RESEARCH PUBLICATIONS OF THE FACULTY MEMBER

NAME: Dr. Rana Aamir Raza
DESIGNATION: Assistant Professor
2018 Rana Aamir Raza Ashfaq:
Random Weight Network-based Fuzzy Nonlinear Regression For Trapezoidal Fuzzy Number Data. Applied Soft Computing (): Elsevier
(2018) [Journal Paper ]
Rana Aamir Raza Ashfaq Co-A:
Further Improvements On Extreme Learning Machine For Interval Neural Network. Neural Computing And Applications 29( 8):DOI: 10.1007/s00521-016-2727-4
(2018) [Journal Paper ]
Rana Aamir Raza Ashfaq - Co-Author:
An Initial Study On The Rank Of Input Matrix For Extreme Learning Machine. International Journal Of Machine Learning And Cybernetics · October 2016 9( 5):DOI: 10.1007/s13042-016-0615-y
(2018) [Journal Paper ]
Rana Aamir Raza Co Author:
Impact Of Different Random Initializations On Generalization Performance Of Extreme Learning Machine. Journal Of Computers (JCP) 7 (13 ):805-822
(2018) [Journal Paper ]
2017 Rana Aamir Raza Ashfaq:
Comparative Analysis Of Gaussian Process Regression Based Extreme Learning Machine. Journal Of Software 04 (12 ):291-301 IET, INSPEC, EI
(2017) [Journal Paper ]
Rana Aamir Raza Ashfaq:
Impact Of Fuzziness Categorization On Divide And Conquer Strategy For Instance Ion. Journal Of Intelligent And Fuzzy Systems 4 (33 ): IOS press
(2017) [Journal Paper ]
Rana Aamir Raza Ashfaq:
A Novel Weighted Variational Model For Image Denoising. International Journal Of Pattern Recognition And Artificial Intelligence ( ):DOI: 10.1142/S0218001417540222 World Scientific
(2017) [Journal Paper ]
Rana Aamir Raza Ashfaq - Co-A:
Monotonic Classification Extreme Learning Machine. Neurocomputing (Elsevier) ( ):DOI: 10.1016/j.neucom.2016.11.021
(2017) [Journal Paper ]
Rana Aamir Raza Ashfaq:
Fuzziness Based Semi-supervised Learning Approach For Intrusion Detection System. Information Sciences ( ):DOI: 10.1016/j.ins.2016.04.019
(2017) [Journal Paper ]
2016 Rana Aamir Raza Ashfaq - Co-Author:
Forensic Artifacts Modeling For Social Media Client Applications To Enhance Investigatory Learning Mechanisms. Journal Of Intelligent And Fuzzy Systems ( ):DOI: 10.3233/JIFS-169105
(2016) [Journal Paper ]
Rana Aamir Raza Ashfaq - Co-Author:
Comments On “Local Coupled Extreme Learning Machine”. Neural Computing And Applications 3 (28 ): DOI: 10.1007/s00521-016-2497-z
(2016) [Journal Paper ]
Rana Aamir Raza Ashfaq - Co-Author:
An Improved Local Coupled Extreme Learning Machine. Journal Of Software 11 (8 ):DOI: 10.17706/jsw.11.8.745-755
(2016) [Journal Paper ]
Rana Aamir Raza Ashfaq:
Toward An Efficient Fuzziness Based Instance Selection Methodology For Intrusion Detection System. International Journal Of Machine Learning And Cybernetics ( ):DOI: 10.1007/s13042-016-0557-4
(2016) [Journal Paper ]
Rana Aamir Raza Ashfaq - Co-Author:
Extreme Learning Machine With Fuzzy Input And Fuzzy Output For Fuzzy Regression. Neural Computing And Applications ( ):DOI: 10.1007/s00521-016-2232-9
(2016) [Journal Paper ]
Rana Aamir Raza Ashfaq - Co-Author:
Impact Of Variances Of Random Weights And Biases On Extreme Learning Machine. Journal Of Software ( ):DOI: 10.17706/jsw.11.5.440-454
(2016) [Journal Paper ]
Rana Aamir Raza Ashfaq - Co-Author:
Imbalanced ELM Based On Normal Density Estimation For Binary-Class Classification. In Book : Trends And Applications In Knowledge Discovery And Data Mining ( ):48-60
(2016) [Book Chapter ]
2015 Rana Aamir Raza Ashfaq:
Fuzziness Based Sample Categorization For Classifier Performance Improvement. Journal Of Intelligent And Fuzzy Systems ( ): DOI: 10.3233/IFS-151729
(2015) [Journal Paper ]
Rana Aamir Raza Ashfaq - Co-Author:
Use Correlation Coefficients In Gaussian Process To Train Stable ELM Models,. In Book: Advances In Knowledge Discovery And Data Mining: Lecture Notes In Computer Science, ( ):
(2015) [Journal Paper ]
2013 Basit Habib, Rana Aamir Raza Ashfaq:
Relationship Between Factors Of Quality Models And The System Development Life Cycle. International Journal Of Computer Applications 10 ( 81 ):39-44
(2013) [Journal Paper ]


The publications listed on this page are maintained by the faculty members themselves through their personal accounts on the Research-Repository Website.

 
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