Wang Y.J.,China Minsheng Banking Corporation |
Wang Y.J.,Chinese Academy of Sciences |
Di G.,Peoples Bank of China |
Yu J.,Chinese Academy of Sciences |
And 3 more authors.
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) | Year: 2013
Nowadays, customer attrition is increasingly serious in commercial banks, particularly with respect tomiddle- and high-valued customers in retail banking. To combat this attrition it is incumbent for banks to develop a prediction mechanism so as to identify customers who might be at risk of attrition. This prediction mechanism can be considered to be a classifier. In particular, the problem of predicting risk of customer attrition can be prototyped as a binary classification task in data mining. In this paper we identify a set of features, for customer "attrition vs. non-attrition" classification, based on the RFM (Recency, Frequency and Monetary) model. The reported evaluation indicates that proposed set of features produces a much more effective classifier than that generated using previously suggested features. © 2013 Springer-Verlag.
Dongyan-Li,North China Electrical Power University |
Donghua-Yang,North China Electrical Power University |
Diankun-Mu,Peoples Bank of China
2010 International Conference on Future Information Technology and Management Engineering, FITME 2010 | Year: 2010
With the continuous development of human resources accounting, the problem of human capital measurement has been more concerned. This paper, proceeding from a property point, and based on achievement of the current income, measures the value of Human Capital © 2010 IEEE.
Tang J.,Chiang Mai University |
Zhou C.,Northwest Normal University |
Yuan X.,Yunnan Normal University |
Sriboonchitta S.,Peoples Bank of China
Scientific World Journal | Year: 2014
This paper concentrates on estimating the risk of Title Transfer Facility (TTF) Hub natural gas portfolios by using the GARCHEVT-copula model.We first use the univariate ARMA-GARCH model tomodel each natural gas return series. Second, the extreme value distribution (EVT) is fitted to the tails of the residuals to model marginal residual distributions.Third, multivariate Gaussian copula and Student t-copula are employed to describe the natural gas portfolio risk dependence structure. Finally, we simulate N portfolios and estimate value at risk (VaR) and conditional value at risk (CVaR). Our empirical results show that, for an equally weighted portfolio of five natural gases, the VaR and CVaR values obtained fromthe Student t-copula are larger than those obtained fromthe Gaussian copula.Moreover, when minimizing the portfolio risk, the optimal natural gas portfolio weights are found to be similar across the multivariate Gaussian copula and Student t-copula and different confidence levels. © 2014 Jiechen Tang et al.
Han A.,CAS Academy of Mathematics and Systems Science |
Zheng G.-H.,Peoples Bank of China |
Wang S.-Y.,CAS Academy of Mathematics and Systems Science
Xitong Gongcheng Lilun yu Shijian/System Engineering Theory and Practice | Year: 2010
Traditional approach to establish coincident index fails to capture the dynamic structure of business cycle and cannot describe the relationships among macroeconomic sections. This paper proposes to apply the generalized dynamic-factor model (GDFM), which addresses the above problems, to conduct prosperity analysis of the financial cycle in China. However, this approach, based on frequency domain principal components and thus on two-sided filtering of observable variables, leads to the lag of application. Therefore, we firstly adjust one-sided filtering in the end of sample data. Then, GDFM is employed to construct the coincident index of the financial cycle in China, which is calculated from coincident indexes of a few sub-cycles obtained simultaneously.
Xiong X.,Huazhong Agricultural University |
Tian J.,Huazhong Agricultural University |
Ruan H.,Peoples Bank of China
China Agricultural Economic Review | Year: 2011
Purpose - As a major agricultural province in central China, Hubei Province mainly carries out the peasant household credit investigation system through rural credit cooperatives (RCCs). The purpose of this paper is to evaluate the efficiency of the peasant household credit investigation system in Hubei RCCs and provide some evidence and ideas to the formulation of relevant policies. Design/methodology/approach - First, this paper briefly reviews the related literature of the efficiency in credit investigation system; second, the paper gives a brief description of the data envelopment analysis (DEA) model and designs the indicators for efficiency evaluation; third, the paper accounts data sources and processing methods; and finally, the paper performs the empirical analysis and draws a conclusion. Findings - The paper finds that the efficiency of the resource allocation in both regions is unoptimistic, the general efficiency is somewhat low, and it shows the trend of declination. The efficiency of pure technology in two regions represents the adverse trend. Every year's average scale efficiency in both regions is higher than the pure technology efficiency. Originality/value - The main contributions of this paper include the first use of DEA model to practically evaluate the efficiency of credit investigation system based on 54 samples of RCCs in Hubei Province and the horizontal and vertical comparisons of the results. The conclusions of this paper not only make the efficiency of credit investigation system in the province's 54 credit cooperatives comparable but also has a great application value to the actual decision-making departments in formulating credit policies, and each credit cooperative in further building the credit investigation system according to its own conditions. Moreover, it has certain reference value to other similar studies. Copyright © 2011 Emerald Group Publishing Limited. All rights reserved.
Hua Z.,Jinan Nursing Vocational College |
Guodong L.,Peoples Bank of China |
Tengfei Z.,China Construction Seventh Engineering Division Corporation
Proceedings - 2013 6th International Conference on Business Intelligence and Financial Engineering, BIFE 2013 | Year: 2014
This paper present it is necessary to develop low carbon economy in China. Additionally, considering the current development status of the low carbon economy in China, this paper puts forward relevant policy suggestions on China's low carbon economy in three aspects of legal measures, economic measures and administrative measures. © 2013 IEEE.
Wang D.,Zhengzhou University |
Zheng G.,Zhengzhou University |
Liu L.,Peoples Bank of China
Proceedings of the 2015 27th Chinese Control and Decision Conference, CCDC 2015 | Year: 2015
As a very important technique in biometric recognition, face recognition has many applications in our daily life. It is a very complex problem influenced by the different light condition, pose, head angles, and so on. 108 face images of 27 subjects in ORL face database are efficiently recognized with the developmental network. To testify the effect of developmental network on the face recognition, the influences of different initializing methods for the weights from X layer to Y layer of the DN, and different neuron numbers and competing neuron number top-k in Y layer, are studied. Experimental results show that when the neuron number in Y layer is bigger than the number of subjects to be recognized, the recognition accuracy can reach over 95%. Otherwise, the recognition accuracy decreases significantly. Under the condition of the same neuron numbers in Y layer, with the increasing of fired neuron number k, the recognition accuracy decreases. © 2015 IEEE.
Wang Z.,Shandong University |
Shi Y.,People's Bank of China |
Wang X.,Huaneng Capital Services Corporation Ltd |
Zhang Q.,Shandong University |
Qu S.,Shandong University
International Journal of Green Energy | Year: 2016
The drying up of the fossil energy sources and the damage from unchecked carbon emissions demand the development of low carbon economy, which promotes the development of new energy sources, such as wind power and photovoltaic. However, the direct connections of wind/photovoltaic power into power grid bring great impacts on power systems, thus affecting the security and stability of power system operations, which challenges the power system dispatching. In despite of many methods for power system dispatch, lack of the models, for power system containing wind power and photovoltaic considering carbon trading and spare capacity variation (PSCWPCCTSCV), restricts the further optimal operations of power systems. This paper studies the economic dispatch modeling problem of power system containing wind power and photovoltaic, establishes the model of economic dispatch of PSCWPCCTSCV. On this basis, adaptive immune genetic algorithm is applied to conduct the economic operation optimization, which can provide the optimal carbon trading price and the optimal power distribution coefficient. Finally, simulations based on the newly proposed models are made to illustrate the economic dispatch of PSCWPCCTSCV. The results show that optimization with the proposed model can not only weaken the volatility of the new energy effectively, but also reduce carbon emissions and reduce power generation costs. © 2016 Taylor & Francis Group, LLC.
Wang D.,Zhengzhou University |
Wang H.,China Shipbuilding Industry Corporation |
Liu L.,Peoples Bank of China
Swarm and Evolutionary Computation | Year: 2016
Effective environment exploration in unknown environment is precondition of constructing the environment map and carrying out other tasks for multi-robot system. Due to its excellent performance, particle swarm optimization (PSO) has been widely used in multi-robot exploration field. To deal with its drawback - easily trapped in local optima, Darwinian PSO (DPSO) optimization is proposed by Tillett et al.  with the natural selection function and first used in real world robot exploration by Couceiro et al. , forming the robotic DPSO (RDPSO). To increase the algorithm performance and control its convergence rate, fractional calculus is used to replace inertia component in RDPSO for its "memory" ability and forming the fractional order RDPSO (FORDPSO). This paper presents a formal analysis of RDPSO and studies the influence of the coefficients on FORDPSO algorithm. To satisfy the requirement of dynamically changing robots' behaviors during the exploration, fuzzy inferring system is designed to achieve better control coefficients. Experiment results obtained in two complex simulated environments illustrate that biological and sociological inspiration is effective to meet the challenges of multi-robot system application in unknown environment exploration, and the exploration effect of the fuzzy adaptive FORDPSO is better than that of the fixed coefficient FORDPSO. Furthermore, the performance of FORDPSO with different neighborhood topologies are studied and compared with other six PSO variations. All the results demonstrate the effect of the FORDPSO on the multi-robot environment exploration. © 2015 Elsevier B.V. All rights reserved.