Research On Knowledge Mining Technology And Application For Scheme Design Of High-Grade Sightseeing Elevator Car

The sightseeing elevator car sheme design is the core for the design and development of sightseeing elevator,while the low efficiency of knowledge acquisition for engineer during the design become a fatal factor which restricte the quality and cycle of sightseeing elevator.In the view of the current problems tthat the knowledge of high-grade sightseeing elevator is difficult to be unified and the knowledge base is redundant,the knowledge demand is depart from the current knowledge push methods,the current methods have low efficiency,This paper studies the design knowledge mining technology and application of high-grade sightseeing elevator car scheme Elevator and the sightseeing elevator knowledge push system was developed which achieved a high efficiency push of sightseeing elevator design knowledge.The system was successfully applied in "BingHu" sightseeing elevator design and Curling sightseeing elevator car design.The main content of this thesis as followsChapter one introduced the background and point out the significance of this thesis,reviewed the current research of design knowledge modeling,knowledge demand minning as well as design knowledge push.Several problems of sightseeing elevator knowledge push were proposed.And finally the research contents and framework was given.Chapter two presented a method of modeling for the heterogeneous knowledge of sightseeing elevator based on knowledge gene.Summarized the characteristics of high-end sightseeing elevator design knowledge and high-grade sightseeing elevator design knowledge for gene division.Combined with concrete examples of high-grade sightseeing elevator design knowledge heterogeneous modeling method,the knowledge filtering method of high-grade sightseeing elevator knowledge based on T-S fuzzy neural network is used to filter the knowledge of high-grade sightseeing elevator design,reduce the degree of knowledge redundancy and compare and analyze the effect of filtering methodChapter three proposed a method to forecast the knowledge demand of high-grade sightseeing elevator based on support regression machine.This paper analyzes the scheme design of elevator car as well as the design knowledge requirement of the high-grade sightseeing elevator car scheme,takes into account the behavior information and design scene of the designer,constructs the knowledge demand model of the high-grade sightseeing elevator car design,and puts forward the knowledge of the high-grade sightseeing elevator car design Demand mining prediction method,design knowledge requirement initialization and updating algorithm,information granular model,extract knowledge structure requirement from knowledge demand model,realize knowledge push by high-grade sightseeing elevator car design knowledge.Chapter four put forward the knowledge reduction match method of high grade sightseeing elevator design based on nonnegative matrix decomposition.The method of calculating the weight of the TF-IWF-IWF is generated by using the natural language segmentation method and the method of calculating the weight of TF-IWF-IWF.The non-negative matrix decomposition technique is used to reduce the dimension of the design of the knowledge gene matrix,and the low-And the matching of the knowledge needs in the low-dimensional space is calculated and the matching degree of the design knowledge in the low-dimensional space is calculated and optimized.The effect of the algorithm is analyzed by experiment.Chapter five developed the sightseeing elevator knowledge push system.The framework and function modules of the system were introduced and several examples were given.Chapter sixth conclude the content and result of this thesis.Meanwhile,the follw studies were discussed.