| dc.description.abstract | Because the flourishing development of the wireless communication industry during these years , realization that every wireless system has because of break-through and quantity of technology too , the wireless products have been already extensive use in various life , existing mobile phone, computer, and new to research and develop generation digit of the Electrical home appliances , etc. Build WIFLY constructed of the Taipei local government on the construction of hardware , and Taipei MRT of Wenhu（文湖） Line , and WIFI in many school education , the wireless system application use in a large amount now . But in RF frequency band use , signal power of area contained appropriate or not , or the monitoring on this area , there were every system that needed to maintain and in charge of accusing after erecting . Because various system of signals contain whole around the environment , this thesis further investigates how to go to assess the signal of classify .
Particle Swarm Optimization (PSO) , it has convergence and fast operation of characteristic that this performs algorithms , this is a good method on the optimization problem generation that solve and apply to the research of neural networks . Every particle in the colony of PSO , There is mutual information communication characteristic , it can offer appropriate information on relevance , and also parameters are set up less 、 fast to search 、 easy to realized . This thesis theme use this to improve K-Means particles relevance among the colonies , offer enough weights by appropriately judging 、 revision of correct signal position in the colony , and combine map system to appear vision result .
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