Prediction of the Production Rate of Chain Saw Machine using the Multilayer Perceptron (MLP) Neural Network
The production rate in rock cutting machines is one of the most influential parameters in designing and planning procedures. Complete understanding of the production rate of cutting machines help experts and owners of this industry to predict the production expenses. Therefore, the present study predicts the production rate of the chain saw machine in dimensional stone quarries. In this research, the method of artificial neural networks was used for modeling and predicting the production rate. In addition, in this modeling, 98 data were collected from the results obtained from field studies on 7 carbonate rock samples as the dataset. Four important parameters, including uniaxial compressive strength (UCS), Los Angeles abrasion (LAA) Test, equivalent quartz content (Qs), and Schmidt Hammer (Sch) were considered as input data and the production rate was considered as the output data. The model was evaluated by the performance indices for artificial neural networks, including the value account for (VAF), root mean square error (RMSE), and coefficient of determination (R2). For simulation, 10 models were created and evaluated. Finally, the best model, i.e. model No. 3, was selected with a 4 × 3 × 1 structure, including 4 input neurons, 3 neurons in the hidden layer and 1 output neuron. The results obtained from the model’s performance indices show that a very appropriate prediction has been done for determining the production rate of the chain saw machine by artificial neural networks.
Careddu, Nicola, Elisa Stefania Perra, and Orietta Masala. "Diamond wire sawing in ornamental basalt quarries: technical, economic and environmental considerations." Bulletin of Engineering Geology and the Environment (2017): 1-12. https://doi.org/10.1007/s10064-017-1112-6.
Careddu, Nicola, Giampaolo Siotto, and Graziella Marras. "The crisis of granite and the success of marble: errors and market strategies. The Sardinian case." Resources Policy 52 (2017): 273-276. https://doi.org/10.1016/j.resourpol.2017.03.010.
Tumac, D., E. Avunduk, H. Copur, N. Bilgin, and C. Balci. "Estimation of the performance of chain saw machines from shore hardness and the other mechanical properties." Dynamic Web Programming and HTML5 (2012): 261.
Mikaeil, Reza, Sina Shaffiee Haghshenas, Sami Shaffiee Haghshenas, and Mohammad Ataei. "Performance prediction of circular saw machine using imperialist competitive algorithm and fuzzy clustering technique." Neural Computing and Applications 29, no. 6 (2018): 283-292. https://doi.org/10.1007/s00521-016-2557-4.
Tumac, Deniz. "Artificial neural network application to predict the sawability performance of large diameter circular saws." Measurement 80 (2016): 12-20. https://doi.org/10.1016/j.measurement.2015.11.025.
Mikaeil, Reza, Yilmaz Ozcelik, Mohammad Ataei, and Sina Shaffiee Haghshenas. "Application of harmony search algorithm to evaluate performance of diamond wire saw." Journal of Mining and Environment (2016). DOI: 10.22044/JME.2016.723.
Korman, Tomislav, Trpimir Kujundžić, Hrvoje Lukačić, and Milan Martinić. "The Impact of Area and Shape of Tool Cut on Chain Saw Performance." Rudarsko-geološko-naftni zbornik 31, no. 3 (2016): 1-13.
Almasi, S. Najmedin, Raheb Bagherpour, Reza Mikaeil, and Yilmaz Ozcelik. "Developing a new rock classification based on the abrasiveness, hardness, and toughness of rocks and PA for the prediction of hard dimension stone sawability in quarrying." Geosystem Engineering 20, no. 6 (2017): 295-310. https://doi.org/10.1080/12269328.2017.1278727.
Yarahmadi, Reza, Raheb Bagherpour, Amir Khademian, Luis MO Sousa, Seied Najmedin Almasi, and Mahin Mansouri Esfahani. "Determining the optimum cutting direction in granite quarries through experimental studies: a case study of a granite quarry." Bulletin of Engineering Geology and the Environment (2017): 1-9. https://doi.org/10.1007/s10064-017-1158-5.
Almasi, S. Najmedin, Raheb Bagherpour, Reza Mikaeil, Yilmaz Ozcelik, and Hamid Kalhori. "Predicting the Building Stone Cutting Rate Based on Rock Properties and Device Pullback Amperage in Quarries Using M5P Model Tree." Geotechnical and Geological Engineering 35, no. 4 (2017): 1311-1326. https://doi.org/10.1007/s10706-017-0177-0.
Mikaeil, Reza, Sina Shaffiee Haghshenas, Yilmaz Ozcelik, and Hojjat Hossinzadeh Gharehgheshlagh. "Performance Evaluation of Adaptive Neuro-Fuzzy Inference System and Group Method of Data Handling-Type Neural Network for Estimating Wear Rate of Diamond Wire Saw." Geotechnical and Geological Engineering: 1-13. https://doi.org/10.1007/s10706-018-0571-2.
Dormishi, Alireza, Mohammad Ataei, Reza Khaloo Kakaie, Reza Mikaeil, and Sina Shaffiee Haghshenas. "Performance evaluation of gang saw using hybrid ANFIS-DE and hybrid ANFIS-PSO algorithms." Journal of Mining and Environment (2018). DOI: 10.22044/JME.2018.6750.1496.
Romoli, L. "Cutting force monitoring of chain saw machines at the variation of the rake angle." International Journal of Rock Mechanics and Mining Sciences 101 (2018): 33-40. https://doi.org/10.1016/j.ijrmms.2017.11.011.
Brown, Edwin Thomas. "Rock characterization, testing & monitoring: ISRM suggested methods." (1981).
Rad, Mostafa Yousefi, Sina Shaffiee Haghshenas, Payam Rajabzade Kanafi, and Sami Shaffiee Haghshenas. "Analysis of Protection of Body Slope in the Rockfill Reservoir Dams on the Basis of Fuzzy Logic." In IJCCI, pp. 367-373. 2012.
Rad, Mostafa Yousefi, Sina Shaffiee Haghshenas, and S. S. Haghshenas. "Mechanostratigraphy of cretaceous rocks by fuzzy logic in East Arak, Iran." In The 4th International Workshop on Computer Science and Engineering-Summer, WCSE. 2014.
Mikaeil, Reza, Sina Shaffiee Haghshenas, and Seyed Hadi Hoseinie. "Rock penetrability classification using artificial bee colony (ABC) algorithm and self-organizing map." Geotechnical and Geological Engineering 36, no. 2 (2018): 1309-1318. https://doi.org/10.1007/s10706-017-0394-6.
Salemi, Akbar, Reza Mikaeil, and Sina Shaffiee Haghshenas. "Integration of finite difference method and genetic algorithm to seismic analysis of circular shallow tunnels (Case study: Tabriz urban railway tunnels)." KSCE Journal of Civil Engineering 22, no. 5 (2018): 1978-1990. https://doi.org/10.1007/s12205-017-2039-y.
Mikaeil, Reza, Sina Shaffiee Haghshenas, Yilmaz Ozcelik, and Sami Shaffiee Haghshenas. "Development of Intelligent Systems to Predict Diamond Wire Saw Performance." Soft Computing in Civil Engineering 1, no. 2 (2017): 52-69. DOI: 10.22115/SCCE.2017.49092.
Sonmez, H., C. Gokceoglu, H. A. Nefeslioglu, and A. Kayabasi. "Estimation of rock modulus: for intact rocks with an artificial neural network and for rock masses with a new empirical equation." International Journal of Rock Mechanics and Mining Sciences 43, no. 2 (2006): 224-235. https://doi.org/10.1016/j.ijrmms.2005.06.007.
Khandelwal, Manoj, and T. N. Singh. "Prediction of blast induced ground vibrations and frequency in opencast mine: a neural network approach." Journal of sound and vibration 289, no. 4-5 (2006): 711-725. https://doi.org/10.1016/j.jsv.2005.02.044.
Bahrami, J., M. R. Kavianpour, M. S. Abdi, A. Telvari, K. Abbaspour, and B. Rouzkhash. "A comparison between artificial neural network method and nonlinear regression method to estimate the missing hydrometric data." Journal of Hydroinformatics 13, no. 2 (2011): 245-254. DOI: 10.2166/hydro.2010.069.
Yagiz, S., E. A. Sezer, and C. Gokceoglu. "Artificial neural networks and nonlinear regression techniques to assess the influence of slake durability cycles on the prediction of uniaxial compressive strength and modulus of elasticity for carbonate rocks." International Journal for Numerical and Analytical Methods in Geomechanics 36, no. 14 (2012): 1636-1650. https://doi.org/10.1002/nag.1066.
Aryafar, Ahmad, Reza Mikaeil, Faramarz Doulati Ardejani, Sina Shaffiee Haghshenas, and Amir Jafarpour. "Application of non-linear regression and soft computing techniques for modeling process of pollutant adsorption from industrial wastewaters." Journal of Mining and Environment (2018). DOI: 10.22044/JME.2018.6511.1469.
Hecht-Nielsen, Robert. "Kolmogorov's mapping neural network existence theorem." In Proceedings of the international conference on Neural Networks, pp. 11-14. IEEE Press, 1987.
Kaastra, Iebeling, and Milton Boyd. "Designing a neural network for forecasting financial and economic time series." Neurocomputing 10, no. 3 (1996): 215-236. https://doi.org/10.1016/0925-2312(95)00039-9.
Kanellopoulos, I., and G. G. Wilkinson. "Strategies and best practice for neural network image classification." International Journal of Remote Sensing 18, no. 4 (1997): 711-725. https://doi.org/10.1080/014311697218719.
Ripley, Brian D. "Statistical aspects of neural networks." Networks and chaos—statistical and probabilistic aspects 50 (1993): 40-123.
Paola, J. D. "Neural network classification of multispectral imagery." Master Tezi, The University of Arizona, USA (1994).
Wang, Changfeng. "A theory of generalization in learning machines with neural network applications." (1994).
Masters, T., and M. Schwartz. "Practical neural network recipes in C." IEEE Transactions on Neural Networks 5, no. 5 (1994): 853-853.
Zorlu, K., C. Gokceoglu, F. Ocakoglu, H. A. Nefeslioglu, and S. Acikalin. "Prediction of uniaxial compressive strength of sandstones using petrography-based models." Engineering Geology 96, no. 3-4 (2008): 141-158.
- There are currently no refbacks.
Copyright (c) 2018 Javad Mohammadi, Mohammad Ataei, Reza Khalo Kakaei, Reza Mikaeil, sina shaffiee Haghshenas
This work is licensed under a Creative Commons Attribution 4.0 International License.