A Note on the Maximum Entropy Approach to Economics

This article argues that there is no principle of maximum entropy which describes the evolutionary direction of the economic system.It describes a general method of calculating a distribution fuction of the system which has maximum entropy under constrained conditions.

Distribution Prediction of Suitable Growth Area for Eucommia ulmoides in China under Climatic Change Background

[ Objective] The research aimed to study distribution prediction of suitable growth area for Eucommia ulmoides in China under climatic change background. [ Method] By using the maximum entropy model and many kinds of climate change scenarios, we predicted current and future distribution pattems of suitable growth area for Eucommia ulmoides in China and its change process. [ Result ] At present, highly suitable growth area of E. ulmoides mainly distributed in Sichuan, Shaanxi and Chongqing, Under climate change background, total suitable growth areas in future three decades all drastically reduced when compared with that at present. It was noteworthy that moderately and highly suitable growth areas of wild E. ulmoides all disappeared, and junction between Shaanxi and Gansu and Taibai Mountain would be stable suitable growth area of wild E. ulmoides. [ Condusioa] The research could provide useful reference data for investigation, protection and sustainable development of the wild E. ulmoides resources.

A moment-based stochastic edge-based smoothed finite element method for electromagnetic forming process

In this paper, a novel stochastic method named as the moment-based stochastic edge-based finite element method(MSES-FEM)is proposed to deal with the uncertain electromagnetic problems. First, electromagnetic and mechanical field are formulated by smoothed Galerkin Weak Form under edge-based smoothed finite element method(ES-FEM) scheme. The moment analysis is then applied to obtain the first four moments of the responses and to observe the effects of each random variable on electromagnetic field responses. The maximum entropy theory is employed to calculate the probability density functions(PDFs) of the responses. A quasi-static electromagnetic problem and a practical electromagnetic forming problem(EMF) are performed. The proposed method successfully solves stochastic electromagnetic forming analysis under the uncertain parameters. Numerical results obtained by the proposed MSES-FEM are quite satisfactory with the ones by the Monte Carlo simulation(MCS).

Imaging source with Gaussian proper time distribution

Making use of the maximum entropy method, we study the most probable source function in heavy ion collisions. An anisotropic Gaussian source is deduced by simply assuming that the particles are emitted within a finite proper-time. The general relations between the most probable source function and the minimal assumptions are discussed, which are instructive in constructing a self-consistent source function from observed Hanbury-Brown/Twiss（HBT） correlations.

APPLICATION OF MEM SPECTRAL ESTIMATION TO MU RADAR OBSERVATION

Preliminary results of the wind velocity estimation using the Maximum Entropy Method (MEM) to MU radar observation data sets are presented. The comparison of the results from the periodogram method and the MEM shows that the MEM estimation is reliable, and has higher accuracy, resolution and detectability than the estimation from periodogram method. The high accuracy power spectrum obtained by the MEM is very useful to studying the atmospheric turbulence structure. However. the MEM needs the longer computing time for obtaining the high accuracy spectrum. Particularly, the estimation of MEM will bring serious devia- tion at lower signal-to-noise ratio.