Huaiqing Wang

Chinese Academy of Sciences

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i-10 index

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Co-Authors

Dongming Xu

University of Queensland

Sherry Sun

Seattle University

Kun Chen

Shenzhen University

Zude Zhou

Wuhan University of Technology

Minhong Wang

University of Hong Kong

Jiaqi Yan

Beihang University

Ping Lou

Wuhan University of Technology

Stephen Shaoyi Liao

City University of Hong Kong

Hokyin Lai

Hong Kong Baptist University

Yuanfeng Ye

Jinling Institute of Technology

Cooperative Institutions

Chinese Academy of Sciences

City University of Hong Kong

Peking University

University of Chinese Academy of Sciences

Chinese Academy of Medical Sciences & Peking Union Medical College

Sichuan University

Central South University

Capital Medical University

Southern University of Science and Technology

Tsinghua University

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A Feature Fusion Based Forecasting Model for Financial Time Series

PLoS ONE (2014)

Zhiqiang Guo Huaiqing Wang Quan Liu Jie Yang

Predicting the stock market has become an increasingly interesting research area for both researchers and investors, and many prediction models have been proposed. In these models, feature selection techniques are used to pre-process the raw data and remove noise. In this paper, a prediction model is constructed to forecast stock market behavior with the aid of independent component analysis, canonical correlation analysis, and a support vector machine. First, two types of features are extracted from the historical closing prices and 39 technical variables obtained by independent component analysis. Second, a canonical correlation analysis method is utilized to combine the two types of features and extract intrinsic features to improve the performance of the prediction model. Finally, a support vector machine is applied to forecast the next day's closing price. The proposed model is applied to the Shanghai stock market index and the Dow Jones index, and experimental results show that the proposed model performs better in the area of prediction than other two similar models.

Canonical correlation

Stock Market Prediction

Predictive modelling

Component (thermodynamics)

10.1371/journal.pone.0101113

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Citations (56)

Intelligent money laundering monitoring and detecting system

Mediterranean Conference on Information Systems (2008)

Yingfeng Wang Huaiqing Wang Shijia Gao Dongming Xu

Criminal elements in today's technology-driven society are using every means available at their disposal to launder the proceeds from their illegal activities. While dedicated efforts are contributed in combating with money laundering (ML) from multi-aspects, without a comprehensive and solid theoretical support, each of them is combating in its own way. To effectively and efficiently prevent and detect such diverse and complex activity, an Anti-Money Laundering (AML) solution should establish comprehensive, solid and fundamental knowledge framework of the monitoring and detecting process. Based on Simons' decision making theory this study proposed an intelligent-agent- oriented solution for money laundering monitoring and detecting process (MLMDP). In order for a more adaptive, intelligent and flexible solution for anti-money laundering, the intelligent agent technology is applied in this research to deal with the complex, dynamic, and distributed MLMDP. Intelligent agents with their properties of autonomy, reactivity and proactivity are well suited for money laundering prevention controls. Several types of agents are proposed and a novel and open multiagent architecture is presented for money laundering monitoring and detecting processes.

Money Laundering

Evasion (ethics)

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高齢者の健康状況と速度の関係について検討する。【JST・京大機械翻訳】

Zhonghua Laonian Yixue Zazhi (2016)

Tiemei Zhang Yu Pulin Senlin Luo Huaiqing Wang Liu Youshou

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Process-Mining-Based Workflow Model Fragmentation for Distributed Execution

IEEE Transactions on Systems Man and Cybernetics - Part A Systems and Humans (2010)

Shuxiang Sun Qingtian Zeng Huaiqing Wang

A complex workflow is often executed by geographically dispersed partners or different organizations. As a solution for dealing with the decentralized nature of workflow applications, a workflow can be fragmented into small pieces and scheduled to different servers for its execution. An important challenge in distributed workflows is to optimize the fragmentation and distribution to achieve efficiency with respect to time and server resources. To tackle this challenge, we propose the application of process mining to the fragmentation of a workflow for distributed execution. The workflow model discovered through process mining records the actual execution of a workflow and allows in-depth analysis of its temporal behavior. Based on examination of the model resulting from process mining, we demonstrate how to determine the minimum time to finish a workflow and how to partition the workflow in order to achieve efficient server usage.

Process mining

Fragmentation

10.1109/tsmca.2010.2069092

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Citations (41)

A Logical Framework for Knowledge Sharing in Multi-agent Systems

Lecture notes in computer science (2001)

Kaile Su Xudong Luo Huaiqing Wang Chengqi Zhang Shichao Zhang

Knowledge Sharing

Logical framework

10.1007/3-540-44679-6_62

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Citations (6)

Development of a Web-service-agents-based Family Wealth Management System

Americas Conference on Information Systems (2004)

Shijia Gao Dongming Xu Yingfeng Wang Huaiqing Wang

The roiling financial markets, constantly changing tax law and increasing complexity of planning transaction increase the demand of aggregated family wealth management (FWM) services. However, current trend of developing such advisory systems is mainly focusing on financial or investment side. In addition, these existing systems lack of flexibility and are hard to be integrated with other organizational information systems, such as CRM systems. In this paper, a novel architecture of Web-service-agents-based FWM systems has been proposed. Multiple intelligent agents are wrapped as Web services and can communicate with each other via Web service protocols. On the one hand, these agents can collaborate with each other and provide comprehensive FWM advices. On the other hand, each service can work independently to achieve its own tasks. A prototype system for supporting financial advice is also presented to demonstrate the advances of the proposed Webservice- agents-based FWM system architecture.

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Knowledge-Based System

Advances in civil and industrial engineering book series (2010)

Zude Zhou Huaiqing Wang Ping Lou

Knowledge-Based System (KBS), a branch research area of AI, has been widely used in interpretation, prediction, diagnosis, debugging, design, planning, monitoring, repair, instruction, and control (Stefik et al., 1982) since it emerged in 1960s. KBS has been recognized as a promising paradigm for the next generation manufacturing systems and there is no doubt that the use of KBS in manufacturing will continue to expand, both in areas of application as well as in depth of knowledge. As a result, factories will benefit a lot, such as improved productivity, more stable and increased yields and increased asset utilization, all leading to improved factory performance. Now KBS are finding an increasing number of applications in almost each stage of intelligent manufacturing, including design, process planning and scheduling, production control, diagnosis and etc. Followed by a case study, the overview over all these applications will be discussed in this chapter after the key technologies of KBS are presented, including knowledge representation, knowledge use, knowledge acquisition and evaluation of KBS.

Knowledge Acquisition

10.4018/978-1-60566-864-2.ch002

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Citations (9)

Intelligent Management Information System

Advances in civil and industrial engineering book series (2010)

Zude Zhou Huaiqing Wang Ping Lou

The Intelligent Management Information System (IMIS) has the potential to transform human decision making by combining research in Artificial Intelligence, Information Technology, and Systems Engineering. The field of Intelligent Decision Making (IDM) is expanding rapidly, due in part to advances in artificial intelligence and networkcentric environments that can deliver the technology. Communication and coordination between dispersed systems can deliver just-in-time information, real-time processing, collaborative environments, and globally up-to-date information to the human decision maker. At the same time, artificial intelligence techniques have demonstrated that they have matured sufficiently to provide computational assistance to humans in practical applications. It is the development direction of modern management science and technology. In this chapter, firstly we introduce the introduction and background of IMIS, and briefly, the related design conception. Subsequently, the Intelligent Decision Support System (IDSS) is depicted, which is the most significant technology of IMIS and related activities in the manufacturing process. The applications of IDSS and two cases for industrial manufacturing are then presented, representing the future development direction of manufacturing management. Lastly, a summary of this chapter is given. IMIS researchers and technologists have built and investigated Decision Support Systems (DSS) for more than 35 years. The developments in DSS began with building model-oriented DSS in the late 1960s which were followed by theory developments in the 1970s, and the implementation of financial planning systems and Group DSS in the early and mid-1980s. During the mid-1980s, Intelligent DSS were implemented through combining knowledge systems with DSS. These developments are discussed below, as well as the origins of Executive Information Systems, On-line Analytical Processing (OLAP), Business Intelligence, and the implementation of Web-based DSS in the mid-1990s, which quickly became a topic for active discussion, and whose influence spread widely.

10.4018/978-1-60566-864-2.ch013

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The Quantitative Profiling of Blood mSEPT9 Determines the Detection Performance on Colorectal Tumors

Epigenomics (2018)

Lele Song Jiayu Wang Huaiqing Wang Yan Chen Jia Jia

Aim: To investigate the quantitative relationship between the positive detection rate (PDR) in colorectal tumor detection and the mSEPT9 level. Materials & methods: The level of blood mSEPT9 in various colorectal diseases was quantified by the Epi proColon 2.0 assay. ΔΔCt values were calculated representing the mSEPT9 level. A total of 1347 subjects were recruited in this quantitative study. Results: PDR or sensitivity was positively correlated with the progression of colorectal tumors and the mSEPT9 level in an exponential relationship. The mSEPT9 level of CRC exhibited a distinct pattern of distribution. Strong correlation was found between mSEPT9 level and PDR or sensitivity in various tumor differentiation, pathological types or metastasis. Conclusion: The quantitative profiling of blood mSEPT9 determines the detection performance on colorectal tumors.

10.2217/epi-2017-0154

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Citations (19)

Intelligent Agent-Based e-Learning System for Adaptive Learning

IGI Global eBooks (2012)

Hokyin Lai Minhong Wang Huaiqing Wang

Adaptive learning approaches support learners to achieve the intended learning outcomes through a personalized way. Previous studies mistakenly treat adaptive e-Learning as personalizing the presentation style of the learning materials, which is not completely correct. The main idea of adaptive learning is to personalize the earning content in a way that can cope with individual differences in aptitude. In this study, an adaptive learning model is designed based on the Aptitude-Treatment Interaction theory and Constructive Alignment Model. The model aims at improving students’ learning outcomes through enhancing their intrinsic motivation to learn. This model is operationalized with a multi-agent framework and is validated under a controlled laboratory setting. The result is quite promising. The individual differences of students, especially in the experimental group, have been narrowed significantly. Students who have difficulties in learning show significant improvement after the test. However, the longitudinal effect of this model is not tested in this study and will be studied in the future.

Presentation (obstetrics)

Constructive

Adaptive Learning

Aptitude

10.4018/978-1-4666-2047-6.ch009

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Citations (1)