期刊：
Discrete Dynamics in Nature and Society,2015年2015(Pt.1) ISSN：1026-0226
通讯作者：
Liu, Xiang
作者机构：
[Liu, Xiang; Chen, Hui; Li, Yanhui; Liu, Bailing] Cent China Normal Univ, Sch Informat Management, Wuhan 430079, Peoples R China.;[Liu, Xiang; Li, Yanhui; Liu, Bailing] Hubei Res Ctr E Commerce, Wuhan 430079, Peoples R China.
通讯机构：
[Liu, Xiang] C;Cent China Normal Univ, Sch Informat Management, Wuhan 430079, Peoples R China.
摘要：
Facility location, inventory control, and vehicle routes scheduling are three key issues to be settled in the design of logistics system for e-commerce. Due to the online shopping features of e-commerce, customer returns are becoming much more than traditional commerce. This paper studies a three-phase supply chain distribution systemconsisting of one supplier, a set of retailers, and a single type of product with continuous review (Q, r) inventory policy. We formulate a stochastic location-inventory-routing problem (LIRP) model with no quality defects returns. To solve the NP-hand problem, a pseudo-parallel genetic algorithm integrating simulated annealing (PPGASA) is proposed. The computational results show that PPGASA outperforms GA on optimal solution, computing time, and computing stability.
作者机构：
[Xiao, Yi] Cent China Normal Univ, Sch Informat Management, Wuhan 430079, Peoples R China.;[Liu, John J.] City Univ Hong Kong, Ctr Transport Trade & Financial Studies, Hong Kong, Hong Kong, Peoples R China.;[Xiao, Jin] Sichuan Univ, Sch Business, Chengdu 610064, Peoples R China.;[Hu, Yi] Univ Chinese Acad Sci, Sch Management, Beijing 100190, Peoples R China.;[Bu, Hui] Beihang Univ, Sch Econ & Management, Beijing 100191, Peoples R China.
通讯机构：
[Liu, John J.] C;City Univ Hong Kong, Ctr Transport Trade & Financial Studies, Hong Kong, Hong Kong, Peoples R China.
关键词：
Singular spectrum analysis;Air transport traffic forecasting;Generalized regression neural network;Radial basis function network
摘要：
The air transport industry crucially depends on traffic forecasting for supporting management decisions. In this study, a singular spectrum analysis (SSA)-based ensemble forecasting modeling approach is proposed. The original air passenger time series is first decomposed into three components: trend, seasonal oscillations, and irregular component. The trend is predicted by generalized regression neural network (GRNN), whereas seasonal oscillations are predicted by radial basis function networks (RNFNs). The empirical results of Hong Kong (HK) air passenger data show a significant improvement of the proposed ensemble method in comparison to other results of competing models.
作者：
Xiao, Yi;Liu, John J.;Wang, Shouyang;Hu, Yi;Xiao, Jin*
期刊：
Neural Computing and Applications,2015年26(2):363-371 ISSN：0941-0643
通讯作者：
Xiao, Jin
作者机构：
[Xiao, Yi] Cent China Normal Univ, Sch Informat Management, Wuhan 430079, Peoples R China.;[Liu, John J.] City Univ Hong Kong, Ctr Transport Trade & Financial Studies, Kowloon, Hong Kong, Peoples R China.;[Wang, Shouyang] Chinese Acad Sci, Acad Math & Syst Sci, Beijing 100190, Peoples R China.;[Hu, Yi] Univ Chinese Acad Sci, Sch Management, Beijing 100190, Peoples R China.;[Xiao, Jin] Sichuan Univ, Sch Business, Chengdu 610064, Peoples R China.
关键词：
Financial market fluctuation;Multiple dimensioned mining;Radial basis function network
摘要：
Fluctuation mining is one of the greatest challenging tasks in the field of finance market. The main contribution of this research was to propose a multiple dimensioned model for financial market fluctuation mining. In this approach, the original financial time series is broken down into different information by the wavelet filtering technique, and then, all this information is handled through radial basis function networks due to its universal approximation abilities and more robust than the ordinary networks. An experimental analysis is conducted with the proposed model using stock index future time series, revealing consistent performance improvement of this kind of multidimensional approach.
作者机构：
[Xiao Jin] Sichuan Univ, Sch Business, Chengdu 610064, Peoples R China.;[Xiao Yi] Cent China Normal Univ, Sch Informat Management, Wuhan 430079, Peoples R China.;[Xiao Yi] Chinese Acad Sci, Acad Math & Syst Sci, Beijing 100190, Peoples R China.;[Fu Julei] Natl Univ Def Technol, Changsha 410073, Hunan, Peoples R China.;[Lai Kin Keung] City Univ Hong Kong, Dept Management Sci, Hong Kong, Hong Kong, Peoples R China.
会议名称：
1st International Conference on Forecasting Economic and Financial Systems (FEFS) / 5th International Workshop on Singular Spectrum Analysis and its Applications (SSA)
会议时间：
MAY 17-20, 2012
会议地点：
Beijing, PEOPLES R CHINA
会议主办单位：
[Xiao Jin] Sichuan Univ, Sch Business, Chengdu 610064, Peoples R China.^[Xiao Yi] Cent China Normal Univ, Sch Informat Management, Wuhan 430079, Peoples R China.^[Xiao Yi] Chinese Acad Sci, Acad Math & Syst Sci, Beijing 100190, Peoples R China.^[Fu Julei] Natl Univ Def Technol, Changsha 410073, Hunan, Peoples R China.^[Lai Kin Keung] City Univ Hong Kong, Dept Management Sci, Hong Kong, Hong Kong, Peoples R China.
关键词：
Analog complexing;container throughput forecasting;discrete particle swarm optimization;transfer forecasting model
摘要：
Accurate forecast of future container throughput of a port is very important for its construction, upgrading, and operation management. This study proposes a transfer forecasting model guided by discrete particle swarm optimization algorithm (TF-DPSO). It firstly transfers some related time series in source domain to assist in modeling the target time series by transfer learning technique, and then constructs the forecasting model by a pattern matching method called analog complexing. Finally, the discrete particle swarm optimization algorithm is introduced to find the optimal match between the two important parameters in TF-DPSO. The container throughput time series of two important ports in China, Shanghai Port and Ningbo Port are used for empirical analysis, and the results show the effectiveness of the proposed model.
作者：
Chen, C. L. Philip*;Li, Hong;Wei, Yantao;Xia, Tian;Tang, Yuan Yan
期刊：
IEEE Transactions on Geoscience and Remote Sensing,2014年52(1):574-581 ISSN：0196-2892
通讯作者：
Chen, C. L. Philip
作者机构：
[Chen, C. L. Philip] Univ Macau, Fac Sci & Technol, Dept Comp & Informat Sci, Macau, Peoples R China.;[Xia, Tian; Tang, Yuan Yan] Univ Macau, Fac Sci & Technol, Macau, Peoples R China.;[Li, Hong] Huazhong Univ Sci & Technol, Sch Math & Stat, Wuhan 430074, Peoples R China.;[Wei, Yantao] Cent China Normal Univ, Coll Informat Technol Journalism & Commun, Wuhan 430079, Peoples R China.;[Wei, Yantao] Huazhong Univ Sci & Technol, Inst Pattern Recognit & Artificial Intelligence, Wuhan 430074, Peoples R China.
通讯机构：
[Chen, C. L. Philip] U;Univ Macau, Fac Sci & Technol, Dept Comp & Informat Sci, Macau, Peoples R China.
关键词：
Derived kernel (DK);Infrared (IR) image;Local contrast;Signal-to-noise ratio (SNR);Target detection
摘要：
Robust small target detection of low signal-to-noise ratio (SNR) is very important in infrared search and track applications for self-defense or attacks. Consequently, an effective small target detection algorithm inspired by the contrast mechanism of human vision system and derived kernel model is presented in this paper. At the first stage, the local contrast map of the input image is obtained using the proposed local contrast measure which measures the dissimilarity between the current location and its neighborhoods. In this way, target signal enhancement and background clutter suppression are achieved simultaneously. At the second stage, an adaptive threshold is adopted to segment the target. The experiments on two sequences have validated the detection capability of the proposed target detection method. Experimental evaluation results show that our method is simple and effective with respect to detection accuracy. In particular, the proposed method can improve the SNR of the image significantly.
作者机构：
[Xiao Yi] Cent China Normal Univ, Sch Informat Management, Wuhan 430079, Peoples R China.;[Xiao Jin] Sichuan Univ, Sch Business, Chengdu 610064, Peoples R China.;[Liu John] City Univ Hong Kong, Ctr Transport Trade & Financial Studies, Hong Kong, Hong Kong, Peoples R China.;[Wang Shouyang] Chinese Acad Sci, Acad Math & Syst Sci, Beijing 100190, Peoples R China.
通讯机构：
[Liu John] C;City Univ Hong Kong, Ctr Transport Trade & Financial Studies, Hong Kong, Hong Kong, Peoples R China.
会议名称：
1st International Conference on Forecasting Economic and Financial Systems (FEFS) / 5th International Workshop on Singular Spectrum Analysis and its Applications (SSA)
会议时间：
MAY 17-20, 2012
会议地点：
Beijing, PEOPLES R CHINA
会议主办单位：
[Xiao Yi] Cent China Normal Univ, Sch Informat Management, Wuhan 430079, Peoples R China.^[Xiao Jin] Sichuan Univ, Sch Business, Chengdu 610064, Peoples R China.^[Liu John] City Univ Hong Kong, Ctr Transport Trade & Financial Studies, Hong Kong, Hong Kong, Peoples R China.^[Wang Shouyang] Chinese Acad Sci, Acad Math & Syst Sci, Beijing 100190, Peoples R China.
摘要：
The financial market volatility forecasting is regarded as a challenging task because of irregularity, high fluctuation, and noise. In this study, a multiscale ensemble forecasting model is proposed. The original financial series are decomposed firstly different scale components (i.e., approximation and details) using the maximum overlap discrete wavelet transform (MODWT). The approximation is predicted by a hybrid forecasting model that combines autoregressive integrated moving average (ARIMA) with feedforward neural network (FNN). ARIMA model is used to generate a linear forecast, and then FNN is developed as a tool for nonlinear pattern recognition to correct the estimation error in ARIMA forecast. Moreover, details are predicted by Elman neural networks. Three weekly exchange rates data are collected to establish and validate the forecasting model. Empirical results demonstrate consistent better performance of the proposed approach.
期刊：
Journal of Systems Science and Systems Engineering,2014年23(3):362-374 ISSN：1004-3756
通讯作者：
Dong, Qingxing
作者机构：
[Dong, Qingxing] Cent China Normal Univ, Sch Informat Management, Wuhan 430079, Peoples R China.;[Saaty, Thomas L.] Univ Pittsburgh, Pittsburgh, PA 15260 USA.
通讯机构：
[Dong, Qingxing] C;Cent China Normal Univ, Sch Informat Management, Wuhan 430079, Peoples R China.
关键词：
Group decision making;Analytic Hierarchy Process (AHP);consensus;judgment updating
摘要：
In group decision making, a certain degree of consensus is necessary to derive a meaningful and valid outcome. This paper proposes a consensus reaching model for a group by using the Analytic Hierarchy Process (AHP). It supports people to improve their group consensus level through an updating of their judgments. In this model, a moderator suggests the most discordant decision maker to update his judgment in each step. The proposed consensus reaching model allows decision makers to accept or reject the suggestion from the moderator. This model ensures that the judgment updating is effective and the final solution will be of acceptable consistency. Finally, a numerical example is given to illustrate the validity of the proposed consensus reaching model.
期刊：
Mathematical Problems in Engineering,2014年2014 ISSN：1024-123X
通讯作者：
Liu, Bailing
作者机构：
[Li, Yanhui; Liu, Bailing; Lu, Mengmeng] Cent China Normal Univ, Sch Informat Management, Wuhan 430079, Peoples R China.
通讯机构：
[Liu, Bailing] C;Cent China Normal Univ, Sch Informat Management, Wuhan 430079, Peoples R China.
摘要：
Facility location and inventory control are critical and highly related problems in the design of logistics system for e-commerce. Meanwhile, the return ratio in Internet sales was significantly higher than in the traditional business. Focusing on the existing problem in e-commerce logistics system, we formulate a closed-loop location-inventory problem model considering returned merchandise to minimize the total cost which is produced in both forward and reverse logistics networks. To solve this nonlinear mixed programming model, an effective two-stage heuristic algorithm named LRCAC is designed by combining Lagrangian relaxation with ant colony algorithm (AC). Results of numerical examples show that LRCAC outperforms ant colony algorithm (AC) on optimal solution and computing stability. The proposed model is able to help managers make the right decisions under e-commerce environment.
摘要：
Stock e-exchange prices forecasting is an important financial problem that is receiving increasing attention. This study proposes a novel three-stage nonlinear ensemble model. In the proposed model, three different types of neural-network based models, i.e. Elman network, generalized regression neural network (GRNN) and wavelet neural network (WNN) are constructed by three non-overlapping training sets and are further optimized by improved particle swarm optimization (IPSO). Finally, a neural-network-based nonlinear meta-model is generated by learning three neural-network based models through support vector machines (SVM) neural network. The superiority of the proposed approach lies in its flexibility to account for potentially complex nonlinear relationships. Three daily stock indices time series are used for validating the forecasting model. Empirical results suggest the ensemble ANNs-PSO-GA approach can significantly improve the prediction performance over other individual models and linear combination models listed in this study.
摘要：
Facility location, inventory control, and vehicle routes scheduling are critical and highly related problems in the design of logistics system for e-business. Meanwhile, the return ratio in Internet sales was significantly higher than in the traditional business. Many of returned merchandise have no quality defects, which can reenter sales channels just after a simple repackaging process. Focusing on the existing problem in e-commerce logistics system, we formulate a location-inventory-routing problem model with no quality defects returns. To solve this NP-hard problem, an effective hybrid genetic simulated annealing algorithm (HGSAA) is proposed. Results of numerical examples show that HGSAA outperforms GA on computing time, optimal solution, and computing stability. The proposed model is very useful to help managers make the right decisions under e-supply chain environment.
关键词：
Shape from images;Shape from silhouette;Viewing line;Visual hull
摘要：
Visual hull of object has been widely applied in many fields in computer vision. The methods computing visual hulls are mainly classified into two categories: surface-based approaches and volume-based approaches. Surface-based approaches are precise and lack robustness while volume-based approaches are robust but inaccurate and work slowly. However, the speeds of both methods cannot satisfy the demand of real-time application. The paper proposes a novel method to compute visual hull rapidly. To this aim, the method is based on viewing lines. First, the viewing lines are computed from all the contours of the object from different viewpoints. Secondly, the viewing lines are confined within limits and sampled into some dispersive points. Thirdly, a sequence of images of the object is used to exclude points which locate outside the surface of the visual hull. Finally, a water-tight surface of visual hull is extracted from the remnant points. Experiments with real data are conducted to test the rapidity of the proposed method. (C) 2013 Elsevier GmbH. All rights reserved.
作者机构：
[He Tingting] Cent China Normal Univ, Dept Comp Sci, Wuhan 430079, Peoples R China.;[Li Fang] Cent China Normal Univ, Engn & Res Ctr Informat Technol Educ, Wuhan 430079, Peoples R China.;[He Tingting; Li Fang] Natl Language Resources Monitoring & Res Ctr, Network Media Branch, Wuhan 430079, Peoples R China.
通讯机构：
[He Tingting] C;Cent China Normal Univ, Dept Comp Sci, Wuhan 430079, Peoples R China.
摘要：
This paper focuses on semantic knowledge acquisition from blogs with the proposed tagtopic model. The model extends the Latent Dirichlet Allocation (LDA) model by adding a tag layer between the document and the topic. Each document is represented by a mixture of tags; each tag is associated with a multinomial distribution over topics and each topic is associated with a multinomial distribution over words. After parameter estimation, the tags are used to describe the underlying topics. Thus the latent semantic knowledge within the topics could be represented explicitly. The tags are treated as concepts, and the top-TV words from the top topics are selected as related words of the concepts. Then PMI-IR is employed to compute the relatedness between each tag-word pair and noisy words with low correlation removed to improve the quality of the semantic knowledge. Experiment results show that the proposed method can effectively capture semantic knowledge, especially the polyseme and synonym.
期刊：
JOURNAL OF INTERNET TECHNOLOGY,2012年13(5):785-792 ISSN：1607-9264
通讯作者：
Liu, Bailing
作者机构：
[Wang, Weijun; Liu, Bailing] Cent China Normal Univ, Dept Informat & Management, Wuhan, Peoples R China.
通讯机构：
[Liu, Bailing] C;Cent China Normal Univ, Dept Informat & Management, Wuhan, Peoples R China.
关键词：
Negotiation strategy;Access control policy;Trust establishment;OBDDs
摘要：
Trust negotiation is an approach that establishes mutual trust between strangers wishing to share resources or conduct business by gradually requesting and disclosing credentials in the Internet. In trust negotiation, negotiation strategies must be adopted to determine the search for a successful negotiation. Deterministic Finite Automaton Negotiation Strategy (DFANS) is a complete and highly efficient negotiation strategy proposed recently. DFANS takes advantage of ordered binary decision diagrams (OBDDs) to represent access control policies. However, the size of OBDDs is highly sensitive to the scanning order of resources in access control policies, which may result in exponentially large OBDDs in the worst case. To address this challenging issue, in this paper, a new data structure called access control policy diagrams (ACPDs) is proposed to take place OBDDs in DFANS. ACPDs are cyclic, directed graphs, whose sizes do not sensitive to the scan order of resources in access control policies, and the number of nodes in an ACPD is not more than the number of resources in the access control policy. Further, an efficient simplified algorithm is developed to reduce the number of nodes and shorten the path length when referring to redundant vertices in ACPDs.
期刊：
Frontiers of Computer Science in China,2011年5(2):135-147 ISSN：1673-7350
通讯作者：
Liu, Bailing
作者机构：
[Liu, Bailing] Huazhong Normal Univ, Dept Informat & Management, Wuhan 430079, Peoples R China.;[Xiao, Feng] Huawei Technol Co Ltd, Wuhan 430000, Peoples R China.;[Deng, Ke] 92373 PLA, Dalian 116001, Peoples R China.
通讯机构：
[Liu, Bailing] H;Huazhong Normal Univ, Dept Informat & Management, Wuhan 430079, Peoples R China.
关键词：
automated trust negotiation (ATN);negotiation success;sensitive information protection;framework;policy language
摘要：
Automated trust negotiation (ATN) is an approach to establishing mutual trust between strangers wishing to share resources or conduct business by gradually requesting and disclosing digitally signed credentials. In ATN, there are conflicts between negotiation success and sensitive information protection, that is, these two needs cannot be given priority at the same time, which is a challenging problem to resolve. In this paper, a language independent ATN framework, which is dynamic, flexible and adaptive, is presented to address this problem, ensuring negotiation success without sensitive information leakage. This framework is independent of the policy language which is used. However, the language used should have the capability to specify all kinds of sensitive information appearing in credentials and policies, and support the separation of attribute disclosure from credential disclosure. Thus definitions of new language features, which can be incorporated into existing policy languages, are given, enabling the used language to support the capabilities mentioned above.
摘要：
This paper examines the relevance of various financial and economic indicators in forecasting business cycle turning points using neural network (NN) models. A three-layer feed-forward neural network model is used to forecast turning points in the business cycle of China. The NN model uses 13 indicators of economic activity as inputs and produces the probability of a recession as its output. Different indicators are ranked in terms of their effectiveness of predicting recessions in China. Out-of-sample results show that some financial and economic indicators, such as steel output, M2, Pig iron yield, and the freight volume of the entire society are useful for predicting recession in China using neural networks. The asymmetry of business cycle can be verified using our NN method.
摘要：
Automated trust negotiation is an approach that establishes mutual trust between strangers wishing to share resources or conduct business by gradually requesting and disclosing digitally signed credentials. Sometimes negotiators do not have very strict security requirements or the efficiency is the most crucial need. In such cases, it is preferable to adopt schemes that speed up negotiations, even if they do not maximize the protection of the involved resources. Therefore, in this paper, we present a trust negotiation framework that speeds up negotiations from two aspects whenever possible, disclosure sequence generation and credential validation, which are computationally expensive during negotiations. The framework we propose presents several innovative features, such as the support for predicting disclosure sequences by locally trusted peers, the use of declaration tickets and proving tickets to reduce the number of exchanged credentials and credential validations. Further, we report experimental results based on our implementation of this framework, which show that our framework can greatly speed up negotiations whenever possible.
摘要：
A new clustering analysis method based on the pseudo parallel genetic algorithm (PPGA) is proposed for business cycle indicator selection. In the proposed method, the category of each indicator is coded by real numbers, and some illegal chromosomes are repaired by the identification and restoration of empty class. Two mutation operators, namely the discrete random mutation operator and the optimal direction mutation operator, are designed to balance the local convergence speed and the global convergence performance, which are then combined with migration strategy and insertion strategy. For the purpose of verification and illustration, the proposed method is compared with the K-means clustering algorithm and the standard genetic algorithms via a numerical simulation experiment. The experimental result shows the feasibility and effectiveness of the new PPGA-based clustering analysis algorithm. Meanwhile, the proposed clustering analysis algorithm is also applied to select the business cycle indicators to examine the status of the macro economy. Empirical results demonstrate that the proposed method can effectively and correctly select some leading indicators, coincident indicators, and lagging indicators to reflect the business cycle, which is extremely operational for some macro economy administrative managers and business decision-makers.
