A fuzzy reasoning knowledge-based system for assessing rain impact
in highway construction scheduling: Part 2. Development and validation of the
system
Abstract: Rainfall often causes adverse impact on productivity and completion
of highway construction projects. Therefore, adequate estimates of the effect
of rain are mandatory for construction contractors to establish reliable
schedules. Based on the analytical model introduced in the Part 1 of this
paper, a fuzzy-based and knowledge-based intelligent scheduling system for
estimating rainfall effect on productivity and duration of highway activities
is presented here. This system contains a knowledge base, database, and fuzzy
logic models. The knowledge base consists of fuzzy if-then rules for use to
assess the impact of rain-related variables on the duration of twenty typical
highway activities. The database includes historical daily rainfall data over
the past 20 years for nine major cities across Taiwan where precipitation data
is available. The fuzzy inference mechanism was developed for use in assessing
the chance to work by considering the impact of rain. A case study involving a
highway construction project implemented in two geographic areas with different
rainfall environments is presented to illustrate the salient features of the
fuzzy reasoning knowledge-based scheduling system (FRESS). System performance
was tested by experts and potential users alike with satisfactory results.
FRESS allows users to simulate experts' judgment and assists contractors to
better estimate activity durations for projects in geographical locations
having rainfall data.
