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An introduction to fuzzy control (2nd ed.)
An introduction to fuzzy control (2nd ed.)
Data mining and knowledge discovery in databases
Communications of the ACM
Intelligent Databases: Object Oriented, Deductive Hypermedia Technologies
Intelligent Databases: Object Oriented, Deductive Hypermedia Technologies
Knowledge Discovery in Databases
Knowledge Discovery in Databases
Statistical Themes and Lessons for Data Mining
Data Mining and Knowledge Discovery
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Construction business abandons in data, such as: prices of individual work items, site productivity data, details on construction materials, and similar, that are used to estimate the works and offer services, at contractor's side, or evaluate construction alternatives and decide on money spending, at owner's side. Such a wealth of data is usually queried using rudimentary tools, producing plain spreadsheet-like reports, such as bills of quantities and lists of materials. Improvements in handling of existing hisorical data, especially cost data, would result in better knowledge extraction during estimating and could generally enhance the quality of construction project management.Construction estimating and evaluation of technology options are not always based on fully determined database queries. Therefore, "flexible" queries such as: "retrieve materials with 'good daily output' and 'acceptable cost'" are likely to be utilized on a historical cost database. Flexible queries are not possible in standard relational databases and there is no such command in SQL relational database language that can be used to retrieve materials with "good daily output" or "acceptable cost". Instead, relational query must state bottom limit for daily output and top limit for acceptable material cost.A standard relational construction cost estimating database has been created, with all necessary functions required by the modern construction practice. In order to enable usage of so-called linguistic variables in queries, relational cost data model has than been extended with concepts from fuzzy theory. User interface has been created in a transparent manner, so software may be used by professionals and alike without knowledge on fuzzy concepts. All extensions to data model have been implemented using standard relational database language, as both relational data model and fuzzy sets are based on theory of sets.Extended data model has been tested on a large construction project to simulate expert's reasoning and provide automated professional advice to the user. Results matched expert's opinion and model proved to be useful knowledge extraction tool in construction estimating practice.