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48篇 您的检索式:作者名="Bahreini"
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1Prediction of roadheaders' performance using artificial neural network approaches (MLP and KOSFM)显示文摘Application of mechanical excavators is one of the most commonly used excavation methods because it can bring the project more productivity, accuracy and safety. Among the mechanical excavators, roadheaders are mechanical miners which have been extensively used in tunneling, mining and civil industries. Performance prediction is an important issue for successful roadheader application and generally deals with machine selection, production rate and bit consumption. The main aim of this research is to investigate the cutting performance(instantaneous cutting rates(ICRs)) of medium-duty roadheaders by using artificial neural network(ANN) approach. There are different categories for ANNs, but based on training algorithm there are two main kinds: supervised and unsupervised. The multi-layer perceptron(MLP) and Kohonen self-organizing feature map(KSOFM) are the most widely used neural networks for supervised and unsupervised ones, respectively. For gaining this goal, a database was primarily provided from roadheaders' performance and geomechanical characteristics of rock formations in tunnels and drift galleries in Tabas coal mine, the largest and the only fullymechanized coal mine in Iran. Then the database was analyzed in order to yield the most important factor for ICR by using relatively important factor in which Garson equation was utilized. The MLP network was trained by 3 input parameters including rock mass properties, rock quality designation(RQD), intact rock properties such as uniaxial compressive strength(UCS) and Brazilian tensile strength(BTS), and one output parameter(ICR). In order to have more validation on MLP outputs, KSOFM visualization was applied. The mean square error(MSE) and regression coefficient(R) of MLP were found to be 5.49 and 0.97, respectively. Moreover, KSOFM network has a map size of 8 5 and final quantization and topographic errors were 0.383 and 0.032, respectively. The results show that MLP neural networks have a strong capability to predict and evaluate the performance of medium-duty roadheaders in coal measure rocks. Furthermore, it is concluded that KSOFM neural network is an efficient way for understanding system behavior and knowledge extraction. Finally, it is indicated that UCS has more influence on ICR by applying the best trained MLP network weights in Garson equation which is also confirmed by KSOFM.Arash Ebrahimabadi Mohammad Azimipour Ali Bahreini 2015Journal of Rock Mechanics and Geotechnical Engineering2015,7,5:8
2Design and operation of a pressure-controlled inlet for airborne sampling with an aerodynamic aerosol lens显示文摘BAHREINI R DUNLEA E J MATTHEW B M 2008Aerosol Science and Technology2008,42,6:1
3Brown carbon and internal mixing in biomass burning particles显示文摘Daniel A. Lack Justin M. Langridge Roya Bahreini Christopher D. Cappa Ann M. Middlebrook Joshua P. Schwarz 2012Proceedings of the National Academy of Sciences2012,,37:1
4Serum paraoxo- nase phenotype distribution in exudative age - related macular de- generation and its relationship to homocysteine and oxidized low - density lipoprotein 显示文摘Javadzadeh A Ghorbanihaghjo A Bahreini 2012Retina2012,32,4:1
5Brown carbon and internal mixing in biomass burning particles显示文摘Daniel A. Lack Justin M. Langridge Roya Bahreini Christopher D. Cappa Ann M. Middlebrook Joshua P. Schwarz 2012Proceedings of the National Academy of Sciences2012,,37:1
6Hygroscopicity of secondary organic aerosols formed by oxida- tion of cycloalkenes, monoterpenes, sesquiterpenes, and related compounds显示文摘VARUTBANGKUL V BRECHTEL F J BAHREINI R 2006Atmospheric Chemistry and Physics2006,6,9:1
7Marine aerosol formation from biogenic iodine emissions显示文摘O’ Dowd C D Jimenez J L Bahreini R 2002Nature2002,417,6889:1
8Hygroscopicity of secondary organic aerosols formed by oxidation of cycloalkenes, monoterpenes, sesquiterpenes, and related compounds显示文摘Varutbangkul V. Brechtel F. J. Bahreini R. Ng N. L. Keywood M. D. Kroll J. H. Flagan R. C. Seinfeld J. H. Lee A. Goldstein A. H 2006Atmospheric Chemistry and Physics2006,,66:1
9Comparison of Head Nurses and Practicing Nurses in Nurse Competence Assessment显示文摘Bahreini M 2011Iran J Nurs Midwifery Res2011,16,3:1
10Marine aerosol formation from biogenic iodine emissions显示文摘O'dowd C D Jimenez J L Bahreini R 2002Nature2002,417,6889:1
11Hygroscopicityof secondary organic aerosols formed by oxidation of cycloalkenes,monoterpenes,sesquiterpenes,and related compounds 显示文摘Varutbangkul V Brechtel F J Bahreini R 2006Atmospheric Chemistry and Physics2006,6,9:1
12Evaluation of calotropis gigantea as a promising raw material for fiber - reinforced composite显示文摘Ashori A Bahreini Z 2009Journal of Composite Materials2009,43,11:1
13Comparison of head nurses and practicing nurses in nurse competence assessment 显示文摘Bahreini M Moattari M Ahmadi F 2011Iran J Nurs Midwifery Res2011,16,3:1
14Comparison of the clinical competence of nurses working in two university hospitals in Iran显示文摘Bahreini M Shahamat S Hayatdavoudi P 2011Nurs Health Sci2011,13,3:1
15Estimates of ge-netic parameters for growth traits in Kermani sheep显示文摘Bahreini M R Shahroudi F E van Vleck L D 2007Journalof Animal Breeding and Genetics2007,124,:1
16Effect of imipramine on the expression and acquisition of morphine-induced conditioned place preference in mice 显示文摘Zarrindast MR Bahreini T Adl M 2002Pharmacol Biochem Behav2002,73,4:1
17Characteristics, sources, and transport of aerosols measured in spring 2008 during the aerosol, radiation, and cloud processes affecting Arctic climate (ARCPAC) Project 显示文摘Brock C A Cozic J Bahreini R 2011Atmospheric Chemistry Physics2011,11,:1
18Marine aerosol formation from biogenic iodine emissions显示文摘O'DOWD C D JIMINEZ J L BAHREINI R 2002Nature2002,417,:1
19Evaluation of calotropis gigantea as a promising rawmaterial for fiber- reinforced composite 显示文摘Asbori A ( Ashor Alireza) Bahreini Z ( Bahreini Zak- er) 2009Jolzrnal of Composite Materials2009,43,11:1
20Marine aerosol formation from b!ogenic iodine emissions 显示文摘O'Dowd C D Jimenez J L Bahreini R 2002Nature2002,417,6889:1
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