Open Access
ITM Web Conf.
Volume 11, 2017
2017 International Conference on Information Science and Technology (IST 2017)
Article Number 01005
Number of page(s) 8
Section Session I: Computational Intelligence
Published online 23 May 2017
  1. Yan Jian-ying, Huang Ke-hua, Liu Qing-min, Huang Xiao-yan, Xu Rong-li. Study on risk factors of high risk postpartum hemorrhage and its clinical value [J].Chinese Journal of Practical Gynecology and Obstetrics, 2014,10: 791–797. [Google Scholar]
  2. David de la Mata-Moya; María Pilar Jarabo-Amores; Jaime Martín de Nicolás; Manuel Rosa-Zurera. Approximating the Neyman–Pearson detector with 2C-SVMs. Application to radar detection[J].Signal Processing. 2017:364–375. [Google Scholar]
  3. Hogan, Anna1;Sellar, Sam2;Lingard, Bob2.Commercialising comparison: Pearson puts the TLC in soft capitalism[J].Journal of Education Policy.2016,Vol.31(No.3):243–258. [CrossRef] [Google Scholar]
  4. Zhao, Sen1;Shojaie, Ali1.A significance test for graph-constrained estimation[J]. Biometrics.2016,Vol.72(No.2):484–493. [CrossRef] [MathSciNet] [Google Scholar]
  5. Adam Claridge-Chang1, 2, 3,;Pryseley N Assam4, 5,.Estimation statistics should replace significance testing.[J].Nat Methods.2016,Vol.13(No.2):108–109. [CrossRef] [Google Scholar]
  6. Milad Jajarmizadeh, Elham Kakaei Lafdani, Sobri Harun,Azadeh Ahmadi. Application of SVM and SWAT models for monthly streamflow prediction, a case study in South of Iran[J]. KSCE Journal of Civil Engineering,2015,191:. [Google Scholar]
  7. David de la Mata-Moya; María Pilar Jarabo-Amores; Jaime Martín de Nicolás; Manuel Rosa-Zurera.Approximating the Neyman–Pearson detector with 2C-SVMs. Application to radar detection[J].Signal Processing. 2017:364–375. [Google Scholar]
  8. Abbas M. Abd;Suhad M. Abd.Modelling the strength of lightweight foamed concrete using support vector machine (SVM)[J].Case Studies in Construction Materials. 2017:8–15. [Google Scholar]
  9. Aslahi-Shahri, B.1;Rahmani, R.2(; Chizari, M.3;Maralani, A.4;Eslami, M.5;Golkar, M.5;Ebrahimi, A.1.A hybrid method consisting of GA and SVM for intrusion detection system[J].Neural Computing and Applications.2016,Vol.27(No.6):1669–1676. [CrossRef] [Google Scholar]
  10. Nadeem,Mohammad1(;Banka,Haider1;Venugopal,R.2.SVM-Based Predictive Modelling of Wet Pelletization Using Experimental and GA-Based Synthetic Data[J].Arabian Journal for Science and Engineering.2016,Vol.41(No.3): 1053–1065. [CrossRef] [Google Scholar]
  11. Francesco Di Tria;Ezio Lefons;Filippo Tangorra.Cost-benefit analysis of data warehouse design methodologies[J].Information Systems.2017: 47–62. [Google Scholar]
  12. Yan-Qing Zhang;Nian-Sheng Tang.Bayesian local influence analysis of general estimating equations with nonignorable missing data[J].Computational Statistics and Data Analysis.2017: 184–200. [Google Scholar]
  13. Shirong Denga;Kin-yat Liub;Xingqiu Zhaobc.Semiparametric regression analysis of multivariate longitudinal data with informative observation times[J].Computational Statistics and Data Analysis.2017: 120–130. [Google Scholar]
  14. V. Bhanu Prasada; Supriya Mallicka; Ashish Dutt Upadhyayb; G.K. Ratha. Systematic review and individual patient data analysis of pediatric head and neck squamous cell carcinoma: An analysis of 217 cases[J].International Journal of Pediatric Otorhinolaryngology.2017: 75–81. [Google Scholar]
  15. G.S. Vyasa(Assistant Professor);K.N. Jhab(Associate Professor).Benchmarking green building attributes to achieve cost effectiveness using a data envelopment analysis[J].Sustainable Cities and Society.2017: 127–134. [Google Scholar]
  16. Shu-yi Guo;Qi Si.Mechanical hydraulic characteristic analysis scheme based on lightweight crowd data in mobile embedded devices[J].EURASIP Journal on Embedded Systems.2017,Vol.2017(No.1) [Google Scholar]

Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.

Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.

Initial download of the metrics may take a while.