Journal articles: 'Optimizing parameters'

1

Lysenko, L. L., and L. V. Gorodilov. "Optimizing publsed-machine parameters." Journal of Mining Science 33, no. 4 (July 1997): 356–62. http://dx.doi.org/10.1007/bf02765855.

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El-Fishawy, Nawal, Mohammad M. Zahra, and Mostafa El-gamala. "OPTIMIZING WIMAX MAC LAYER PARAMETERS." JES. Journal of Engineering Sciences 39, no. 6 (November 1, 2011): 1403–15. http://dx.doi.org/10.21608/jesaun.2011.129431.

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Ríos-Fachal, Matilde, Javier Tarrío-Saavedra, Jorge López-Beceiro, Salvador Naya, and Ramón Artiaga. "Optimizing fitting parameters in thermogravimetry." Journal of Thermal Analysis and Calorimetry 116, no. 3 (January 30, 2014): 1141–51. http://dx.doi.org/10.1007/s10973-013-3623-0.

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Tamvakis, Androniki, Vasilis Trygonis, John Miritzis, George Tsirtsis, and Sofie Spatharis. "Optimizing biodiversity prediction from abiotic parameters." Environmental Modelling & Software 53 (March 2014): 112–20. http://dx.doi.org/10.1016/j.envsoft.2013.12.001.

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Bemmerl, Thomas, and Thomas Bonk. "Optimizing cache parameters using CAE workstations." Microprocessing and Microprogramming 24, no. 1-5 (August 1988): 541–46. http://dx.doi.org/10.1016/0165-6074(88)90107-x.

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Huey, Gary, Susan Stair, and Robert Stern. "Hyaluronic Acid Determinations: Optimizing Assay Parameters." Matrix 10, no. 2 (May 1990): 67–74. http://dx.doi.org/10.1016/s0934-8832(11)80172-1.

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Lanciano, Rachelle. "Optimizing radiation parameters for cervical cancer." Seminars in Radiation Oncology 10, no. 1 (January 2000): 36–43. http://dx.doi.org/10.1016/s1053-4296(00)80019-3.

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Bitar, Nabil N., and Carol Y. Espy‐Wilson. "Optimizing acoustic parameters for phonetic features." Journal of the Acoustical Society of America 100, no. 4 (October 1996): 2756. http://dx.doi.org/10.1121/1.416323.

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Galiani, Silvia, Benjamin Harke, Giuseppe Vicidomini, Gabriele Lignani, Hanako Tsushima, Evelina Chieregatti, Fabio Benfenati, Paolo Bianchini, and Alberto Diaspro. "Optimizing Parameters for Wll STED Imaging." Biophysical Journal 102, no. 3 (January 2012): 725a. http://dx.doi.org/10.1016/j.bpj.2011.11.3932.

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Ristovska, Bojana, Elena Papazoska, and Valentina Gecevska. "IMPROVING MANUFACTURING PROCESS BY OPTIMIZING TIME PARAMETERS." Journal of Production Engineering 22, no. 1 (June 2019): 42–46. http://dx.doi.org/10.24867/jpe-2019-01-042.

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11

Hu, Jian Hua, and Yuan Hua Shuang. "A Reverse Approach in Optimizing Pass Parameters." Advanced Materials Research 113-116 (June 2010): 1707–11. http://dx.doi.org/10.4028/www.scientific.net/amr.113-116.1707.

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A method combines a back propagation neural networks (BPNN) with the data obtained using finite element method (FEM) is introduced in this paper as an approach to solve reverse problems. This paper presents the feasibility of this approach. FEM results are used to train the BPNN. Inputs of the network are associated with dimension deviation values of the steel pipe, and outputs correspond to its pass parameters. Training of the network ensures low error and good convergence of the learning process. At last, a group of optimal pass parameters are obtained, and reliability and accuracy of the parameters are verified by FEM simulation.

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Xu, Guang Shen, Gen Yang, and Jing Gong. "Optimizing Build Parameters for Integral Stereolithography System." Advanced Materials Research 424-425 (January 2012): 52–55. http://dx.doi.org/10.4028/www.scientific.net/amr.424-425.52.

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To improve the dimension accuracy, an experimental investigation has been conducted to determine the optimum build parameters of integral stereolithography (SL) system with Taguchi method. The build parameters include shrinkage compensation factor of resin (factor A), liquid surface waiting time (factor B), exposure time (factor C) and light intensity (factor D). It was found that factor A, factor B, factor D and the interaction between factor A and factor D significantly affect the dimension accuracy, and the interaction between factor A and factor B, the interaction between factor A and factor D also have effects on the dimension accuracy. The optimum factors combination of the integral SL system is concluded by using ANOVA. With the optimum factors combination, an error of ±10μm has been reached using the integral SL system. Confirmation experiment results indicated that the dimension accuracy has been significantly improved with the optimum factors combination

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Prokopyev, V. N., and K. V. Gavrilov. "Optimizing parameters of complexly loaded friction bearings." Journal of Machinery Manufacture and Reliability 36, no. 5 (October 2007): 461–66. http://dx.doi.org/10.3103/s1052618807050135.

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de la Garza-Gutiérrez, H., J. P. Muñoz-Mendoza, O. Chimal-Valencia, Roberto Martínez-Sánchez, S. D. De la Torre, A. García-Luna, and Perla E. García. "Optimizing Milling Parameters for Refining Portland Cement." Journal of Metastable and Nanocrystalline Materials 15-16 (April 2003): 395–400. http://dx.doi.org/10.4028/www.scientific.net/jmnm.15-16.395.

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Troche, C. J., A. W. Anderson, and J. C. Gore. "Optimizing MR-parameters for functional brain experiments." NeuroImage 3, no. 3 (June 1996): S40. http://dx.doi.org/10.1016/s1053-8119(96)80042-5.

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16

Park, S.-T., and T.-T. Luu. "Techniques for optimizing parameters of negative stiffness." Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science 221, no. 5 (May 1, 2007): 505–10. http://dx.doi.org/10.1243/0954406jmes390.

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Passive isolation systems based on springs are often used to resist vibration due to their low cost and reliability. The basic principle of these systems is that they try to decrease the natural frequency as low as possible. Stiffness of the overall spring system must be low to make the isolator achieve the low natural frequency. An approach to obtain the low dynamic stiffness is the combination of a negative stiffness system and a common isolator. There are, however, a lot of negative stiffness systems, and selecting the best one is difficult. In this paper, mathematical analyses are used to determine the best system that is then applied to construct a vertical isolator of the anti-vibration table.

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17

Nazari, M., R. M. Behbahani, A. Goshtasbi, and M. Ghavipour. "Optimizing the Operating Parameters for DME Production." Energy Sources, Part A: Recovery, Utilization, and Environmental Effects 37, no. 7 (March 6, 2015): 766–74. http://dx.doi.org/10.1080/15567036.2011.590858.

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18

Hovden, G., and Nam Ling. "Optimizing facial animation parameters for MPEG-4." IEEE Transactions on Consumer Electronics 49, no. 4 (November 2003): 1354–59. http://dx.doi.org/10.1109/tce.2003.1261240.

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19

Tellinghuisen, Joel. "Optimizing Experimental Parameters in Isothermal Titration Calorimetry." Journal of Physical Chemistry B 109, no. 42 (October 2005): 20027–35. http://dx.doi.org/10.1021/jp053550y.

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20

Nakorchevskii, A. I. "Optimizing the parameters of soil heat accumulators." Thermal Engineering 55, no. 12 (December 2008): 1026–30. http://dx.doi.org/10.1134/s0040601508120070.

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21

Zhu, Mingde, Roberto Rodriguez, and Tim Wehr. "Optimizing separation parameters in capillary isoelectric focusing." Journal of Chromatography A 559, no. 1-2 (October 1991): 479–88. http://dx.doi.org/10.1016/0021-9673(91)80095-x.

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22

Potapov, V. D., and A. M. Luk'yanov. "Optimizing the parameters of adhesive-bonded joints." Strength of Materials 20, no. 4 (April 1988): 518–23. http://dx.doi.org/10.1007/bf01530866.

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23

Li, Lin Na, and Dong Wang Zhong. "Study on the Optimizing Parameters of Underwater Drilling Blasting." Applied Mechanics and Materials 193-194 (August 2012): 614–18. http://dx.doi.org/10.4028/www.scientific.net/amm.193-194.614.

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Optimizing design of parameters is essential for the underwater blasting. The key point of optimizing model is to reflect the relation of blasting parameters, rock fragmentation and operation cost. In this paper, the blasting optimization mathematical model is established, and the optimization of the blasting parameters is obtained using the complex method with computer. Calculation results show that the blasting parameters designed by the optimizing model make the engineering cost lowest.

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24

Al-Ahmari, A. M. A., and Javed Aalam. "Optimizing parameters of freeform surface reconstruction using CMM." Measurement 64 (March 2015): 17–28. http://dx.doi.org/10.1016/j.measurement.2014.12.031.

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25

Dong, H., Y. Liu, Y. Shen, and X. Wang. "Optimizing Machining Parameters of Compound Machining of Inconel718." Procedia CIRP 42 (2016): 51–56. http://dx.doi.org/10.1016/j.procir.2016.02.185.

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26

Wang, Qiao, Shi-Fa Wu, Xu-Feng Li, and Xiao-Gang Wang. "Optimizing bowtie structure parameters for specific incident light." Chinese Physics B 19, no. 11 (November 2010): 117304. http://dx.doi.org/10.1088/1674-1056/19/11/117304.

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27

van Leeuwen, F., A. N. Morgan, and D. L. Harrison. "Optimizing point-source parameters for scanning satellite surveys." Monthly Notices of the Royal Astronomical Society 398, no. 4 (October 1, 2009): 2074–84. http://dx.doi.org/10.1111/j.1365-2966.2009.15253.x.

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28

Javadi-Dashcasan, M., F. Hajiesmaeilbaigi, H. Razzaghi, M. Mahdizadeh, and M. Moghadam. "Optimizing the Yb:YAG thin disc laser design parameters." Optics Communications 281, no. 18 (September 2008): 4753–57. http://dx.doi.org/10.1016/j.optcom.2008.05.055.

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29

Rigie, D. S., and P. J. La Rivière. "Optimizing spectral CT parameters for material classification tasks." Physics in Medicine and Biology 61, no. 12 (May 26, 2016): 4599–622. http://dx.doi.org/10.1088/0031-9155/61/12/4599.

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30

Šišak, Dubravka, Christian Baerlocher, Lynne B. McCusker, and Christopher J. Gilmore. "Optimizing the input parameters for powder charge flipping." Journal of Applied Crystallography 45, no. 6 (November 15, 2012): 1125–35. http://dx.doi.org/10.1107/s0021889812040411.

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Over the past few years, the powder charge-flipping algorithm has proved to be a useful one for structure solution from powder diffraction data, so a semi-systematic study of the effect of the different input parameters on its success has been performed. Two data sets were studied in these tests: a zirconium phosphate framework material and D-ribose. TheSuperflipinput parameters tested were the reflection overlap factor, the intensity repartitioning frequency, the isotropic displacement parameter, the threshold for charge flipping and the number of cycles/runs. By varying the values of these parameters within sensible ranges, an optimized set could be found for the zirconium phosphate case, but no combination of parameters allowed the D-ribose structure to be solved. Reasoning that starting with nonrandom phases might help, an approximate (but incorrect) structure was generated using the direct-space global-optimization method implemented in the programFOX. This structure was then used to calculate initial phase sets forSuperflipby allowing the calculated phases to vary in a random fashion by a user-defined percentage. With such phases and reoptimized input parameters, some fully interpretable solutions with the correct symmetry could be produced, even with fairly low resolution data. Unfortunately, it was not possible to recognize these solutions using theSuperflip Rvalues, so other criteria were sought. Both cluster analyses and maximum entropy calculations of the solutions were performed, and the latter, in particular, look very promising. A set of guidelines derived from these two structures could be applied successfully to a further two inorganic and seven organic structures.

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31

Bärring, Hans K., Hans F. M. Boelens, Onno E. De Noord, and Age K. Smilde. "Optimizing Meta-Parameters in Continuous Piecewise Direct Standardization." Applied Spectroscopy 55, no. 4 (April 2001): 458–66. http://dx.doi.org/10.1366/0003702011951975.

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32

Holland, Matthew, Tianqi Wang, Bulent Tavli, Alireza Seyedi, and Wendi Heinzelman. "Optimizing physical-layer parameters for wireless sensor networks." ACM Transactions on Sensor Networks 7, no. 4 (February 2011): 1–20. http://dx.doi.org/10.1145/1921621.1921622.

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33

Gee, S., B. Johnson, and A. L. Smith. "Optimizing electrospinning parameters for piezoelectric PVDF nanofiber membranes." Journal of Membrane Science 563 (October 2018): 804–12. http://dx.doi.org/10.1016/j.memsci.2018.06.050.

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34

Daneshjou, K., and M. Ahmadi. "OPTIMIZING THE EFFECTIVE PARAMETERS OF TUNGSTEN – COPPER COMPOSITES." Transactions of the Canadian Society for Mechanical Engineering 30, no. 3 (September 2006): 321–28. http://dx.doi.org/10.1139/tcsme-2006-0020.

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35

Severijns, C. A., and W. Hazeleger. "Optimizing Parameters in an Atmospheric General Circulation Model." Journal of Climate 18, no. 17 (September 1, 2005): 3527–35. http://dx.doi.org/10.1175/jcli3430.1.

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Abstract An efficient method to optimize the parameter values of the subgrid parameterizations of an atmospheric general circulation model is described. The method is based on the downhill simplex minimization of a cost function computed from the difference between simulated and observed fields. It is used to find optimal values of the radiation and cloud-related parameters. The model error is reduced significantly within a limited number of iterations (about 250) of short integrations (5 yr). The method appears to be robust and finds the global minimum of the cost function. The radiation budget of the model improves considerably without violating the already well simulated general circulation. Different aspects of the general circulation, such as the Hadley and Walker cells improve, although they are not incorporated into the cost function. It is concluded that the method can be used to efficiently determine optimal parameters for general circulation models even when the model behavior has a strong nonlinear dependence on these parameters.

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36

Mane, P., K. Mossi, and C. Green. "Optimizing energy harvesting parameters using response surface methodology." IEEE Transactions on Ultrasonics, Ferroelectrics and Frequency Control 56, no. 3 (March 2009): 429–36. http://dx.doi.org/10.1109/tuffc.2009.1061.

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37

Bhojani, Naeem, and James E. Lingeman. "Shockwave Lithotripsy–New Concepts and Optimizing Treatment Parameters." Urologic Clinics of North America 40, no. 1 (February 2013): 59–66. http://dx.doi.org/10.1016/j.ucl.2012.09.001.

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38

Machida, Haruhiko, Toshiyuki Yuhara, Takako Mori, Eiko Ueno, Yoshio Moribe, and John M. Sabol. "Optimizing Parameters for Flat-Panel Detector Digital Tomosynthesis." RadioGraphics 30, no. 2 (March 2010): 549–62. http://dx.doi.org/10.1148/rg.302095097.

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39

Šišak, D., C. Baerlocher, and L. B. McCusker. "Optimizing the input parameters for powder charge flipping." Acta Crystallographica Section A Foundations of Crystallography 67, a1 (August 22, 2011): C798. http://dx.doi.org/10.1107/s0108767311079773.

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40

Pakhomov, G. V., I. N. Safronich, D. L. Dorofeev, and B. A. Zon. "Optimizing the parameters of a four-detector polarimeter." Journal of Optical Technology 70, no. 3 (March 1, 2003): 166. http://dx.doi.org/10.1364/jot.70.000166.

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41

Pena, A. E., F. D. Anania, and C. Mohora. "Methodology for optimizing cutting parameters on milling process." IOP Conference Series: Materials Science and Engineering 400 (September 18, 2018): 022044. http://dx.doi.org/10.1088/1757-899x/400/2/022044.

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42

Bueno, P., R. Tapias, F. López, and M. J. Díaz. "Optimizing composting parameters for nitrogen conservation in composting." Bioresource Technology 99, no. 11 (July 2008): 5069–77. http://dx.doi.org/10.1016/j.biortech.2007.08.087.

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43

Polikarpov, M. I., V. I. Kolchkov, Yu A. Tetenev, and A. E. Daniloytsev. "Optimizing the precision parameters of welded butt joints." Chemical and Petroleum Engineering 25, no. 3 (March 1989): 150–53. http://dx.doi.org/10.1007/bf01229487.

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44

Ershov, S. I., V. S. Mel’nitskii, and A. M. Freidin. "Optimizing the parameters of a system of workings." Soviet Mining Science 26, no. 1 (January 1990): 47–55. http://dx.doi.org/10.1007/bf02499765.

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45

Chang-jiang, Zhang, Lu Shu, and Xu Peng-geng. "The optimizing research about radar absorbent material parameters." Wuhan University Journal of Natural Sciences 4, no. 4 (December 1999): 445–48. http://dx.doi.org/10.1007/bf02832279.

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46

Moustafa, Tamer, Waleed Khalifa, M. Raafat El-Koussy, and Nahed Abd El-Reheem. "Optimizing the Welding Parameters of Reinforcing Steel Bars." Arabian Journal for Science and Engineering 41, no. 5 (October 31, 2015): 1699–711. http://dx.doi.org/10.1007/s13369-015-1929-x.

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47

Rizzino, Angie, and Eric Ruff. "Parameters for optimizing detection of transforming growth factors." Journal of Tissue Culture Methods 10, no. 2 (June 1986): 109–15. http://dx.doi.org/10.1007/bf01404601.

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48

Nair, Arun U., David G. Taggart, and Frederick J. Vetter. "Optimizing cardiac material parameters with a genetic algorithm." Journal of Biomechanics 40, no. 7 (January 2007): 1646–50. http://dx.doi.org/10.1016/j.jbiomech.2006.07.018.

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49

Carolin Mabel, M., D. Suja Darling, and D. Jeraldin Auxilia. "Optimizing wind turbine parameters to enhance power generation." Journal of Renewable and Sustainable Energy 10, no. 1 (January 2018): 013303. http://dx.doi.org/10.1063/1.5020041.

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50

Muttaqi, K. M., An D. T. Le, J. Aghaei, E. Mahboubi-Moghaddam, M. Negnevitsky, and G. Ledwich. "Optimizing distributed generation parameters through economic feasibility assessment." Applied Energy 165 (March 2016): 893–903. http://dx.doi.org/10.1016/j.apenergy.2016.01.006.

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Journal articles on the topic 'Optimizing parameters'

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