Brain-like Intelligent Data Mining Mechanism Based on Convolutional Neural Network

Many important advances in artificial intelligence research in recent years reflect a trend: inspired by brain science, even partial references can effectively improve the intelligence level of existing artificial intelligence models and systems. However, in order to truly approach or even surpass human-level artificial intelligence, more in-depth research and reference on the brain information processing mechanism is needed. The goal of brain-inspired intelligence research is to realize the next-generation artificial intelligence system with brain-like mechanism and human-like behavior by learning from the neural structure and information processing mechanism of the brain. Because brain-inspired intelligence data has a variety of different cognitive abilities and has strong adaptive ability to complex environments, it is necessary to establish a brain-inspired intelligence data mining mechanism. However, when the current algorithm is used to establish a mining mechanism, it is difficult to eliminate the redundancy in the data accurately, and there is a problem of large data mining errors. Therefore, a brain-like intelligence data mining mechanism based on opportunistic cognition is proposed. The above methods are combined with the time granularity. First, the time series of the original data is segmented to complete the preprocessing of the data, and the correlation between the variables of the brain-like intelligence data is adjusted according to the Mahalanobis distance, and its eigenvalues and characteristics are obtained through the covariance matrix. Vector, which reduces the attributes of the discretized intelligent data on the basis of rough set theory, and eliminates redundant fragments in the table without losing the original brain-like intelligence data information, thus forming a class based on opportunistic cognition. Brain intelligence data mining mechanism. The experimental results show that the proposed method performs better in brain-like intelligent data mining, and the mining efficiency is faster.