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Sophistication of a HCAN control environment and an anatomy of the agent modules for enabling intelligent data fusion and management are presented.
The main advantages of the model include: removing direct human intervention, overcoming the complexity of computations in resulting algorithm by means of multi agent modules, and ranking suppliers based on both voice of customer and engineering characteristics during all stages of the process.
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As this methodology is employing an agent module, the agent is also implemented in this step.
As the proposed methodology is used, this process is replaced by an agent module.
This agent module is made using the predesigned specifications, models and platforms, and profiles.
In this experiment, application intent map agent, which has information about each service's user priority, is the agent module.
The approach that GENIUS uses in defining an agent's behavior is based on a hierarchical parametric approach which is a part of the Agent Module (AM) module.
Obviously, the primary user does not contain the cognitive radio module, while the agent module is common in both the primary and secondary users.
The third part, secondary user interface (SUI) sends a request message to the agent module, whenever a user wants to have a portion of spectrum (for internet surfing, watching high quality videos, etc).
Note that, in essence, spectrum sensing and characterizing is beyond the scope of our work; thus, our focus will be on agent module which is the key functionary to enable cooperation between primary and secondary users.
The learning agent module in that system is self-adjusting and learns the network-based audit data and the host-based audit data, with a capability of learning more than one technique of data mining, such as association rules and so on.
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CEO of Professional Science Editing for Scientists @ prosciediting.com