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Genetic algorithm is a kind of way to solve complex problems effectively, for it is not bound by the restrictive assumptions of the search space, and doesn't require the assumption conditions such as continuity and derivatives. So this algorithm has its advantage that the traditional algorithm can not compared. Genetic algorithm uses multi-point search. In each iteration, the new individuals are generated...
An improved image enhancement algorithm based on genetic algorithm has been presented and applied for transmission line image processing in this paper, in which fuzziness is served as the optimization method of the image enhancement procedure. Because the complexity and uncertainty of the image itself, fuzzy theory has been used in the image processing. In this process, the parameters of the transformation...
With the rapid development of Internet, mobile-learning system has created new ways for educators to communicate with learners. Mobile-learning as a new mode of learning, the relationship between the study object and the subject and among the study main body and among the study object show multiple interaction and the construction, etc. This study model shows the advantages that the traditional model...
In order to evaluate the optimization efficiency of Genetic Algorithms (GA), this paper presents an efficiency evaluation criterion based on average optimization generation and time efficiency of GA, which not only can avoid infection evaluating the efficiency of GA on random factors commendably, but also consider the time firstly. So that it provides gist of evaluation criterion and theory for selecting...
To improve the ship's anti-roll effect, a new idea is put forward that fin and flap fin are considered as two independent executing outfits to design the control strategy. The regressive method is adopted to found the mathematic models of hydrodynamic coefficient of fin/lap fin. The simulation model of disturbance moment of sea wave is also founded. The intelligent assignment rule of fin angle/flap-fin...
An accurate prediction of gas emission volume under the shaft is the premise for the prevention of gas explosion. To more accurately predict the gas emission volume, a novel wavelet neural network is proposed in this paper. First, a new structure of wavelet neural network is established. This structure is a kind of compact metric structure, in which the Daubechies wavelet is adopted. And then genetic...
Data Mining is rapidly evolving areas of research that are at the intersection of several disciplines, including statistics, databases, pattern recognition, and high- performance and parallel computing. In this paper, we propose a novel mining algorithm, called ARMAGA (association rules mining algorithm based on a novel genetic algorithm), to mine the association rules from an image database, where...
For the characteristic of scale-free networks, containing a few nodes that have a very high degree and many with low degree,the high connectivity nodes play an important role of hubs in communication and networking. This characteristic can be exploited with designing efficient search algorithms. This paper proposes an algorithm to change each new node connecting to the network based on its high-degree-probability...
Data mining technology has emerged as a means for identifying patterns and trends from large quantities of data. Mining encompasses various algorithms such as clustering, classification, and association rule mining. In this paper we take advantage of the genetic algorithm (GA) designed specifically for discovering association rules. We propose a novel spatial mining algorithm, called ARMNGA(association...
Task scheduling is a NP-hard problem and is an integral part of parallel and distributed computing. This paper combined with the advantages of genetic algorithm and simulated annealing, brings forward a parallel genetic simulated annealing algorithm and applied to solve task scheduling in grid computing. It first generates a new group of individuals through genetic operation such as reproduction,...
Task scheduling is a NP-hard problem and is an integral part of parallel and distributed computing. This paper combined with the advantages of genetic algorithm and simulated annealing, brings forward a parallel genetic simulated annealing algorithm and applied to solve task scheduling in grid computing. It first generates a new group of individuals through genetic operation such as reproduction,...
Since the task scheduling in grid computing faces a NP-hard problem, it leads very difficult to validate the methods of task scheduling. This paper combined with the advantages of two evaluative algorithms: genetic algorithm and simulated annealing, brings forward an hybrid evaluative algorithm and applied to solve task scheduling problem in grid computing. From the analysis and experiment result,...
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