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Journal of Electronic Science and Technology 2020年第4期18卷 341-349页

作者： Li Tang He-Ping Pan Yi-Yong Yao School of Management and Economics University of Electronic Science and Technology of ChinaChengdu 611731 Tianfu College Southwestern University of Finance and EconomicsChengdu 610052 intelligent finance Research Center Chongqing Institute of FinanceChongqing 400067

On the basis of machine leaning,suitable algorithms can make advanced time series *** paper proposes a complex k-nearest neighbor(KNN)model for predicting financial time *** model uses a complex feature extraction process integrating a forward rolling empirical mode decomposition(EMD)for financial time series signal analysis and principal component analysis(PCA)for the dimension *** information-rich features are extracted then input to a weighted KNN classifier where the features are weighted with PCA ***,prediction is generated via regression on the selected nearest *** structure of the model as a whole is *** test results on real historical data sets confirm the effectiveness of the models for predicting the Chinese stock index,an individual stock,and the EUR/USD exchange rate.

关键词： Empirical mode decomposition(EMD) k-nearest neighbor(KNN) principal component analysis(PCA) time series

Single Image Super-Resolution via Dynamic Lightweight Database with Local-Feature Based Interpolation

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Journal of Computer Science & Technology 2019年第3期34卷 537-549页

作者： Na Ding Ye-Peng Liu Lin-Wei Fan Cai-Ming Zhang School of Software Shandong UniversityJinan 250101China Shandong Co-Innovation Center of Future intelligent Computing Yantai 264025China Digital Media Research institute Shandong University of Finance and Economics Jinan 250061China

Single image super-resolution is devoted to generating a high-resolution image from a low-resolution one,which has been a research hotspot for its significant applications. A novel method that is totally based on the single input image itself is proposed in this paper. Firstly, a local-feature based interpolation method where both edge pixel property and location information are taken into consideration is presented to obtain a better initialization. Then, a dynamic lightweight database of self-examples is built with the aid of our in-depth study on self-similarity, from which adaptive linear regressions are learned to directly map the low-resolution patch into its high-resolution version. Furthermore, a gradually upscaling strategy accompanied by iterative optimization is employed to enhance the consistency at each *** without any external information, extensive experimental comparisons with state-of-the-art methods on standard benchmarks demonstrate the competitive performance of the proposed scheme in both visual effect and objective evaluation.

关键词： lightweight database linear regression local-feature interpolation super-resolution

A complete coalition logic of temporal knowledge for multi-agent systems

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Frontiers of Computer Science 2015年第1期9卷 75-86页

作者： Qingliang CHEN Kaile SU Yong HU Guiwu HU Department of Computer Science Jinan University Guangzhou 510632 China institute for Integrated and intelligent Systems Griffith University Brisbane Qld 4111 Australia 3 institute of Business Intelligence and Knowledge Discovery Guangdong University of Foreign Studies Guangzhou 510006 China School of Mathematics and Statistics Guangdong University of Finance and Economics Guangzhou 510320 China

Coalition logic （CL） is one of the most influential logical formalisms for strategic abilities of multi-agent systems. CL can specify what a group of agents can achieve through choices of their actions, denoted by [C]φ to state that a group of agents C can have a strategy to bring about φ by collective actions, no matter what the other agents do. However, CL lacks the temporal dimension and thus can not capture the dynamic aspects of a system. Therefore, CL can not formalize the evolvement of rational mental attitudes of the agents such as knowledge, which has been shown to be very useful in specifications and verifications of distributed systems, and has received substantial amount of studies. In this paper, we introduce coalition logic of temporal knowledge （CLTK）, by incorporating a temporal logic of knowledge （Halpern and Vardi＇s logic of CKLn） into CL to equip CL with the power to formalize how agents＇ knowledge （individual or group knowledge） evolves over the time by coalitional forces and the temporal properties of strategic abilities as well. Furthermore, we provide an axiomatic system for CLTK and prove that it is sound and complete, along with the complexity of the satisfiability problem which is shown to be EXPTIME-complete.

关键词： coalition logic temporal logic of knowledge complete axiomatization multi-agent systems

Quasi-Developable B-Spline Surface Design with Control Rulings

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Journal of Computer Science & Technology 2022年第5期37卷 1221-1238页

作者： Zi-Xuan Hu Peng-Bo Bo Cai-Ming Zhang School of Computer Science and Technology Harbin Institute of TechnologyWeihai 264209China Shandong Co-Innovation Center of Future intelligent Computing Yantai 264005China Shandong Province Key Laboratory of Digital Media Technology Shandong University of Finance and EconomicsJinan 250061China

We propose a method for generating a ruled B-spline surface fitting to a sequence of pre-defined ruling lines and the generated surface is required to be ***,the terminal ruling lines are treated as hard *** from existing methods that compute a quasi-developable surface from two boundary curves and cannot achieve explicit ruling control,our method controls ruling lines in an intuitive way and serves as an effective tool for computing quasi-developable surfaces from freely-designed *** treat this problem from the point of view of numerical optimization and solve for surfaces meeting the distance error tolerance allowed in *** performance and the efficacy of the proposed method are demonstrated by the experiments on a variety of models including an application of the method for path planning in 5-axis computer numerical control(CNC)flank milling.

关键词： developable surface surface modeling B-spline surface numerical optimization

A first-order coalition logic for BDI-agents

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Frontiers of Computer Science 2016年第2期10卷 233-245页

作者： Qingliang CHEN Kaile SU Abdul SATTAR Xiangyu LUO Aixiang CHEN Department of Computer Science Jinan University Guangzhou 510632 China institute for Integrated and intelligent Systems Griffith University Brisbane 4111 Australia College of Computer Science and Technology Huaqiao University Xiamen 361021 China School of Mathematics and Statistics Guangdong University of Finance and Economics Guangzhou 510320 China

Coalition logic （CL） enables us to model the strategic abilities and specify what a group of agents can achieve whatever the other agents do. However, some rational mental attitudes of the agents are beyond the scope of CL such as the prestigious beliefs, desires and intentions （BDI） which is an interesting and useful epistemic notion and has spawned substantial amount of studies in multi-agent systems. In this paper, we introduce a first-order coalition BDI （FCBDI） logic for multi-agent systems, which provides a semantic glue that allows the formal embedding and interaction of BDI, coalition and temporal operators in a first-order language. We further introduce a semantic model based on the interpreted system model and present an axiomatic system that is proved sound and complete with respect to the semantics. Finally, it is shown that the computational complexity of its model checking in finite structures is PSPACE-complete.

关键词： coalition logic BDI logic complete axiomatization computational complexity

Image Smoothing Based on Image Decomposition and Sparse High Frequency Gradient

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Journal of Computer Science & Technology 2018年第3期33卷 502-510页

作者： Guang-Hao Ma Ming-Li Zhang Xue-Mei Li Cai-Ming Zhang School of Computer Science and Technology Shandong University Jinan 250101 China Shandong Co-Innovation Center of Future intelligent Computing Yantai 264025 China School of Software Shandong University Jinan 250101 China Digital Media Research institute Shandong University of Finance and Economics Jinan 250061 China

Image smoothing is a crucial image processing topic and has wide applications. For images with rich texture, most of the existing image smoothing methods are difficult to obtain significant texture removal performance because texture containing obvious edges and large gradient changes is easy to be preserved as the main edges. In this paper, we propose a novel framework （DSHFG） for image smoothing combined with the constraint of sparse high frequency gradient for texture images. First, we decompose the image into two components： a smooth component （constant component） and a non-smooth （high frequency） component. Second, we remove the non-smooth component containing high frequency gradient and smooth the other component combining with the constraint of sparse high frequency gradient. Experimental results demonstrate the proposed method is more competitive on efficiently texture removing than the state-of-the-art methods. What is more, our approach has a variety of applications including edge detection, detail magnification, image abstraction, and image composition.

关键词： image smoothing texture removal image decomposition

A Choquet integral-based TODIM method for q-rung trapezoidal fuzzy numbers and its application in group decision-making

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International Journal of intelligent Computing and Cybernetics 2023年第3期16卷 545-573页

作者： Benting Wan Juelin Huang Shenzhen Research institute Jiangxi University of Finance and EconomicsNanchangChina School of Software and Internet of Things Engineering Jiangxi University of Finance and EconomicsNanchangChina

Purpose–The purpose of this paper is to develop a multi-attribute group decision-making(MAGDM)method under the q-rung orthopair trapezoidal fuzzy environment,which calculates the interaction between the criteria depending on the proposed q-rung orthopair trapezoidal fuzzy aggregation Choquet integral(q-ROTrFACI)and employ TODIM(an acronym in Portuguese of Interactive and Multi-criteria Decision Making)to consider the risk psychology of decision-makers,to determine the optimal ranking of ***/methodology/approach–In MAGDM,q-rung orthopair trapezoidal fuzzy numbers(q-ROTrFNs)are efficient to indicate the quantitative vagueness of *** q-ROTrFACI operator is defined and some properties are ***,a novel similarity measure is developed by fusing the area and coordinates of the q-rung orthopair trapezoidal fuzzy *** on the above,a Choquet integral-based TODIM(CI-TODIM)method to consider the risk psychology of decision-makers is proposed and two cases are provided to prove superiority of the ***–The paper investigates q-ROTrFACI operator to productively solve problems with interdependent ***,an approach is proposed to determine the center point of q–ROTrFNs and a q-rung orthopair trapezoidal fuzzy similarity is ***,CI-TODIM method is devised based on the proposed q-ROTrFACI operator and similarity in q-rung orthopair trapezoidal fuzzy *** illustration example of business models’solutions and hypertension health management are given to demonstrate the effectiveness and superiority of proposed ***/value–Thepaperdevelops a novelCI-TODIMmethodthat effectivelysolves the MAGDM problems under the premise of fully considering the priority of criteria and the risk preference of decision-makers,which provides guiding advantages for practical decision-making and enriches the application of decision-making theory.

关键词： Multi-criteria group decision-making TODIM Choquet integral Q-rung orthopair trapezoidal fuzzy numbers

Predicting the returns of the US real estate investment trust market:evidence from the group method of data handling neural network

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Financial Innovation 2023年第1期9卷 2668-2700页

作者： Wendi Zhang Bin Li Alan Wee‑Chung Liew Eduardo Roca Tarlok Singh Department of Accounting Finance and EconomicsGriffith Business SchoolGriffith UniversityNathan CampusBrisbaneQLDAustralia institute for Integrated and intelligent Systems Griffith UniversityNathanBrisbaneQLDAustralia

Purpose:The Group Method of Data Handling(GMDH)neural network has demon-strated good performance in data mining,prediction,and *** have used it to forecast stock and real estate investment trust(REIT)returns in some coun-tries and region,but not in the United States(US)REIT *** primary goal of this study is to predict the US REIT market using GMDH and then compare its accuracy with that derived from the traditional prediction ***/methodology/approach:To forecast the return on the US REIT index,this study used the GMDH neural network and the generalized autoregressive conditional heteroscedasticity(GARCH)*** this test,the training samples,testing samples,and kernel functions of the GMDH model are controlled to investigate their impact on the accuracy of the machine learning *** experiments were performed using the GARCH model,and the accuracies of these two approaches were ***:Compared with GARCH,GMDH’s accuracy is much higher,indicating that the machine learning approach can provide a highly accurate prediction of REIT *** size of the training samples and the kernel functions in the GMDH model affect the accuracy of the prediction *** particular,the kernel function has a signifi-cant impact on prediction *** linear and linear covariance kernel functions are simple to train and yield accurate predictions,whereas the quadratic function is difficult to *** with small training samples,GMDH can outperform GARCH in prediction *** limitations/implications:Although GMDH shows good performance in predicting the US REIT return,it is still a black-box model,and the algorithm is difficult for financial analysts to develop and *** data used in this study come from the US REIT market,which is the world’s largest and most liquid *** implications:This research shows that the GMDH model outperforms the GARCH model in forecasting REIT ***,

关键词： REIT prediction Machine learning GMDH GARCH Accuracy

An Empirical Investigation on the Risk-Return Relationship of Carbon Future Market

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Journal of Systems Science & Complexity 2016年第4期29卷 1057-1070页

作者： LI Ziran QIAO Han SONG Nan ZU Lei Collaborative Innovation Center for the Innovation and Regulation of Internet-Based finance Southwestern University of Finance and EconomicsChengdu 611130China CFFEX institute for Financial Derivatives Beijing 100033China School of Management University of Chinese Academy of SciencesBeijing 100190China Directors'Office Institute of High Energy PhysicsChinese Academy of SciencesBeijing 100049China School of Management Sciences and Engineering Central University of Finance and EconomicsBeijing 100081China

This paper examines the risk-return relationship for the carbon future market during Phases I, II and III of the European Union Emission Trading Scheme(EU ETS). The risk factors derived from the newly developed LSW model, are embedded into a GARCH framework. This new specification is compared with several GARCH-M type models analyzing the risk-return relationship in the carbon market. The results show that the new specification consistently achieves a good fit and possesses superior explanatory power for the European Union Allowance(EUA) data. Some policy suggestions regarding market efficiency are also provided.

关键词： Carbon price GARCH information diffusion risk-return.

The Risk Linkage Effects of Stock Indexes Based on Quantile Regression and Granger Causality Test

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The Risk Linkage Effects of Stock Indexes Based on Quantile ...