Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: A novel wireless LAN prediction tool using the genetic algorithm and neural network has been proposed.  establish a site survey tool system to predict the received signal strength index (RSSI) in an indoor environment. The system includes six items. (1) The fading function: it corrects the functional characteristics of the RSSI for different types of wireless LAN cards in free space. (2) The setting of the attributes of obstacles in the indoor environment: the idea of a "single attribute of local area" is proposed. If there are the same obstacles in one area,  set the area as one attribute. (3) The genetic algorithm: where  use reproduction, crossover and mutation to obtain the propagation loss through the different obstacles (Li). (4) The neural network:  use neural network concept to correct the prediction error arising from the multipath effect in the indoor environment. (5) The auxiliary judgment for the sampling points: the method is helpful to users in establishing the best sampling points. (6) The calibration of prediction results:  use calibration to correct the prediction error arisen from Li.
['Rong-Hou Wu', 'Yang-Han Lee', 'Shih-An Chen']
I am writing a research paper on a idea Planning system for indoor wireless network
[{"from": "human", "value": "I am writing a research paper on a idea Planning system for indoor wireless network"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: A novel wireless LAN prediction tool using the genetic algorithm and neural network has been proposed.  establish a site survey tool system to predict the received signal strength index (RSSI) in an indoor environment. The system includes six items. (1) The fading function: it corrects the functional characteristics of the RSSI for different types of wireless LAN cards in free space. (2) The setting of the attributes of obstacles in the indoor environment: the idea of a \"single attribute of local area\" is proposed. If there are the same obstacles in one area,  set the area as one attribute. (3) The genetic algorithm: where  use reproduction, crossover and mutation to obtain the propagation loss through the different obstacles (Li). (4) The neural network:  use neural network concept to correct the prediction error arising from the multipath effect in the indoor environment. (5) The auxiliary judgment for the sampling points: the method is helpful to users in establishing the best sampling points. (6) The calibration of prediction results:  use calibration to correct the prediction error arisen from Li."}]