Xiaoyang Fu

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A resource limited immune approach (RLIA) was developed to evolve architecture and initial connection weights of multilayer neural networks. Then, with Back-Propagation (BP) algorithm, the appropriate connection weights can be found. The RLIA-BP classifier, which is derived from hybrid algorithm mentioned above, is demonstrated on SPOT multi-spectral image(More)
In this paper, an evolving neural network ensembles (ENNE) classifier using variable string genetic algorithm (VGA) is proposed. For neural network ensembles (NNE) with regularized negative correlation learning (RNCL) algorithm, the two improvements are adopted: The first term is to evolve the appropriate architecture and initial connection weights of NNE(More)
A variety of researches have been proposed to address commercial prospect of emerging technologies, as it has become one of the research hotspots. Through an extensive literature review, this paper presents a method based on bibliometrics for the investigation of commercial prospects of emerging technologies. Then, the intelligent control in municipal(More)
  • Xiaoyang Fu
  • 2016 Eighth International Conference on Advanced…
  • 2016
In this paper, we investigate neural network ensemble (NNE) classifier and its application to multi-spectral image classification. The effectiveness of the NNE classifier is demonstrated on SPOT multi-spectral image data. Compared with standard classifiers, such as Bayes maximum-likelihood classifier, k-NN classifier, it has shown that the NNE classifier(More)
Due to uncertainties and complexities give birth to the future of emerging technologies, conventional methods for technology evaluation are subjected to many drawbacks and limitations. After combing the relevant literature to the commercial potential of emerging technologies, this paper proposes technology commercialization success to assess the(More)
This paper proposed an improved artificial immune recognition system (IAIRS). It takes multi-training that the affinity threshold scalar ATS is adjusted automatically instead of one shot training, and modifies the criterion of evolving memory cells pool that the affinity threshold AT is only calculated over all samples with the class as the training sample.(More)
In this paper, we study neural network ensembles (NNE) classifier with regularized negative correlation learning (RNCL) and its application to pattern classification. In RNCL algorithm, the regularization parameter is used to control the trade off between mean square error and regularization, and to improve the ensemble's generalization ability. We propose(More)