevolving competing populations." Physica A: Statistical Mechanics and its Applications 385, no. 1 (November 2007): 249–54. http://dx.doi.org/10.1016/j.physa.2007.06.013.

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