作者机构：
[高玮] Department of Civil Engineering, Wuhan Polytechnic University, Wuhan 430023, China;[冯夏庭; 高玮] Key Laboratory of Rock and Soil Mechanics, Institute of Rock and Soil Mechanics, Chinese Academy of Sciences, Wuhan 430071, China
通讯机构：
Department of Civil Engineering, Wuhan Polytechnic University, China
期刊：
PROCEEDINGS OF THE 11TH INTERNATIONAL CONFERENCE ON INDUSTRIAL ENGINEERING AND ENGINEERING MANAGEMENT, VOLS 1 AND 2: INDUSTRIAL ENGINEERING AND ENGINEERING MANAGEMENT IN THE GLOBAL ECONOMY,2005年:621-625
摘要：
Stock market is complicated dynamic system affected by many factors. To model it, many methods have been proposed. But those methods cannot solve this problem very well. In this paper, from analyses the mathematic description of stock market system, a new method based on new evolutionary neural network is proposed here. In this new evolutionary neural network, the traditional BP algorithm and a new bionics algorithm, immunized evolutionary programming proposed by author 1 is combined. In order to verify this new method, the stock market data of Shanghai market in 1996 is used. The results show that, our new method is very good to real practice.
期刊：
Progress in Safety Science and Technology Volume 4:Proceedings of the 2004 International Symposium on Safety Science and Technology,2004年4(PART A):922-926
关键词：
ant colony algorithm;combination optimization;mine ventilation system
摘要：
The optimization of mine ventilation system is a very complicated combination optimization. Ant colony algorithm proposed recently is a very good method to solve complicated combination optimization problem. Considering the essence of optimization of mine ventilation system, the ant colony algorithm is introduced here to solve the problem of mine ventilation system optimization. The detailed process of ant colony algorithm to optimization of mine ventilation system is described in this paper. At last, a mining engineering example is used to verify the effect of this new method. The results show that, ant colony algorithm is a very good method to complicated combination optimization problem. It not only can solve optimization of ventilation system, but also can solve the similar problem of scheme optimization.
摘要：
From the generalized constitutive law of geo-material elastic-plastic model, the problem of model identification among one model type is transformed to a problem of parameter identification. So, using the new bionics algoritlun-Immune Evolutionary Programming (IEP) proposed by author recently, the elastic-plastic model identification among one model type is studied, and a new model identification method is proposed. At last, this method is verified by a numerical example. The results show that, this method can get the suitable geo-material model when only displacements are known.
作者机构：
[高玮] Dept. of Civil Eng., Wuhan Polytech. Univ., Wuhan 430023, China;[冯夏庭; 高玮] Lab. of Rock and Soil Mech., Inst. of Rock and Soil Mech., Chinese Acad. of Sci., Wuhan 430071, China
通讯机构：
Dept. of Civil Eng., Wuhan Polytech. Univ., China
