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Journal articles on the topic 'Inverse Model'

Author: Grafiati

Published: 4 June 2021

Last updated: 25 May 2024

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1

Keream, Settar S., Ahmed N. Abdalla, Ruzlaini Ghoni, Mohd Razali Daud, and Youssif Al Mashhadany. "Robust Dynamic Inverse Controller For Spacecraft Model." International Journal of Scientific Research 3, no. 5 (2012): 113–17. http://dx.doi.org/10.15373/22778179/may2014/37.

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2

Sahoo, Abhilipsa, and Kaushika Patel. "Machine Learning-based Inverse Design Model of a Transistor." Indian Journal Of Science And Technology 17, no. 7 (2024): 617–24. http://dx.doi.org/10.17485/ijst/v17i7.3076.

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Objectives: To develop an inverse design model for transistors, utilizing machine learning algorithms to predict key design parameters specifically, the length and width based on specified gain and bandwidth requirements. And to conduct a comprehensive comparative analysis with existing literature, evaluating the efficacy and novelty of the proposed model in the context of semiconductor engineering challenges and methodologies. Methods: The comprehensive dataset, comprising 30,000 values generated through LTspice simulations, forms the basis for training the machine learning model. Utilizing a

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3

Cárcamo Hernández, A. E., and S. F. King. "Littlest inverse seesaw model." Nuclear Physics B 953 (April 2020): 114950. http://dx.doi.org/10.1016/j.nuclphysb.2020.114950.

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4

Kaipio, Jari, and Erkki Somersalo. "Statistical inverse problems: Discretization, model reduction and inverse crimes." Journal of Computational and Applied Mathematics 198, no. 2 (2007): 493–504. http://dx.doi.org/10.1016/j.cam.2005.09.027.

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5

Mehl, Steffen. "Forward Model Nonlinearity versus Inverse Model Nonlinearity." Ground Water 45, no. 6 (2007): 791–94. http://dx.doi.org/10.1111/j.1745-6584.2007.00372.x.

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6

Hu, Xiaoyin, Jianshu Li, Xiaoya Li, and Jinchuan Cui. "A Revised Inverse Data Envelopment Analysis Model Based on Radial Models." Mathematics 8, no. 5 (2020): 803. http://dx.doi.org/10.3390/math8050803.

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In recent years, there has been an increasing interest in applying inverse data envelopment analysis (DEA) to a wide range of disciplines, and most applications have adopted radial-based inverse DEA models. However, results given by existing radial based inverse DEA models can be unreliable as they neglect slacks while evaluating decision-making units’ (DMUs) overall efficiency level, whereas classic radial DEA models measure the efficiency level through not only radial efficiency index but also slacks. This paper points out these disadvantages with a counterexample, where current inverse DEA

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7

Schaich, W. L. "Model calculations of inverse photoemission." Physical Review B 45, no. 7 (1992): 3744–48. http://dx.doi.org/10.1103/physrevb.45.3744.

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8

Stipsitz, Monika, Gerhard Kahl, and Emanuela Bianchi. "Generalized inverse patchy colloid model." Journal of Chemical Physics 143, no. 11 (2015): 114905. http://dx.doi.org/10.1063/1.4930600.

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9

O'Neill, Terence J. "The Inverse Proportional Hazards Model." Statistics & Probability Letters 12, no. 2 (1991): 125–29. http://dx.doi.org/10.1016/0167-7152(91)90055-v.

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10

Kim, Young-Jin. "Comparison between Inverse Model and Chaos Time Series Inverse Model for Long-Term Prediction." Sustainability 9, no. 6 (2017): 982. http://dx.doi.org/10.3390/su9060982.

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11

Ko, Young-Rae, and Tae-Hyoung Kim. "Inverse Hysteresis Modeling for Piezoelectric Stack Actuators with Inverse Generalized Prandtl-Ishlinskii Model." Journal of Korean Institute of Intelligent Systems 24, no. 2 (2014): 193–200. http://dx.doi.org/10.5391/jkiis.2014.24.2.193.

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12

Kwon, Kyung-Woo, Suk-Joo Lee, and Jun-Seok Park. "A Case Study on Energy Performance Analysis of Retrofitted Building Using Inverse Model Toolkit." Korean Journal of Air-Conditioning and Refrigeration Engineering 26, no. 8 (2014): 394–400. http://dx.doi.org/10.6110/kjacr.2014.26.8.394.

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13

Ho, Anh Pham Huy, and Nam Thanh Nguyen. "Dynamic model identification of IPMC actuator using fuzzy NARX model optimized by MPSO." Science and Technology Development Journal 17, no. 1 (2014): 62–80. http://dx.doi.org/10.32508/stdj.v17i1.1295.

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In this paper, a novel inverse dynamic fuzzy NARX model is used for modeling and identifying the IPMC-based actuator’s inverse dynamic model. The contact force variation and highly nonlinear cross effect of the IPMC-based actuator are thoroughly modeled based on the inverse fuzzy NARX model-based identification process using experiment input-output training data. This paper proposes the novel use of a modified particle swarm optimization (MPSO) to generate the inverse fuzzy NARX (IFN) model for a highly nonlinear IPMC actuator system. The results show that the novel inverse dynamic fuzzy NARX

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14

Taheri, Mohammad Ali. "Inverse Cosmos." Scientific Journal of Cosmointel 3, TC1EN (2024): 12–31. http://dx.doi.org/10.61450/joci.v3itc1en.175.

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The Big Bang Model is the most widely accepted cosmological model regarding the origin of the universe, resting on two fundamental assumptions: one is Einstein's theory of general relativity, describing the gravitational interaction of matter with space-time, and the other is the cosmological principle, stating that an observer viewing the universe will be faced with homogeneity and isotropy, meaning that the universe has no edge. According to this model, one cannot seek a specific point of origin of the big bang, as this explosion occurred simultaneously throughout the whole universe. Through

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15

VaraPrasadRao, B., K. Gangadhara Rao, and B. Srinivasa Rao. "Inverse Rayleigh Software Reliability Growth Model." International Journal of Computer Applications 75, no. 6 (2013): 1–5. http://dx.doi.org/10.5120/13112-0470.

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16

Power, Michael Declan, and Yuexiao Dong. "Bayesian model averaging sliced inverse regression." Statistics & Probability Letters 174 (July 2021): 109103. http://dx.doi.org/10.1016/j.spl.2021.109103.

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17

Patnaik, Prachee, Debi Prasad Das, and Santosh Kumar Mishra. "Adaptive Inverse Model of Nonlinear Systems." International Journal of Intelligent Systems and Applications 7, no. 5 (2015): 40–47. http://dx.doi.org/10.5815/ijisa.2015.05.06.

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18

Havelka, Jan, and Jan Sýkora. "Künzel Model and Boundary Inverse Problem." Advanced Materials Research 1144 (March 2017): 115–20. http://dx.doi.org/10.4028/www.scientific.net/amr.1144.115.

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In order to obtain material properties of a given system it is convenient in many casesto perform only noninvasive, i.e. boundary measurements. Our interest is then focused on buildingmaterials and their functionality when exposed to heat and moisture. To describe the underlying phenomena of heat and moisture transfer we use Künzel model with stochastic description of materialproperties for its relative simplicity and sufficient accuracy. For the inverse procedure weintend to utilize the Calderón’s problem framework which is regularly used in medical imaging asElectrical Impedance Tomography a

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19

Clarke, G. P. Y. "Inverse Estimates from a Multiresponse Model." Biometrics 48, no. 4 (1992): 1081. http://dx.doi.org/10.2307/2532700.

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20

Leite, J. V., N. Sadowski, P. Kuo-Peng, N. J. Batistela, J. P. A. Bastos, and A. A. deEspindola. "Inverse Jiles–Atherton Vector Hysteresis Model." IEEE Transactions on Magnetics 40, no. 4 (2004): 1769–75. http://dx.doi.org/10.1109/tmag.2004.830998.

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21

Wigley, T. M. L. "A simple inverse carbon cycle model." Global Biogeochemical Cycles 5, no. 4 (1991): 373–82. http://dx.doi.org/10.1029/91gb02279.

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22

Dénes, István, and Péter Baranyi. "Inverse Model of DC-DC Converters." IFAC Proceedings Volumes 33, no. 28 (2000): 147–52. http://dx.doi.org/10.1016/s1474-6670(17)36825-8.

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23

Leuzzi, L. "Spin-glass model for inverse freezing." Philosophical Magazine 87, no. 3-5 (2007): 543–51. http://dx.doi.org/10.1080/14786430600919310.

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24

Kambhampati, C., R. J. Craddock, M. Tham, and K. Warwick. "Inverse model control using recurrent networks." Mathematics and Computers in Simulation 51, no. 3-4 (2000): 181–99. http://dx.doi.org/10.1016/s0378-4754(99)00116-0.

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25

Feudale, Robert N., and Steven D. Brown. "An inverse model for target detection." Chemometrics and Intelligent Laboratory Systems 77, no. 1-2 (2005): 75–84. http://dx.doi.org/10.1016/j.chemolab.2004.09.011.

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26

Zheng, Hui Jun, and Qiao Fu. "Fault Diagnoses Using Inverse Fuzzy Model." Applied Mechanics and Materials 571-572 (June 2014): 171–76. http://dx.doi.org/10.4028/www.scientific.net/amm.571-572.171.

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This paper investigates a new method of fault diagnoses and reliability analysis based on inverse fuzzy model method. The proposed method employs inverse fuzzy model solving method to estimate the component state based on the measured system performance and relationship about component state and system performance which is constructed by expert. The method is proved to be effective in fault diagnoses.

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27

Puig, Xavier, Josep Ginebra, and Marta Perez-Casany. "Extended truncated Inverse Gaussian–Poisson model." Statistical Modelling: An International Journal 9, no. 2 (2009): 151–71. http://dx.doi.org/10.1177/1471082x0800900204.

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28

Peña P, Alejandro, Jesús A. Hernández, and Victoria M. Toro. "Computational evolutionary inverse lagrangian puff model." Environmental Modelling & Software 25, no. 12 (2010): 1890–93. http://dx.doi.org/10.1016/j.envsoft.2010.04.013.

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29

SHAHVERDIEV, E. M., R. A. NURIEV, and R. H. HASHIMOV. "PARAMETER MISMATCHES AND INVERSE SYNCHRONIZATION IN THE IKEDA MODEL." International Journal of Modern Physics B 18, no. 13 (2004): 1911–18. http://dx.doi.org/10.1142/s0217979204025087.

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We investigate inverse retarded synchronization between two uni-directionally linearly coupled chaotic non-identical Ikeda models and show that parameter mismatches are of crucial importance to achieve synchronization. We establish that independent of the relation between the delay time in the coupled systems and the coupling delay time, only inverse retarded synchronization with the coupling delay time is obtained. We derive existence and stability conditions for the inverse retarded synchronization manifold. We show that with parameter mismatch or without it neither inverse complete nor inve

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30

Bigras, Pascal, Maarouf Saad, and Jules O'shea. "Convergence Analysis of an Inverse Flexible Manipulator Model Algorithm." Journal of Vibration and Control 9, no. 10 (2003): 1141–58. http://dx.doi.org/10.1177/107754603030705.

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In this paper we present a convergence analysis of an iterative method to obtain the inverse model in the virtual joint space of a class of flexible manipulators. Virtual joints are defined so as to be related kinematically to the workspace. Thus, when the desired trajectory can be transformed from the workspace to the virtual joint space, the inverse model in the virtual joint space can be used to obtain a trajectory tip-tracking controller. Because the robot model in the virtual joint space is a non-minimum phase system, its inverse is unstable. The inverse method is then based on a causal-a

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31

BISSANTZ, NICOLAI, HOLGER DETTE, and KATHARINA PROKSCH. "Model Checks in Inverse Regression Models with Convolution-Type Operators." Scandinavian Journal of Statistics 39, no. 2 (2012): 305–22. http://dx.doi.org/10.1111/j.1467-9469.2011.00778.x.

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32

Zhou, Yunji, Roland A. Matsouaka, and Laine Thomas. "Propensity score weighting under limited overlap and model misspecification." Statistical Methods in Medical Research 29, no. 12 (2020): 3721–56. http://dx.doi.org/10.1177/0962280220940334.

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Propensity score weighting methods are often used in non-randomized studies to adjust for confounding and assess treatment effects. The most popular among them, the inverse probability weighting, assigns weights that are proportional to the inverse of the conditional probability of a specific treatment assignment, given observed covariates. A key requirement for inverse probability weighting estimation is the positivity assumption, i.e. the propensity score must be bounded away from 0 and 1. In practice, violations of the positivity assumption often manifest by the presence of limited overlap

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33

Hellwinkel, Dieter, Heinrich Georg Gaa, and Reiner Gottfried. "Inverse Triphenylmethylium-Farbstoffe / Inverse Triphenylmethylium Dyes." Zeitschrift für Naturforschung B 41, no. 8 (1986): 1045–60. http://dx.doi.org/10.1515/znb-1986-0820.

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Keywords When in the conventional triphenylmethylium dye systems of the crystal violet and malachit green type, 6 and 7, the N̈ -donor and C⊕ -acceptor centers are interchanged , the “Inverse Triphenylmethylium Dye Types” 4 and 5 are obtained , showing very similar colors. The stable models with R = phenyl (8-10) and R = p-tolyl (11-13) were investigated in more detail. The visual observations were supported by the VIS spectra which show ed nearly the same longest wavelength absorption maxim a for corresponding pairs of inverse and conventional dye representatives. The experimental results can

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34

Jiang, Wen, Yi Xin Su, and Dan Hong Zhang. "Research on Inverse Control of Active Magnetic Bearing Based on Fuzzy Inverse Model." Applied Mechanics and Materials 575 (June 2014): 744–48. http://dx.doi.org/10.4028/www.scientific.net/amm.575.744.

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For magnetic bearing system with characteristics of zero damping, negative stiffness and nonlinearity, this paper put forward a method of inverse control based on the fuzzy inverse model. The fuzzy system with fuzzifier and defuzzifier was used as an interpolator to approximate the inverse model of magnetic bearing. Then we connected the fuzzy inverse model in series with the magnetic bearing system to form a generalized pseudo linear plant, and selected a PID controller to control the pseudo linear plant. The fuzzy inverse model and the PID controller together formed an inverse controller to

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35

Howell, J. R., O. A. Ezekoye, and J. C. Morales. "Inverse Design Model for Radiative Heat Transfer." Journal of Heat Transfer 122, no. 3 (2000): 492–502. http://dx.doi.org/10.1115/1.1288774.

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Inverse solution techniques are applied to the design of heat transfer systems where radiation is important. Various solutions using inverse methods are demonstrated, and it is argued that inverse design techniques provide an alternative to conventional iterative design methods that is more accurate and faster, and can provide a greatly improved first estimate of a thermal design. This estimate can then be used as a trial design in more complete thermal analysis programs for predicting system behavior, eliminating many faulty first design trials. [S0022-1481(00)02703-1]

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36

Dean, C., J. F. Lawless, and G. E. Willmot. "A mixed poisson-inverse-gaussian regression model." Canadian Journal of Statistics 17, no. 2 (1989): 171–81. http://dx.doi.org/10.2307/3314846.

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37

Virgala, Ivan, Alexander Gmiterko, Michal Kelemen, Ľubica Miková, and Martin Varga. "Inverse Kinematic Model of Humanoid Robot Hand." Applied Mechanics and Materials 611 (August 2014): 75–82. http://dx.doi.org/10.4028/www.scientific.net/amm.611.75.

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Our study deals with inverse kinematic model of humanoid robot hand. It is important for modeling to know biomechanics of biological human hand, what is discussed in the second section. Based on theoretical aspect of kinematic configuration of the hand, the hand consisting of 24 degrees of freedom is assumed. Subsequently, there are four numerical methods of inverse kinematics used, namely pseudoinverse method, Jacobian transpose method, damped least squares and optimization method. Each of them is simulated in software Matlab and the results are compared and discussed. In the conclusion the b

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38

Novikov, R. G. "Inverse scattering for the Bethe-Peierls model." Eurasian Journal of Mathematical and Computer Applications 6, no. 1 (2018): 52–55. http://dx.doi.org/10.32523/2306-6172-2018-6-1-52-55.

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39

Gilton, Davis, Gregory Ongie, and Rebecca Willett. "Model Adaptation for Inverse Problems in Imaging." IEEE Transactions on Computational Imaging 7 (2021): 661–74. http://dx.doi.org/10.1109/tci.2021.3094714.

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40

Wang, Ping, and Xiaoping Wu. "OpenMP Programming for a Global Inverse Model." Scientific Programming 10, no. 3 (2002): 253–61. http://dx.doi.org/10.1155/2002/620712.

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The objective of our investigation is to establish robust inverse algorithms to convert GRACE gravity and ICESat altimetry mission data into global current and past surface mass variations. To assess separation of global sources of change and to evaluate spatio-temporal resolution and accuracy statistically from full posterior covariance matrices, a high performance version of a global simultaneous grid inverse algorithm is essential. One means to accomplish this is to implement a general, well-optimized, parallel global model on massively parallel supercomputers. In our present work, an effic

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41

BERNARD, James, and Mark PICKELMANN. "An Inverse Linear Model of a Vehicle." Vehicle System Dynamics 15, no. 4 (1986): 179–86. http://dx.doi.org/10.1080/00423118608968850.

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42

Dhar, Deepak, and S. S. Manna. "Inverse avalanches in the Abelian sandpile model." Physical Review E 49, no. 4 (1994): 2684–87. http://dx.doi.org/10.1103/physreve.49.2684.

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43

Babovsky, H. "An inverse model problem in kinetic theory." Inverse Problems 11, no. 3 (1995): 555–70. http://dx.doi.org/10.1088/0266-5611/11/3/005.

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44

Vekslerchik, V. E. "Inverse scattering transform for the nonlinear -model." Inverse Problems 12, no. 4 (1996): 517–34. http://dx.doi.org/10.1088/0266-5611/12/4/012.

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45

Garayoa, Julia, Maria Concepion Gonzalez-Garcia, and Nuria Rius. "Soft leptogenesis in the inverse seesaw model." Journal of High Energy Physics 2007, no. 02 (2007): 021. http://dx.doi.org/10.1088/1126-6708/2007/02/021.

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46

Ma, Jianjun, Xingzhong Xu, and Junlong Zhao. "Inverse Regression in Binary Response LDV Model." Communications in Statistics - Theory and Methods 37, no. 2 (2008): 233–46. http://dx.doi.org/10.1080/03610920701649225.

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47

Tahara, Daisuke, Yukitoshi Motome, and Masatoshi Imada. "Antiferromagnetic Ising Model on Inverse Perovskite Lattice." Journal of the Physical Society of Japan 76, no. 1 (2007): 013708. http://dx.doi.org/10.1143/jpsj.76.013708.

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48

Deng, Huaxia, Rui Yue, Xinyu Lian, et al. "Self-updating inverse model for magnetorheological dampers." Smart Materials and Structures 28, no. 11 (2019): 115033. http://dx.doi.org/10.1088/1361-665x/ab473b.

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49

White, Luther W., Baxter Vieux, and David Armand. "Surface flow model: inverse problems and predictions." Advances in Water Resources 25, no. 3 (2002): 317–24. http://dx.doi.org/10.1016/s0309-1708(01)00062-8.

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50

Qian, Xie, and Huang Meichun. "Inverse Lattice Problem and Finnis-Sinclair Model." Chinese Physics Letters 12, no. 4 (1995): 221–24. http://dx.doi.org/10.1088/0256-307x/12/4/009.

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