Zobrazeno 1 - 10
of 18
pro vyhledávání: '"Pritam Anand"'
Publikováno v:
IEEE Access, Vol 11, Pp 109841-109855 (2023)
In this paper, we have developed a series of wave hybrid models for significant wave height prediction. Our developed hybrid models uses a triplet of signal decomposition method, regression model and meta-heuristic algorithm. We have used the $\epsil
Externí odkaz:
https://doaj.org/article/1d77fbedccc44604b764acd466c71bc4
Publikováno v:
Intelligent Systems with Applications, Vol 17, Iss , Pp 200169- (2023)
Twin Extreme Learning Machine models can obtain better generalization ability than the standard Extreme Learning Machine model. But, they require to solve a pair of quadratic programming problems for this. It makes them more complex and computational
Externí odkaz:
https://doaj.org/article/486ed1c766364e2b8b733eb1ab3eab60
Publikováno v:
Research Reports on Computer Science. :113-135
Quantile regression models have become popular among researchers these days. These models are being used frequently for obtaining the probabilistic forecast in different real-world applications. The Support Vector Quantile Regression (SVQR) model can
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::515fc5152dc18d00ca0758fb1db4ea35
https://doi.org/10.37256/rrcs.1220221662
https://doi.org/10.37256/rrcs.1220221662
Publikováno v:
Neural Computing and Applications. 33:5733-5752
Phishing websites are on the rise and are hosted on compromised domains such that legitimate behavior is embedded into the designed phishing site to overcome the detection. The traditional heuristic techniques using HTTPS, search engine, Page Ranking
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::a915b2215f3c5b6c0827eef4ad8ed838
https://doi.org/10.1007/s00521-020-05354-z
https://doi.org/10.1007/s00521-020-05354-z
Autor:
Pritam Anand
Publikováno v:
2021 IEEE 18th India Council International Conference (INDICON).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::3db99a50c432fa45c0c2f6ce44748c58
https://doi.org/10.1109/indicon52576.2021.9691714
https://doi.org/10.1109/indicon52576.2021.9691714
Publikováno v:
Transactions on Emerging Telecommunications Technologies. 32
The standard support vector machine (SVM) with a hinge loss function suffers from feature noise sensitivity and instability. Employing a pinball loss function instead of a hinge loss funct...
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::fdb2e04780abce427144faaf66157b03
https://doi.org/10.1002/ett.3820
https://doi.org/10.1002/ett.3820
Publikováno v:
Neural Computing and Applications. 32:3633-3648
This paper presents an efficient and robust Large-margin Distribution Machine formulation for regression. The proposed model is termed as ‘Large-margin Distribution Machine-based Regression’ (LDMR) model, and it is in the spirit of Large-margin D
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::0e8f3c0268d51a954fcf7ab086b8d18c
https://doi.org/10.1007/s00521-018-3921-3
https://doi.org/10.1007/s00521-018-3921-3
Publikováno v:
Optimization. 66:1895-1911
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::7a1d205a6b89479c9ef8e6ff8934677b
https://doi.org/10.1080/02331934.2017.1364739
https://doi.org/10.1080/02331934.2017.1364739
Autor:
Pritam Anand, Amisha Bharti
Publikováno v:
2019 Second International Conference on Advanced Computational and Communication Paradigms (ICACCP).
In this paper, we have introduced a novel combined reward cum penalty loss function to measure the empirical risk in Extreme Learning Machine. The proposed Reward cum Penalty loss function based Extreme Learning Machine (RP-ELM) penalizes those data
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::e4a98ba84bbec8df46c082786554f25b
https://doi.org/10.1109/icaccp.2019.8882885
https://doi.org/10.1109/icaccp.2019.8882885
Publikováno v:
Applied Intelligence. 46:670-683
This paper presents an efficient ź-Twin Support Vector Machine Based Regression Model with Automatic Accuracy Control (ź-TWSVR). This ź-TWSVR model is motivated by the celebrated ź-SVR model (Schlkoff et al. 1998) and recently introduced źź-TSV
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::bdd2c8e534eb93b6c4d0eb9a45611a2c
https://doi.org/10.1007/s10489-016-0860-5
https://doi.org/10.1007/s10489-016-0860-5