| The elevator is an indispensable vertical traffic means of transport in the skysraper, with the emerging in a large amount of the high-story intelligent building, passengers have put forward higher and higher demand to the systematic function of the elevator. In recent years, the control technology of the elevator has got fast development, a lot of advanced control technology is applied to the Elevator Group Control System(EGCS), improving the systematic performance of EGCS greatly, but there are many stressing problems demanding prompt solutions.The thesis regards the EGCS as the research object. On the basis of analysing in depth to the control technology of the elevator, deep research has been carried on to the group control intelligence system of the elevators regarding improving the systematic intelligent level of EGCS, reducing waiting time, improving the service quality and meeting the needs of modern work as the goal. A kind of new multi-target intelligent optimize dispatching method has been putting forward by setting up an EGCS controlled on the basis of the traffic pattern-recognition.The thesis analyses the systematic characteristic, control method, performance evaluation index and traffic flow situation of EGCS at first, setting up complicated flow of passengers and analysing models, this model can produce the flow of passengers data under any traffic mode, offer the emulation environment for EGCS. In traffic pattern-recognition, fuzzy neural network is adopted to distinguish the traffic flow, this method has very good recognition capability to the complicated traffic flow and can play very good guidance function to adopt the corresponding group control policy to EGCS according to different traffic.
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