Experimental results show that our approach outperforms both baseline methods and state-of-the-art methods on various evaluation metrics.
With the implementation of modern quarry production methods and state-of-the-art techniques, Turkey is among the seven leading large producers of natural stone in the world [2].
Subsequent sections in this paper discuss some of the basic definitions, provide an overview of the various preprocessing methods and state-of-the-art data processing tools for multivariate analysis that are widely used in Raman and IR spectroscopy.
Furthermore, two methods in the NSST domain, GΓD ‐ NSST [13], NIG ‐ NSST [13], and a high-order total variation method based on compressive sensing called High-TV [15] are also applied to compare the achieved performance among the proposed methods and state-of-the-art papers under the same circumstances.
Since these conventional methods are benchmarking methods and state-of-the-art methods of ordinal regression, they are suitable for comparison with the proposed method.First, we show the estimation performance of prediction error degrees by the proposed method and the conventional methods.
The numerical results show that the new SL-TLBO algorithm is a viable alternative approach for solving both small and large scale dynamic dispatch problems and outperforms other popular heuristic methods and state-of-the-art TLBO variants in the tests on well-known benchmarks and DEED problem with proper parameter tuning.
The resulting algorithm, which we name SHeArlet based No-reference Image quality Assessment (SHANIA), is tested on several database (LIVE, Multiply Distorted LIVE and TID2008) and shown to be suitable for many common distortions, consistent with subjective assessment and comparable to full-reference IQA methods and state-of-the-art general purpose NR-IQA algorithms.
Second, use of sensitive, selective, and accurate analytical methods and state-of-the-art laboratory facilities.
Using our newly developed culturing and computational methods and state-of-the-art proteomics and transcriptomics analyses, we generated the first systems-level molecular phenotype of replicatively aging yeast.
Detailed results for single machine learning methods and the consensus methodology are also provided, together with the comparison to previously published methods and state-of-the-art software tools.
Meanwhile, comparative study was conducted on the proposed method and the state-of-the-art SVM.
