Component ACD Model and Its Application in Studying the Price-Related Feedback Effect in Investor Trading Behaviors in Chinese Stock Market

This paper explores the investors’ feedback to the price change by modelling the price-related dynamics of trading intensity. A component decomposition duration modeling approach, called the component autoregressive conditional duration (CACD) model, is proposed to capture the variation of trading intensity across time intervals between price change events. Based on the CACD model, an empirical analysis is carried out on the Chinese stock market that covers different market statuses. The empirical results suggest that the CACD model can capture the price-related dynamics of trading intensity, which supports the existence of the feedback effect and is robust across different market statuses. The authors also study how the investors react to the price change by examining the driven factors of the price-related dynamics of trading intensity. The authors find that the trading can be triggered by the fast rise in the price level and the high trading volume. Besides, investors are more sensitive to the price change direction in the sideways market than in the upward or downward markets.     

An FE-Inexact Heterogeneous ADMM for Elliptic Optimal Control Problems with <Emphasis Type="Italic">L</Emphasis><Superscript>1</Superscript>-Control Cost

Elliptic PDE-constrained optimal control problems with L¹-control cost (L¹-EOCP) are considered. To solve L¹-EOCP, the primal-dual active set (PDAS) method, which is a special semismooth Newton (SSN) method, used to be a priority. However, in general solving Newton equations is expensive. Motivated by the success of alternating direction method of multipliers (ADMM), we consider extending the ADMM to L¹-EOCP. To discretize L¹-EOCP, the piecewise linear finite element (FE) is considered. However, different from the finite dimensional l1-norm, the discretized L¹-norm does not have a decoupled form. To overcome this difficulty, an effective approach is utilizing nodal quadrature formulas to approximately discretize the L¹-norm and L²-norm. It is proved that these approximation steps will not change the order of error estimates. To solve the discretized problem, an inexact heterogeneous ADMM (ihADMM) is proposed. Different from the classical ADMM, the ihADMM adopts two different weighted inner products to define the augmented Lagrangian function in two subproblems, respectively. Benefiting from such different weighted techniques, two subproblems of ihADMM can be efficiently implemented. Furthermore, theoretical results on the global convergence as well as the iteration complexity results o(1/k) for ihADMM are given. In order to obtain more accurate solution, a two-phase strategy is also presented, in which the primal-dual active set (PDAS) method is used as a postprocessor of the ihADMM. Numerical results not only confirm error estimates, but also show that the ihADMM and the two-phase strategy are highly efficient.     

Influence of strategy continuity on cooperation in spatial prisoner’s dilemma games with migrating players

The phenomenon of cooperation is prevalent in both nature and human society. In this paper a simulative model is developed to examine how the strategy continuity influences cooperation in the spatial prisoner’s games in which the players migrate through the success-driven migration mechanism. Numerical simulations illustrate that the strategy continuity promotes cooperation at a low rate of migration, while impeding cooperation when the migration rate is higher. The influence of strategy continuity is also dependent on the game types. Through a more dynamic analysis, the different effects of the strategy continuity at low and high rates of migration are explained by the formation, expansion, and extinction of the self-assembled clusters of “partial- cooperators” within the gaming population.     

A framework for personalized adaptive user interest prediction based on topic model and forgetting mechanism

User interest is not static and changes dynamically. In the scenario of a search engine, this paper presents a personalized adaptive user interest prediction framework. It represents user interest as a topic distribution, captures every change of user interest in the history, and uses the changes to predict future individual user interest dynamically. More specifically, it first uses a personalized user interest representation model to infer user interest from queries in the user’s history data using a topic model; then it presents a personalized user interest prediction model to capture the dynamic changes of user interest and to predict future user interest by leveraging the query submission time in the history data. Compared with the Interest Degree Multi-Stage Quantization Model, experiment results on an AOL Search Query Log query log show that our framework is more stable and effective in user interest prediction.     

Integrated heat and power dispatch model for wind-CHP system with solid heat storage device based on robust stochastic theory

This paper built a combined heat and power (CHP) dispatch model for wind-CHP system with solid heat storage device (SHS) aiming at minimizing system coal consumption, and set system demand-supply balance and units’ operation conditions as the operation constraints. Furthermore, robust stochastic optimization theory was used to describe wind power output uncertainty. The simulation result showed that SHS increased CHP peak-valley shifting capability and reduced abandoned wind rate from 12% to 6%, and reduced 5% coal consumption, compared with the original system operation by flexible charging electric power and heating. The payback period of employing SHS in wind-CHP system is far shorter than SHS expected service life.     

Generalized Intersection Bodies with Parameter

AIn 2005, the classical intersection bodies and L_p intersection bodies were extended. Afterwards, the concept of general L_p intersection bodies and the generalized intersection bodies was introduced. In this paper, we define the generalized bodies with parameter. Besides, we establish the extremal values for volume, Brunn-Minkowski type inequality for radial combination and L_p harmonic Blaschke combination of this notion.     

Global Existence and Optimal Decay Rate of the Compressible Magnetohydrodynamic Equation with Potential Force

In this paper, we consider the three dimensional compressible viscous magnetohydrodynamic equations(MHD) with the external potential force. We first derive the corresponding non-constant stationary solutions. Next, we show global wellposedness of the initial value problem for the three dimensional compressible viscous magnetohydrodynamic equations, provided that the initial data is close to the stationary solution. Finally, based on the elaborate energy estimates for the nonlinear system and L~p-L~q decay estimates of the linearized equation, we show the optimal convergence rates of the solution in L~q-norm with 2≤q≤6 and its first derivative in L~2-norm when the initial perturbation is bounded in L~p-norm with 1≤p6/5.     

Seasonal Variation and Land-Use/Land-Cover Type Impacts on the Correlation of Urban Heat Island Intensity and Difference Vegetation Index with Satellite Data in Xi’an,China

Green coverage has pronounced influences on urban heat island (UHI) effect, while the impacts of seasonal variation and Land-Use/Land-Cover (LULC) types on this effect has not been implemented. This paper investigated the spatio-seasonal characteristics of urban thermal environment and the vegetation-soil mixed area, and then explored the effects of vegetation status on UHI intensity from the perspectives of seasons and regions in Xi’an using four Landsat 8 images. UHI intensity index was implemented to extract UHI intensity based on thermal infrared imagery, and difference vegetation index (DVI) was used to represent vegetation-soil mixed area. Results indicated that DVI has impacts on UHI intensity, and their relations vary with season and region. In the whole Xi’an, if UHI intensity is smaller than -0.1, DVI increases with the increase of UHI intensity; whereas for UHI intensity is greater than -0.1, DVI decreases with increases of the UHI intensity from early spring to autumn. The highest correlation level was discovered in the autumn map (R²=0.713). Results of correlation analysis further displayed that DVI positively correlated with UHI intensity at impervious surface, and that the main urban area possessed the best correlation with R²=0.564 5.     

A Time-Domain Electromagnetic Transmitter with Great Power and Large Current by Using a Closed-Loop Phase Shifting Control Strategy

A time-domain electromagnetic transmitter (TDET) with great power and large current was designed by using a closed-loop phase shifting control strategy. A clamping voltage source circuit was applied in this system to improve the falling edge of emission current and shorten the turn-off time. The simulated results showed that this TDET exhibited the advantages including a large current, strong capability for rapid turn-off, stably output voltage, preferably dynamic performance, a widely adjustable range in transmitting voltage, accurate measurement precision.     

Software Module Clustering Algorithm Using Probability Selection

Software module clustering problem is an important and challenging problem in software reverse engineering whose main goal is to obtain a good modular structure of the software system. The large complex software system can be divided into some subsystems that are easy to understand and maintain through the software module clustering. Aiming at solving the problem of slow convergence speed, the poor clustering result, and the complex algorithm, a software module clustering algorithm using probability selection is proposed. Firstly, we convert the software system into complex network diagram, and then we use the operation of merger, adjustment and optimization to get the software module clustering scheme. To evaluate the effectiveness of the algorithm, a set of experiments was performed on 5 real-world module clustering problems. The comparison of the experimental results proves the simplicity of the algorithm as well as the low time complexity and fast convergence speed. This algorithm provides a simple and effective engineering method for software module clustering problem.