Titlebook: Computational Intelligence: Theories, Applications and Future Directions - Volume II; ICCI-2017 Nishchal K. Verma,A. K. Ghosh Conference pr

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TelNEClus: Telugu Named Entity Clustering Using Semantic Similaritylogies represent the documents using the vector space model (VSM) traditionally known as bag-of-words (BoW) hypothesis. The main disadvantage of BoW is that the grammatical and the structural information of words is not captured. In this paper, we have attempted to cluster named entities (NEs) extra

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Convolutional Neural Network with Stacked Autoencoder for Kernel Initialization detection, and many other tasks. The data generated in all these areas are very large, and there are a large number of samples along with a large number of attributes. Areas like bioinformatics have a large amount of data, but face the problem of a small number of samples with a large number of att

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Improved EMD Local Energy with SVM for Fault Diagnosis in Air Compressor role in the fault diagnosis. This paper proposes local energy based feature extraction technique derived from improved empirical mode decomposition. Relevancy of feature is examined by correlation method. Support vector machine is used for classification of features. The proposed approach is compar

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Simultaneous Structure and Parameter Learning of Convolutional Neural Network approach is proposed to automatically evolve the architecture of CNN. The evolution of the structure is done using compact genetic algorithm (cGA) by optimizing the number of filters in each layer, and simultaneously, the associated weight parameters are tuned by stochastic gradient descent (SGD).

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