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New technological advances in large-scale protein-protein interaction (PPI) detection provide researchers a valuable source for elucidating the bimolecular mechanism in the cell. In this paper, we investigate the problem of protein complex detection from noisy protein interaction data, i.e., finding the subsets of proteins that are closely coupled via protein interactions. Many people try to solve...
For a groundwater source heat pump (GWHP) system, how to realize system high efficiency operation is very important issue. On basis of development idea of modular and open energy management, a model of non-energy-saving (NES) fault diagnosis has been presented, the model involves input of basic characteristic data and index characteristic data and output of NES fault factors, the relationship database...
The importance of reverse logistics channel design has been widely recognized for green supply chain management. This paper aims to choose an appropriate reverse channel structure for remanufacturing while the new and remanufactured products are differential pricing. We also explore some characteristics of the channel coordination mechanisms, which maximize the expected revenue of the manufacturer...
A major challenge in the post-genomic era is to determine protein function on a proteomic scale. There are only less than half of the actual functional annotations available for a typical proteome. The recent high-throughput bio-techniques have provided us large-scale protein-protein interaction data, and many studies have shown that function prediction from protein-protein interaction data is a promising...
The number of variables used for credit scoring can be quite large, and selecting the most relevant variables becomes an important topic. In this paper, we use gradient learning method for variable selection in credit scoring. The original method in the literature does not work on credit datasets because of the large sample size. To conquer this, we modify the algorithm by resampling data and voting...
Bankruptcy prediction has been one of the most challenging tasks and a major research topic in accounting and finance. In this paper, bagging ensemble, a popular technique in the machine learning community, is proposed to improve the prediction performance of artificial neural networks in bankruptcy prediction analysis. The experiments conducted on the public dataset show that the proposed approach...
According to meteorological element data of test reference year (TRY), a dynamic simulation program calculates the hourly cooling loads of an office building from April to September. Then, a general Visual Basic program is developed based on the error back-propagation (BP) algorithm of artificial neural network (ANN). The network is trained and tested by the obtained data. The results are presented...
Since speech is one of the most direct and effective means of human communication, itpsilas natural to apply biomimetic processing mechanism to automatic speech recognition to solve the existing speech recognition problems. In this paper, three typical techniques were selected respectively: simulated evolutionary computation (SEC), artificial neural network (ANN) and fuzzy logic and reasoning technique,...
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