Showing papers by "Southwest University published in 2003"

Tabu search algorithm based on insertion method

Abstract: This paper presents a tabu insertion search algorithm (TIS) based on the merits of insertion method (IM) and tabu search (TS) algorithm for solving travel salesman problem (TSP). TIS combines the good local search ability of tabu search with the good tour construct ability of insertion method to search the solution space and to solve the combinatorial optimization problem. In this paper, we use the classical NP hard problem TSP to test the effectiveness of TIS. Results show that TIS has the good ability to jump beyond local optimum and to obtain the global optimum.

A novel adaptive search strategy of intensification and diversification in tabu search

Abstract: Intensification and diversification are two highly important components of tabu search At many cases, these two components are also conflicting between them It is worthy of being studied that how to harmonize this conflict Aiming at this problem, a novel adaptive search strategy of intensification and diversification was proposed in this paper Taking traveling salesman problem as samples, many experiments was investigated The results shows: this strategy is feasible and effective

A novel chaotic neural network for many-to-many associations and successive learning

Abstract: In this paper, we propose a novel successive learning chaotic neural network (NSLCNN). It has two distinctive features: (1) it can deal with many-to-many associations; (2) it can learn unknown pattern successively. As for the first feature, when a stored pattern is given to the network, the network searches around the input pattern by chaos. The proposed model makes use of this property to deal with many-to-many associations. As for the second one, when a different input pattern is given, a different response is received. So it can distinguish unknown patterns from the known patterns and learn the unknown patterns successively. A series of computer simulations show the effectiveness of the proposed model.

The Empirical Research of the Volatility Clustering of the GARCH Effect of the Shanghai Exchanges in China

Abstract: Frequent volatility is a feature of stock market. Autoregressive Conditional Heteroscedasticity (ARCH) model is often used to forecast the variance of the benefit of financial capitals. Statistic descriptions indicate that the benefit of finance capitals in China has the characteristic of autoregressive conditional hetero -skedasticity and abnormality. The ARCH models by Eviews are adopted in this paper to forecast the variance of the benefit of financial capitals from 1993 to 2003. Results obtained show that the Generalized Autoregressive Conditional Heteroscedasticity( GARCH) model is a better model for frequent volatility of stock market in Chi-

Dummy Economy:A New Sphere of Human Economic Activities

Abstract: In the dummy economy research in a bid to make known the variation of human economic activities, the inherent ideas about it must be eliminated and all Karl Marx's exposition on hypothetical capital must be fully understood. And the dummy economy cannot be equated with hypothetical capital, Internet economy and bubble economy. The contemporary noteworthy dummy economy is derivative financial commodity transaction, e-currency and dot.com bank.

Partial cloning of 17B-HSD1 from the Nile tilapia ovary and its expression pattern during spawning cycle

Abstract: A 548 bp partial cDNA fragment of 17β-hydroxysteroid dehydrogenase (17β-HSD1) was obtained by RT-PCR from the ovary of Nile Tilapia. The expression of 17β-HSD1 was high from 0 to 11 days after spawning, but there was a sharp decline at the day of spawning (day 14) indicating its involvement in ovarian cycle.