Wednesday, April 7, 2010

multi-agent

This study includes the following sections:1, Based on multi-agent and strategy technology, maximizing the performance utility value, meeting the constraint matching conditions of the sensor and the task, we establish the distribution model of sensor.2, In accordance chi hair straightener with the established distribution model of sensor, we use double-particle swarm algorithm for optimal scheduling.3, This paper improve double-particle swarm algorithm and use test laboratories to verify that the improved algorithm can effectively avoid local optimization and improve the ralph lauren polo shirts ability of global optimization.4, In accordance with an example of sensor allocation, we use Matlab simulation experiments to show that, compared with the original Lacoste Polo Shirts double-particle swarm algorithm and genetic algorithms, applying improved double-particle swarm algorithm to chi hair straightener sensor resources allocation of the wireless sensor network, we can achieve the men's nike shoes better allocation results of sensor resources.5, In the process of optimal scheduling of sensor resources, we introduce an improved dynamic energy management in order to reduce energy consumption of sensor node and extend the life cycle of the whole network.
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