المؤلفون: TRUNG, TRAN DUC, TUAN, DAO ANH, HUONG, CHU DIEU

المساهمون: Technická univerzita v Liberci

مصطلحات موضوعية: Unevenness, Artificial neural network, Regression function, Predicting yarn unevenness, Winding

وصف الملف: text; 8 stran; application/pdf

العلاقة: Nguyen, C.H., Tran, L.H., Ho, K.N.: Application of neural network to predict the workability parameters of selfcompacting concrete. In: CIGOS 2019, Innovation for Sustainable Infrastructure. Lecture Notes in Civil Engineering, 54, 2020. https://doi.org/10.1007/978-981-15-0802-8_186Test; Doke S. and Shanmugam N.: Artificial Intelligence and its applications in textile, Asian Textile Journal, 49, 2002.; Malik, S., Farooq, A., Gereke, T. et al.: Prediction of blended yarn evenness and tensile properties by using artificial neural network and multiple linear regression, Autex Research Journal, 16(2), 2016, pp. 43-50. https://doi.org/10.1515/aut-2015-0018Test; Furferi R. and Gelli M.: Yarn strength prediction.: A practical model based on artificial neural networks, Advances in Mechanical Engineering, 2010, 640103. https://doi.org/10.1155/2010/640103Test; Haghighat E., Johari M.S., Etrati S.M., et al.: Study of the hairiness of polyester - viscose blended yarn: Part III - predicting yarn hairiness using an artificial neural networks, Fibres & Textiles in Eastern Europe, 20(1), 2012, pp. 33-38.; El-Geiheini A., Elkateb S., Abd-Elhamied M.R.: Yarn tensile properties modeling using Artificial Intelligence, Alexandria Engineering Journal, 59, 2020, pp. 4435-4440. https://doi.org/10.1016/j.aej.2020.07.049Test; Majumdar P.K., Majumdar A.: Predicting the breaking elongation of ring spun cotton yarns using mathematical, statistical, and artificial neural network models, Textile Research Journal, 74(7), 2004, pp. 652-655. https://doi.org/10.1177/004051750407400717Test; Islan MD. Z.: Effect of winding speed on yarn properties, Journal of Engineering Research and Application, 9(3), 2019, pp. 28 - 34.; Trung T.D., Huong Ch.D., Tuan D.A.: Research on new modeling of winding process for controlling yarn package pressure on grooved drum, In: Proceeding Aun/Seed-net joint regional conferences in transportation, energy and mechanical manufacturing engineering - RCTEMME 2021 pp. 162-168.; ASTM A1425/D1425M-14: Standard Test Method for Evenness of Textile Strands Using Capacitance Testing Equipment.; Trun T.D., Huong Ch.D., Tuan A.T.: Influence of some winding parameters on hairiness of yarn after winding process, Vlakna a textil, 29(4), 2022, pp. 29-37. https://doi.org/10.15240/tul/008/2022-4-004Test; Stjepanovič Z., Anton J.: Optimisation of cotton fibre blends using AI machine learning techniques, Department of Textiles, Faculty of Mechanical Engineering, University of Maribor, 2001.; Shanbeh M., Hasani H., and Tabatabaei S.A.: Modelling and predicting the breaking strength and mass irregularity of cotton rotor-spun yarns containing cotton fiber recovered from ginning process by using artificial neural network algorithm, Modelling and Simulation in Engineering, 2011, 591905. https://doi.org/10.1155/2011/591905Test; Ünal P.G., Özdil N., Taşkın C.: The effect of fiber properties on the characteristics of spliced yarns Part I: Prediction of spliced yarns tensile properties, Textile Research Journal, 80, 2010, pp. 429-438. https://doi.org/10.1177/0040517509342318Test; Beltran R., Wang L., Wang X.: Predicting worsted spinning performance with an artificial neural network model, Textile Research Journal, 74(9), 2004, pp. 757-763. https://doi.org/10.1177/004051750407400902Test; Fibres and Textiles; https://dspace.tul.cz/handle/15240/174544Test

الإتاحة: https://doi.org/10.15240/tul/008/2023-5-001Test
https://doi.org/10.1007/978-981-15-0802-8_186Test
https://doi.org/10.1515/aut-2015-0018Test
https://doi.org/10.1155/2010/640103Test
https://doi.org/10.1016/j.aej.2020.07.049Test
https://doi.org/10.1177/004051750407400717Test
https://doi.org/10.15240/tul/008/2022-4-004Test
https://doi.org/10.1155/2011/591905Test
https://doi.org/10.1177/0040517509342318Test
https://doi.org/10.1177/004051750407400902Test

المؤلفون: Bílková Diana

المصدر: ACC Journal, Vol 25, Iss 2, Pp 21-45 (2019)

مصطلحات موضوعية: Average annual wage, GDP per capita, Cluster analysis, Ward method, Euclidean distance metric, Linear regression hyperplane, Quadratic regression function, Science, Social Sciences

وصف الملف: electronic resource

العلاقة: https://acc-ern.tul.cz/archiv/PDF/ACC_2019_2_02.pdfTest; https://doaj.org/toc/1803-9782Test; https://doaj.org/toc/2571-0613Test

الوصول الحر: https://doaj.org/article/5066422f99324b5a9669af438e18f39aTest

المؤلفون: Zouharová, Daniela

مرشدي الرسالة: Špačková,, Romana, Doubravský, Karel

مصطلحات موضوعية: financial analysis, statistické metody, regression function, regresní funkce, finanční analýza, predikce, časové řady, time series, prediction, statistic methods

الإتاحة: http://www.nusl.cz/ntk/nusl-443124Test

المؤلفون: Shalaginova, Daria

مرشدي الرسالة: Novotná, Veronika, Doubravský, Karel

مصطلحات موضوعية: statistical methods, regresní analýza, statistické metody, regression function, korelační analýza, time series analysis, regresní funkce, analýza časových řad, regression analysis, financial indicators, finanční ukazatele, correlation analysis

الإتاحة: http://www.nusl.cz/ntk/nusl-414494Test

المؤلفون: Hofmanová, Aneta

مرشدي الرسالة: Michalíková, Eva, Doubravský, Karel

مصطلحات موضوعية: financial analysis, regression function, korelační analýza, time series analysis, regresní funkce, finanční analýza, predikce, prediction, analýza časových řad, correlation analysis

الإتاحة: http://www.nusl.cz/ntk/nusl-377969Test

المؤلفون: Ťoupal, Tomáš, Marek, Patrice

مصطلحات موضوعية: Neparametrické jádrové odhady, jádrová funkce, regresní funkce, podkladové aktivum, vyhlazovací parametr, Nonparametric kernel estimation, kernel function, regression function, underlying asset, smoothing parameter

وصف الملف: 8 s.; application/pdf

العلاقة: Managing and Modelling of Financial Risks, 8th International Scientific Conference - Proceedings; http://hdl.handle.net/11025/30440Test; 429179000037

الإتاحة: http://hdl.handle.net/11025/30440Test

المؤلفون: Turisová, Alena

مرشدي الرسالة: Novotná, Veronika, Doubravský, Karel

مصطلحات موضوعية: regresní analýza, test nezávislosti, regression function, korelační analýza, time series analysis, regresní funkce, test for independence, analýza časových řad, regression analysis, financial indicators, finanční ukazatele, correlation analysis

الإتاحة: http://www.nusl.cz/ntk/nusl-317063Test

المؤلفون: Machová, Hana

المساهمون: Doubravský, Karel, MSc,, Miroslav Hladký

مصطلحات موضوعية: finanční analýza, poměrové ukazatele, časové řady, regresní analýza, regresní funkce, korelační analýza, financial analysis, financial ratios, time series, regression analysis, regression function, correlation analysis

وصف الملف: application/pdf; text/html

العلاقة: MACHOVÁ, H. Posouzení ekonomické situace společnosti a návrhy na její zlepšení [online]. Brno: Vysoké učení technické v Brně. Fakulta podnikatelská. 2022.; 142599; http://hdl.handle.net/11012/205088Test

الإتاحة: http://hdl.handle.net/11012/205088Test

المؤلفون: Vyparinová, Marie

المساهمون: Michalíková, Eva, Fojtů,, Kateřina

المصدر: VYPARINOVÁ, M. Analýza ekonomických dat s využitím statistických metod [online]. Brno: Vysoké učení technické v Brně. Fakulta podnikatelská. 2022.

مصطلحات موضوعية: finanční analýza, statistické metody, časové řady, regresní funkce, prognóza, financial analysis, statistic methods, time lines, regression function, prognosis

وصف الملف: text/html

العلاقة: http://hdl.handle.net/11012/208034Test

الإتاحة: http://hdl.handle.net/11012/208034Test

المؤلفون: Kováč, Robin

المساهمون: Heckenbergerová, Jana

مصطلحات موضوعية: regrese, regresní funkce, logistická regrese, nelineární modely, lineární modely, odhad parametrů, regression, regression function, logistic regression, nonlinear models, linear models, parameter estimation

وصف الملف: 61 s.; application/pdf

العلاقة: https://hdl.handle.net/10195/78817Test; 39240

الإتاحة: https://hdl.handle.net/10195/78817Test