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To overcome the shortages of the existing financial prediction models such as strict hypothesis, poor generalization ability, low prediction accuracy and low learning rate etc., a new early warning model of financial crisis have established for listed company using Extreme Learning Machine. From five dimensions of solvency, operating-ability, profitability, cash-ability and grow-ability, fifteen financial...
In order to coordinate with and promote the scientific process of the national fencing team, we developed the decision support system for training. In fencing training, we established a two-way reasoning model based on Bayesian network and found the relationship between training process and physiological indicators. Combined with experienced knowledge and sample data, we did research on knowledge...
As is known to all, the neutral network has made a great progress in many fields. But due to some strict theoretical system, there are still many defaults in practical application. In this paper, we present an active learning artificial neural network (ALANN). The key issue of this kind of approach is what information can be analysis and forecast about time series(TS). However, the parameters of ALANN...
During face-to-face conversation, the speaker's head is continually in motion. These movements serve a variety of important communicative functions, and may also be influenced by our emotions. The goal for this work is to build a domain-independent model of speaker's head movements and investigate the effect of using affective information during the learning process. Once the model is learned, it...
The major limitation in bilingual latent semantic analysis (bLSA) is the requirement of parallel training corpora. Motivated by semi-supervised learning, we propose a clusterbased bLSA training approach to incorporate monolingual corpora. Treating each parallel document pair as centroids of the parallel document clusters, each monolingual document is associated to the closest centroid according to...
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