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The concept of internet finance has attracted increasing attention in recent years. As a result, more and more online peer-to-peer (P2P) lending platforms have been established at home and abroad. It is actually meaningful to predict investment amounts of online lenders in the following period. In this paper, we propose a Hybrid Investment Prediction Model (HIPM), an effective non-linear prediction...
Most well-known discriminative clustering models, such as spectral clustering (SC) and maximum margin clustering (MMC), are non-Bayesian. Moreover, they merely considered to embed domain-dependent prior knowledge into data-specific kernels, while other forms of prior knowledge were seldom considered in these models. In this paper, we propose a Bayesian maximum margin clustering model (BMMC) based...
Based on fuzzy clustering and multi-model support vector regression, a novel lithium-ion battery state of charge (SOC) estimating model for electric vehicle is proposed. Fuzzy C-means and subtractive clustering combined algorithm is employed to implement the fuzzy partition for the input space with the input vectors sampled in UDDS drive cycle, temperature, current, load voltage of the lithium-ion...
In this paper we consider the weighted (1-center) location problems weighted by the possibilistic clustering method. Such weighting method leads to better robustness to outliers compared with minimax location estimation. Its effectiveness was further verified by the experiments on the artificial dataset.
Outlier detection in high-dimensional space is a hot topic in data mining, the main goal is to find out a small quantity of data objects with abnormal behavior in data set. In this paper, the concepts of the feature vector and the attribute similarity are defined, an improved algorithm SWHOT based on weighed hypergraph model for outlier detection in high dimensional space is presented. The objects...
Urban traffic state analysis plays an important role in the solution of traffic congestion problem. To estimate traffic state effectively is a foundational work for improving traffic condition and preventing traffic congestion. In this paper, a novel pattern-based approach is proposed to model the clustering and classification of traffic state. First, fuzzy-set clustering method is utilized to divide...
With the crucial problem of specifying cluster number in clustering algorithm, a cluster number specification-free algorithm, F-CMSVM, is proposed in this paper. Firstly, the data set is classified into two clusters by Fuzzy C-means algorithm (FCM). Then the result is tested by Support Vector Machine (SVM) associated with a fuzzy membership function to confirm whether the data set could be classified...
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