The Research On Extension Data Mining For Extension Residential Architectural Design

Extension Data Mining for Extension Residential Architectural Design,an interdisciplinary and multi-cross research subject in the field of residential architecture design,extenics and data mining,is an important part of the project supported by the National Natural Science Foundation of China(Research on the Theories and Methods of Extension Data Mining for Extension Architectural Planning and Design,Project No.: 51178132).In the context of mass data and poor knowledge based on the Internet and big data,this study explores a new way for artificial intelligence to assist residential architectural design decision-making,which is an useful supplement to the existing theories and method systems of residential architectural design.This thesis constructs the basic theory,method,database construction and framework structure of application method of extension data mining for extension residential architecture design from the perspective of interdisciplinary research.This study aims to give full play to the advantages of multi-disciplinary and multicross research methods,combine theory with data practice to reveal the design rules hidden in the massive residential architectural design data,mine the design knowledge and assist the residential architectural design,and eventually build a bridge for computer-assisted residential architectural design and make the research on residential architectural design theories and methods more comprehensive and scientific,which is an useful supplement to the existing research system of residential architectural design.Based on an in-depth analysis of the research results of extension architectural design and extension data mining,an overview of extension data mining for extension residential architectural design puts forward the basic theory and method of extension data mining for extension residential building design and summarizes the extension data mining of extension residential architectural design.This chapter elaborates the meaning,level,location,characteristics and advantages of extension data mining for extension residential architectural design,constructs a extension data mining pyramid for extension residential architectural design,lists the basic research methods of extension data mining for extension residential architectural design,defines the research direction and task of extension data mining for extension residential architectural design,and points out the types of knowledge that can be found in the extension data mining for extension residential architectural design on this basis,thus laying a foundation for the following application research.On the basis of full consideration and reference to the core advantages of extenics and the characteristics of residential architectural design data,research on the construction of extension data mining for extension residential architectural design is a data platform for knowledge output of extension data mining and a database construction guide for extension residential architectural design and suitable for extension data mining.This chapter describes the meaning,characteristics,advantages of extension residential architectural design database and the data types contained in the database,namely image data and attribute data,analyzes in detail the construction process and method of extension residential architectural design database.At the same time,it realizes the construction goal of extension database for extension residential architectural design based on Arc GIS software,points out the main functional modules of the database,and takes the construction of residential building related database as an example to show the feasibility of the computer software system.The practical application of data query,statistics,visual analysis and other functions becomes more efficient by establishing extension database for extension residential architectural design,thus providing data support for extension data mining for extension residential architectural design.The chapter of extension residential architectural design data mining methods elaborates respectively the definition,algorithms and application analysis of three typical extension data mining methods.The method of extension categorical data mining is a branch of extension transformation.In one hand,it has the same function of categorization and predicting the category of things as data mining,that is,a systematic method of establishing a classification model according to the input dataset,a classification method under supervision.In the other hand,it describes the property of things between belong and not belong or match and not match.Transformed data could also be mutually transformed among qualitative quantitative and boundary extension changes.It describes some information metadata with certain features experience mutual changing of quality and quantity under extension transformation and some data could just meet quantitative changes.This classification method can well fit the correlation between class labels and attribute sets in the input data with a good ability of generalization.Extension clustering data mining method refers to the classification of data objects based on information found in the data that describes objects and their relationships.In machine learning,the classification method of clustering,an unsupervised learning method,is independent of a training set.Different from extension categorical data mining,extension clustering data mining has no division It brings basic-element into clustering based on their location in the universe discourse.It can be transformed as the transformation is implemented without explicit classification of evaluation factors.We could get following knowledge: Which type of data information can be turned into one category through transformation.With the changes of clustering compared before and after transformation,extension association data mining,a correlation analysis-based conductive transformation data mining in traditional data mining,obtains data class’ s rules of mutual changing between quality and quantity through extension transformation.The chapter of extension residential architectural design data mining’s application elaborates on the application methods and cases of extension data mining when it’s used to resolve residential building design issues.It explains the steps and methods to solve the contradiction of designs in detail: namely,make data preparation based on the data information of relevant evaluation traits at the core of design problems and conduct data mining from the core problems of residential architectural design.This chapter emphasizes three major methods of applying extension data mining: extension categorical data mining,extension clustering data mining and extension association data mining as well as steps,mindsets,and categorical data mining which could transform from opposition to unity in solving four categories of issues in set design,morphological design,residential area design and construction technology.Through extension data mining of the corresponding data information to the relevant evaluation traits involved in the core contradictory issues,the transformation between design law and knowledge promotion contradiction could be realized.This thesis aims to conduct a database-based research on extension residential architectural design with extension primitives as the language and extension data mining methods as the guidance,thus solving the bottleneck problem of massive data and poor knowledge and providing theoretical and method support for the gradual realization of artificial intelligent assisted residential architectural design.For this reason,the theory,method and application system of extension data mining for extension residential architectural design are constructed,which provides new theories and methods for residential architectural design decision-making and broadens the application range of the extension data mining theory and method.