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This research presents the application of intelligent computing models in Air Traffic Flow Management (ATFM). Firstly, multi-agent system in grid computing environment is applied to deal with the problem of ATFM synchronization. The developed system consists of software agents, which are implemented in a Computational Grid platform for congestions identification, conflicts resolution and agreements negotiation among the participating airports. A metric criterion, called Agent's Balancing Standard (ABS), is used as a basic index to measure the effectiveness of reducing both the amount of communication among agents and the delay of flights. Secondly, a brief discussion about the Meta-Level Control model is introduced in ATFM issues to improve the efficiency of communication among the agents. The system is developed to analyze the traffic flow information received, identify its importance and process it in the most adequate order.

A method to balance the communication among Multi-Agents in real time traffic synchronization is proposed in this research. The paper presents Air Traffic Flow Management (ATFM) problem and its synchronization property. For such a complex problem, combing grid computing with multi-agent coordination techniques to improve ATFM computational efficiency is the main objective of actual research. To demonstrate the developed model – ATFM in Grid Computing (ATFMGC), the grid architecture, the basic components and the relationship among them are described. At the same time, the function of agents (tactical planning agent etc.), their knowledge representation and inference processes are also discussed. As criteria to measure the effective to reduce quantity of the communication among agents and the delay of the flights, Standard of Balancing among Agents (SBA) is used in the analysis. The simulation shows the efficiency of the developed model and successful application in the case study.

Some web usage mining algorithms showed the potential application to find the difference among the organizations expected by visitors to the website. However, there are still no efficient method and criterion for a web administrator to measure the performance of the modification. In this paper, we developed an AntWeb, a model inspired by ants' behavior to simulate the sequence of visiting the website, in order to measure the efficient of the web structure. We implemented a web usage mining algorithm using backtrack to the intranet website of the Politec Informatic Ltd., Brazil. We defined throughput (the number of visitors to reach their target pages per time unit relates to the total number of visitors) as an index to measure the website's performance. We also used the link in a web page to represent the effect of visitors' pheromone trails. For every modification in the website organization, for example, putting a link from the expected location to the target object, the simulation reported the value of throughput as a quick answer about this modification. The experiment showed the stability of our simulation model, and a positive modification to the intranet website of the Politec.