We performed simulations for comparing three approaches of LVQ neural network: Kohonen's LVQ, Adaptive LVQ and the proposed AFLVQ. From the results, we conclude that the proposed hybrid Adaptive-Fuzzy-LVQ algorithm outperforms several other methods in terms of classification accuracy and smoothness ...
For mouse survival curves, a log rank test was used to calculate statistical significance using GraphPad Prism. Raw expression data were normalized using Genepattern software by a robust multiarray average algorithm with quantile normalization and background correction. Probe sets that had 50% or more...
一种基于AF的决策树算法
In Section 2 we establish mathematical foundations for the recognition method. In Section 3 we specify how feature vectors are extracted from pulses. In Section 4, we explicate the type number estimation algorithm. Section 5 concludes the flow chart and discusses requirements for practical ...
Several adaptive algorithms were proposed to try to find good strategies for general situations. In this paper, we described the implementation techniques of an adaptive pattern growth algorithm, called AFOPT, which demonstrated good performance on all tested datasets. We also extended the algorithm ...
singlemaximumfrequentitemsminingalgorithmefficiencyimprovelimited,onthebasisofin-depthstudytherelatedknowledgeofcloudcomputingandHadoopplatform,developimproveddistributedalgorithmforA—MFI,realizedthedistributedimplementationofminingmaximumfrequentitems.Verifiedbytheexperiment,themaximumfrequentitemsminingmethodofdistributedhas...
However, with this algorithm the energy consumption was unbalanced. 2.3. The Diagnosis Method Based on Artificial Intelligence Recently, the artificial intelligence method was introduced for fault diagnosis applications. Because neural networks have convenient learning and data structure optimization training,...
It improves the performance of BERT through large-scale data training and model parameter optimization. Roberta outperforms the original BERT on several natural language processing tasks. Data2vec [30] proposes a powerful self-supervised algorithm for multiple modal inputs. It also represents a new,...
Dazhi Jiang, Kaichao Wu, Dicheng Chen, Geng Tu, Teng Zhou, Akhil Garg, and Liang Gao. A probability and integrated learning based classification algorithm for high-level human emotion recognition problems. Measurement, 150:107049, 2020. (中科院...
It uses various machine learning techniques (Ridge regression, multi-objective evolutionary algorithm for hyperparameter optimisation, gradient-based optimisation for budget allocation etc.) to define media channel efficiency and effectivity, explore adstock rates and saturation curves. It's built for ...