Artykuły w czasopismach na temat „Roughness prediction”
Utwórz poprawne odniesienie w stylach APA, MLA, Chicago, Harvard i wielu innych
Sprawdź 50 najlepszych artykułów w czasopismach naukowych na temat „Roughness prediction”.
Przycisk „Dodaj do bibliografii” jest dostępny obok każdej pracy w bibliografii. Użyj go – a my automatycznie utworzymy odniesienie bibliograficzne do wybranej pracy w stylu cytowania, którego potrzebujesz: APA, MLA, Harvard, Chicago, Vancouver itp.
Możesz również pobrać pełny tekst publikacji naukowej w formacie „.pdf” i przeczytać adnotację do pracy online, jeśli odpowiednie parametry są dostępne w metadanych.
Przeglądaj artykuły w czasopismach z różnych dziedzin i twórz odpowiednie bibliografie.
Nalbant, Muammer, Hasan Gokkaya i İhsan Toktaş. "Comparison of Regression and Artificial Neural Network Models for Surface Roughness Prediction with the Cutting Parameters in CNC Turning". Modelling and Simulation in Engineering 2007 (2007): 1–14. http://dx.doi.org/10.1155/2007/92717.
Pełny tekst źródłaLin, Wan-Ju, Shih-Hsuan Lo, Hong-Tsu Young i Che-Lun Hung. "Evaluation of Deep Learning Neural Networks for Surface Roughness Prediction Using Vibration Signal Analysis". Applied Sciences 9, nr 7 (8.04.2019): 1462. http://dx.doi.org/10.3390/app9071462.
Pełny tekst źródłaSaleh, A., D. W. Fryrear i J. D. Bilbro. "AERODYNAMIC ROUGHNESS PREDICTION FROM SOIL SURFACE ROUGHNESS MEASUREMENT". Soil Science 162, nr 3 (marzec 1997): 205–10. http://dx.doi.org/10.1097/00010694-199703000-00006.
Pełny tekst źródłaCai, Xiao Jiang, Z. Q. Liu, Q. C. Wang, Shu Han, Qing Long An i Ming Chen. "Surface Roughness Prediction in Turning of Free Machining Steel 1215 by Artificial Neural Network". Advanced Materials Research 188 (marzec 2011): 535–41. http://dx.doi.org/10.4028/www.scientific.net/amr.188.535.
Pełny tekst źródłaLi, Shilong, Xiaolei Yang i Yu Lv. "Predictive capability of the logarithmic law for roughness-modeled large-eddy simulation of turbulent channel flows with rough walls". Physics of Fluids 34, nr 8 (sierpień 2022): 085112. http://dx.doi.org/10.1063/5.0098611.
Pełny tekst źródłaAlajmi, Mahdi S., i Abdullah M. Almeshal. "Prediction and Optimization of Surface Roughness in a Turning Process Using the ANFIS-QPSO Method". Materials 13, nr 13 (4.07.2020): 2986. http://dx.doi.org/10.3390/ma13132986.
Pełny tekst źródłaZeng, Shi, i Dechang Pi. "Milling Surface Roughness Prediction Based on Physics-Informed Machine Learning". Sensors 23, nr 10 (22.05.2023): 4969. http://dx.doi.org/10.3390/s23104969.
Pełny tekst źródłaNg, J. J., Z. W. Zhong i T. I. Liu. "Prediction of Roughness Heights of Milled Surfaces for Product Quality Prediction and Tool Condition Monitoring". Journal of Materials and Applications 8, nr 2 (15.11.2019): 97–104. http://dx.doi.org/10.32732/jma.2019.8.2.97.
Pełny tekst źródłaZhang, Qi, Yuechao Pei, Yixin Shen, Xiaojun Wang, Jingqi Lai i Maohui Wang. "A New Perspective on Predicting Roughness of Discontinuity from Fractal Dimension D of Outcrops". Fractal and Fractional 7, nr 7 (22.06.2023): 496. http://dx.doi.org/10.3390/fractalfract7070496.
Pełny tekst źródłaGu, Jiali, i Pingxiang Cao. "Prediction of straight tooth milling of Scots pine wood by shank cutter based on neural net computations and regression analysis". BioResources 17, nr 2 (4.02.2022): 2003–19. http://dx.doi.org/10.15376/biores.17.2.2003-2019.
Pełny tekst źródłaAlam, S., A. K. M. Nurul Amin, Anayet Ullah Patwari i Mohamed Konneh. "Prediction and Investigation of Surface Response in High Speed End Milling of Ti-6Al-4V and Optimization by Genetic Algorithm". Advanced Materials Research 83-86 (grudzień 2009): 1009–15. http://dx.doi.org/10.4028/www.scientific.net/amr.83-86.1009.
Pełny tekst źródłaLin, Yung-Chih, Kung-Da Wu, Wei-Cheng Shih, Pao-Kai Hsu i Jui-Pin Hung. "Prediction of Surface Roughness Based on Cutting Parameters and Machining Vibration in End Milling Using Regression Method and Artificial Neural Network". Applied Sciences 10, nr 11 (5.06.2020): 3941. http://dx.doi.org/10.3390/app10113941.
Pełny tekst źródłaMirifar, Siamak, Mohammadali Kadivar i Bahman Azarhoushang. "First Steps through Intelligent Grinding Using Machine Learning via Integrated Acoustic Emission Sensors". Journal of Manufacturing and Materials Processing 4, nr 2 (25.04.2020): 35. http://dx.doi.org/10.3390/jmmp4020035.
Pełny tekst źródłaSun, Hao, Chaochao Zhang, Yikai Li, Tingting Yin, Hanming Zhang i Jin Pu. "Study on prediction model of surface roughness of SiCp/Al composites based on Neural Network". Journal of Physics: Conference Series 2174, nr 1 (1.01.2022): 012091. http://dx.doi.org/10.1088/1742-6596/2174/1/012091.
Pełny tekst źródłaYang, Ching Been, Chyn Shu Deng i Hsiu Lu Chiang. "The Establishment of a Prediction Model for Surface Roughness in Ultrasonic-Assisted Turning". Applied Mechanics and Materials 120 (październik 2011): 119–25. http://dx.doi.org/10.4028/www.scientific.net/amm.120.119.
Pełny tekst źródłaLi, Qinghua, Chunlu Ma, Chunyu Wang, Zhengxi Lu i Shihong Zhang. "Application of Combined Prediction Model in Surface Roughness Prediction". Journal of Nanoelectronics and Optoelectronics 17, nr 11 (1.11.2022): 1511–16. http://dx.doi.org/10.1166/jno.2022.3335.
Pełny tekst źródłaDing, Ning, Chang Long Zhao, Xi Chun Luo, Qing Hua Li i Yao Chen Shi. "An Intelligent Prediction of Surface Roughness on Precision Grinding". Solid State Phenomena 261 (sierpień 2017): 221–25. http://dx.doi.org/10.4028/www.scientific.net/ssp.261.221.
Pełny tekst źródłaLu, Xiaohong, Xiaochen Hu, Hua Wang, Likun Si, Yongyun Liu i Lusi Gao. "Research on the prediction model of micro-milling surface roughness of Inconel718 based on SVM". Industrial Lubrication and Tribology 68, nr 2 (14.03.2016): 206–11. http://dx.doi.org/10.1108/ilt-06-2015-0079.
Pełny tekst źródłaZhang, Wenhe. "Surface Roughness Prediction with Machine Learning". Journal of Physics: Conference Series 1856, nr 1 (1.04.2021): 012040. http://dx.doi.org/10.1088/1742-6596/1856/1/012040.
Pełny tekst źródłaAhmed, Siddig E., i Mohammed B. Saad. "Prediction of Natural Channel Hydraulic Roughness". Journal of Irrigation and Drainage Engineering 118, nr 4 (lipiec 1992): 632–39. http://dx.doi.org/10.1061/(asce)0733-9437(1992)118:4(632).
Pełny tekst źródłaDenkena, B., A. Abrão, A. Krödel i K. Meyer. "Analytic roughness prediction by deep rolling". Production Engineering 14, nr 3 (30.04.2020): 345–54. http://dx.doi.org/10.1007/s11740-020-00961-0.
Pełny tekst źródłaUkar, E., A. Lamikiz, S. Martínez, I. Tabernero i L. N. López de Lacalle. "Roughness prediction on laser polished surfaces". Journal of Materials Processing Technology 212, nr 6 (czerwiec 2012): 1305–13. http://dx.doi.org/10.1016/j.jmatprotec.2012.01.007.
Pełny tekst źródłaZhang, Qing, Song Zhang, Jia Man i Bin Zhao. "Effect Analysis and ANN Prediction of Surface Roughness in End Milling AISI H13 Steel". Materials Science Forum 800-801 (lipiec 2014): 590–95. http://dx.doi.org/10.4028/www.scientific.net/msf.800-801.590.
Pełny tekst źródłaKim, Dong Woo, Young Jae Shin, Kyoung Taik Park, Eung Sug Lee, Jong Hyun Lee i Myeong Woo Cho. "Prediction of Surface Roughness in High Speed Milling Process Using the Artificial Neural Networks". Key Engineering Materials 364-366 (grudzień 2007): 713–18. http://dx.doi.org/10.4028/www.scientific.net/kem.364-366.713.
Pełny tekst źródłaNajm, Sherwan Mohammed, i Imre Paniti. "Predict the Effects of Forming Tool Characteristics on Surface Roughness of Aluminum Foil Components Formed by SPIF Using ANN and SVR". International Journal of Precision Engineering and Manufacturing 22, nr 1 (13.11.2020): 13–26. http://dx.doi.org/10.1007/s12541-020-00434-5.
Pełny tekst źródłaHerwan, Jonny, Seisuke Kano, Oleg Ryabov, Hiroyuki Sawada, Nagayoshi Kasashima i Takashi Misaka. "Predicting Surface Roughness of Dry Cut Grey Cast Iron Based on Cutting Parameters and Vibration Signals from Different Sensor Positions in CNC Turning". International Journal of Automation Technology 14, nr 2 (5.03.2020): 217–28. http://dx.doi.org/10.20965/ijat.2020.p0217.
Pełny tekst źródłaChen, Yuan Ling, Bao Lei Zhang, Wei Ren Long i Hua Xu. "Research on Surface Roughness Prediction Model for High-Speed Milling Inclined Plane of Hardened Steel". Advanced Materials Research 97-101 (marzec 2010): 2044–48. http://dx.doi.org/10.4028/www.scientific.net/amr.97-101.2044.
Pełny tekst źródłaZhang, Ming, X. Q. Yang i Bo Zhao. "On-Line Prediction Model of Ultrasonic Polishing Surface Roughness". Key Engineering Materials 455 (grudzień 2010): 539–43. http://dx.doi.org/10.4028/www.scientific.net/kem.455.539.
Pełny tekst źródłaHweju, Zvikomborero, Fundiswa Kopi i Khaled Abou-El-Hossein. "Statistical evaluation of PMMA surface roughness". Journal of Physics: Conference Series 2313, nr 1 (1.07.2022): 012030. http://dx.doi.org/10.1088/1742-6596/2313/1/012030.
Pełny tekst źródłaLiu, Xubao, Yuhang Pan, Ying Yan, Yonghao Wang i Ping Zhou. "Adaptive BP Network Prediction Method for Ground Surface Roughness with High-Dimensional Parameters". Mathematics 10, nr 15 (5.08.2022): 2788. http://dx.doi.org/10.3390/math10152788.
Pełny tekst źródłaVencovský, Václav. "Roughness Prediction Based on a Model of Cochlear Hydrodynamics". Archives of Acoustics 41, nr 2 (1.06.2016): 189–201. http://dx.doi.org/10.1515/aoa-2016-0019.
Pełny tekst źródłaHu, Jin Ping, Yan Li i Jing Chong Zhang. "Surface Roughness Prediction of High Speed Milling Based on Back Propagation Artificial Neural Network". Advanced Materials Research 201-203 (luty 2011): 696–99. http://dx.doi.org/10.4028/www.scientific.net/amr.201-203.696.
Pełny tekst źródłaCheng, Rong Kai, Yun Huang i Yao Huang. "Experimental Research on the Predictive Model for Surface Roughness of Titanium Alloy in Abrasive Belt Grinding". Advanced Materials Research 716 (lipiec 2013): 443–48. http://dx.doi.org/10.4028/www.scientific.net/amr.716.443.
Pełny tekst źródłaDing, Ning, Long Shan Wang i Guang Fu Li. "Study of Intelligent Prediction Control of Surface Roughness in Grinding". Key Engineering Materials 329 (styczeń 2007): 93–98. http://dx.doi.org/10.4028/www.scientific.net/kem.329.93.
Pełny tekst źródłaWang, Jing He, Shen Dong, H. X. Wang, Ming Jun Chen, Wen Jun Zong i L. J. Zhang. "Forecasting of Surface Roughness and Cutting Force in Single Point Diamond Turning for KDP Crystal". Key Engineering Materials 339 (maj 2007): 78–83. http://dx.doi.org/10.4028/www.scientific.net/kem.339.78.
Pełny tekst źródłaWu, Tian-Yau, i Chi-Chen Lin. "Optimization of Machining Parameters in Milling Process of Inconel 718 under Surface Roughness Constraints". Applied Sciences 11, nr 5 (28.02.2021): 2137. http://dx.doi.org/10.3390/app11052137.
Pełny tekst źródłaYU, J., Y. NAMBA i M. SHIOKAWA. "FRACTAL ROUGHNESS CHARACTERIZATION OF SUPER-GROUND Mn-Zn FERRITE SINGLE CRYSTALS". Fractals 04, nr 02 (czerwiec 1996): 205–11. http://dx.doi.org/10.1142/s0218348x96000285.
Pełny tekst źródłaGuo, Xiong Hua, Mao Fu Liu i Chang Rong Zhao. "Surface Roughness Prediction in Precision Surface Grinding of Nano-Ceramic Coating Based on Improved ANFIS". Applied Mechanics and Materials 44-47 (grudzień 2010): 2293–98. http://dx.doi.org/10.4028/www.scientific.net/amm.44-47.2293.
Pełny tekst źródłaVidakis, Nectarios, Markos Petousis, Nikolaos Vaxevanidis i John Kechagias. "Surface Roughness Investigation of Poly-Jet 3D Printing". Mathematics 8, nr 10 (13.10.2020): 1758. http://dx.doi.org/10.3390/math8101758.
Pełny tekst źródłaTangjitsitcharoen, Somkiat, i Angsumalin Senjuntichai. "Intelligent Monitoring and Prediction of Surface Roughness in Ball-End Milling Process". Applied Mechanics and Materials 121-126 (październik 2011): 2059–63. http://dx.doi.org/10.4028/www.scientific.net/amm.121-126.2059.
Pełny tekst źródłaHuiping, Zhang, Zhang Hongxia i Lai Yinan. "Surface Roughness and Residual Stresses of High Speed Turning 300 M Ultrahigh Strength Steel". Advances in Mechanical Engineering 6 (1.01.2014): 859207. http://dx.doi.org/10.1155/2014/859207.
Pełny tekst źródłaWang, Yahui, Yiwei Wang, Lianyu Zheng i Jian Zhou. "Online Surface Roughness Prediction for Assembly Interfaces of Vertical Tail Integrating Tool Wear under Variable Cutting Parameters". Sensors 22, nr 5 (3.03.2022): 1991. http://dx.doi.org/10.3390/s22051991.
Pełny tekst źródłaDing, Ning, Yi Chen Wang, Ding Tong Zhang, Yu Xiang Shi i Jian Shi. "Surface Roughness Prediction Model of Cylinder Grinding". Applied Mechanics and Materials 157-158 (luty 2012): 123–26. http://dx.doi.org/10.4028/www.scientific.net/amm.157-158.123.
Pełny tekst źródłaCebeci, Tuncer, i David A. Egan. "Prediction of transition due to isolated roughness". AIAA Journal 27, nr 7 (lipiec 1989): 870–75. http://dx.doi.org/10.2514/3.10194.
Pełny tekst źródłaKong, Dongdong, Junjiang Zhu, Chaoqun Duan, Lixin Lu i Dongxing Chen. "Bayesian linear regression for surface roughness prediction". Mechanical Systems and Signal Processing 142 (sierpień 2020): 106770. http://dx.doi.org/10.1016/j.ymssp.2020.106770.
Pełny tekst źródłaGrzenda, Maciej, i Andres Bustillo. "The evolutionary development of roughness prediction models". Applied Soft Computing 13, nr 5 (maj 2013): 2913–22. http://dx.doi.org/10.1016/j.asoc.2012.03.070.
Pełny tekst źródłaReddy, B. Sidda, G. Padmanabha i K. Vijay Kumar Reddy. "Surface Roughness Prediction Techniques for CNC Turning". Asian Journal of Scientific Research 1, nr 3 (15.04.2008): 256–64. http://dx.doi.org/10.3923/ajsr.2008.256.264.
Pełny tekst źródłaJesuthanam, C. P., S. Kumanan i P. Asokan. "SURFACE ROUGHNESS PREDICTION USING HYBRID NEURAL NETWORKS". Machining Science and Technology 11, nr 2 (29.05.2007): 271–86. http://dx.doi.org/10.1080/10910340701340141.
Pełny tekst źródłaSingh, Sanjay Kumar, K. Srinivasan i D. Chakraborty. "Acoustic characterization and prediction of surface roughness". Journal of Materials Processing Technology 152, nr 2 (październik 2004): 127–30. http://dx.doi.org/10.1016/j.jmatprotec.2004.03.023.
Pełny tekst źródłaBrezocnik, M., M. Kovacic i M. Ficko. "Prediction of surface roughness with genetic programming". Journal of Materials Processing Technology 157-158 (grudzień 2004): 28–36. http://dx.doi.org/10.1016/j.jmatprotec.2004.09.004.
Pełny tekst źródła