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The influence from individual preference and circumstance has been considered in the distributed path-planning model which is generated by Maximum Likelihood Estimation (MLE) and Bayesian Theory, and the model parameter can be determined with actual driving records of an optimal path-planning model. The new model develops the previous one from a single path into a distribution based on driving records...
Research community has recently put more attention to the Extreme Learning Machines (ELMs) algorithm in Neural Network (NN) area. The ELMs are much faster than the traditional gradient-descent-based learning algorithms due to its analytical determination of output weights with the random choice of input weights and hidden layer bias. However, since the input weights and bias are randomly assigned...
It is difficult to get satisfactory churn prediction results by traditional models, because the available customer samples in target domain are usually few and the class distribution of customer data is imbalanced. This study proposes a group method of data handling (GMDH) based dynamic transfer ensemble (GDTE) model for churn pre-diction. It first transfers the data in related source domains to the...
For a support vector algorithm, the problem of sensitivity to noise points is considered as one of the major problems that may affect the accuracy of the results. In this paper, a weighted method based on rough neighborhood approximation is proposed to reduce the influence of noise points for support vector data description algorithm, which is an important branch of support vector model. Based on...
In order to analyze the influence degree between after-sales service quality and usage quality of aviation equipment, a method based on wavelet neural network (WNN) is proposed that support the equipment supplier to determine the key workflow and factors. Supplier workflow index-equipment usage quality relation function was established, and the overall effectiveness was defined. MATLAB was used for...
Customer churn prediction is an important issue in customer relationship management. The class distribution of customer data is often imbalanced, which may affect the performance of churn prediction model greatly. This paper combines transfer learning and multiple classifiers ensemble, and proposes a transfer ensemble model for imbalanced data (TEMID). This method focuses on using transfer learning...
This paper presents a low-power VLSI implementation of a 4-channel independent component analysis (ICA) processor for portable EEG signal processing applications. The low-power scheme employed for this ICA chip is based on power gating and clock gating by utilizing Cadence common power flow (CPF) low-power methodology and also according to the characteristics of ICA training behavior using different...
The focus of this paper is the effect mechanism of employee callaberation on organizational creativity. Employee callaberation and trust are highlighted in promoting organizational creativity. The processes of knowledge creation are then identified, with the employee callaberation analyzed. It is also suggested that knowledge creation process have mediated the effects of employee callaberation on...
In many real-world applications, the problem of class imbalance and cost-sensitive always arise simultaneously. To address this problem, we propose an effective solution named VOTCL: first, we generate several balanced training datasets by combining under-sampling and over-sampling techniques; then, they are trained to get base learners; at last, voting based on optimal threshold is proposed to ensemble...
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