The paper builds one-dimensional cellular automat environment model to improve the efficiency of mobile computing application and optimizes process evolution rule and strategy. And it analyzes the computing efficiency of Pascal's Triangle Rule and Bermuda Triangle Rule, thus gives out the evolution rules for the corresponding environment modeling.
As a software component which is capable of learning in an autonomous way, software agent should have the capability of learning in a dynamic environment. Genetic Algorithm has a wide perspective in the machine learning because of its unique characteristic (e.g. dynamic adaptability, self-organization, global convergence and robustness). But when applying GA to agent’s dynamic learning model, it encounters a series of problem. In this paper, a Modifided Multi-Objective Genetic Algorithm(MMOGA) will be introduced to solve these problems. Finally, an Agent’s Dynamic learning model based on a MMOGA which has the flexible dynamic learning capability, better global convergence and performance, will be introduced.
Knowledge Discovery, the science and technology of exploring knowledge in order to discover previously unknown patterns, is a part of the overall process of getting information in databases. In today’s computer-driven world, these databases contain a lot of information. The significant value of this information makes knowledge discovery a matter of considerable importance and necessity. A decision tree is a predictive model which can be used to represent both classifiers and regression models. When a decision tree is used for classification tasks, it is more appropriately referred to as a classification tree.in this paper, Classification Trees Method of Knowledge Discovery In Internet is given.
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