A fuzzy reasoning knowledge-based system for assessing rain impact in highway construction scheduling

Part 1. Analytical model

Nang-Fei Pan, Fabian C. Hadipriono, Earl Whitlatch

Research output: Contribution to journalArticle

5 Citations (Scopus)

Abstract

Rainfall is regarded as a major uncertainty factor that has adverse impacts on productivity and duration of highway construction activities. In practice, given the location, type, start date, and original duration of the activities, a common approach for construction schedulers to assess the effect of rain is by adding a certain percentage of time to tasks. However, this method depends mainly on the experience and subjective judgment of the schedulers, who may be unfamiliar with the rainfall pattern and its impact on productivity of the operations, and thus, oftentimes produces inaccurate results. This paper presents a model that uses historical daily rainfall data and experts' knowledge, and employs fuzzy set concept for assessing the impact of rain on project completion. Variables considered by the model include soil drainage, exposure level, and adverse consequence on productivity. The result of this study is a tool for use in estimating indirect rain impact on highway construction activities, and as such it can be used to make the decision to work or not to work. Examples of how to use the model are illustrated.

Original languageEnglish
Pages (from-to)157-167
Number of pages11
JournalJournal of Intelligent and Fuzzy Systems
Volume16
Issue number3
Publication statusPublished - 2005 Sep 30

Fingerprint

Fuzzy Reasoning
Knowledge-based Systems
Knowledge based systems
Analytical Model
Rain
Analytical models
Rainfall
Scheduling
Productivity
Scheduler
Inaccurate
Date
Fuzzy Sets
Completion
Soil
Percentage
Model
Fuzzy sets
Uncertainty
Drainage

All Science Journal Classification (ASJC) codes

  • Statistics and Probability
  • Engineering(all)
  • Artificial Intelligence

Cite this

@article{e0ceed7dfe234fab9c0d98d3c20eccbd,
title = "A fuzzy reasoning knowledge-based system for assessing rain impact in highway construction scheduling: Part 1. Analytical model",
abstract = "Rainfall is regarded as a major uncertainty factor that has adverse impacts on productivity and duration of highway construction activities. In practice, given the location, type, start date, and original duration of the activities, a common approach for construction schedulers to assess the effect of rain is by adding a certain percentage of time to tasks. However, this method depends mainly on the experience and subjective judgment of the schedulers, who may be unfamiliar with the rainfall pattern and its impact on productivity of the operations, and thus, oftentimes produces inaccurate results. This paper presents a model that uses historical daily rainfall data and experts' knowledge, and employs fuzzy set concept for assessing the impact of rain on project completion. Variables considered by the model include soil drainage, exposure level, and adverse consequence on productivity. The result of this study is a tool for use in estimating indirect rain impact on highway construction activities, and as such it can be used to make the decision to work or not to work. Examples of how to use the model are illustrated.",
author = "Nang-Fei Pan and Hadipriono, {Fabian C.} and Earl Whitlatch",
year = "2005",
month = "9",
day = "30",
language = "English",
volume = "16",
pages = "157--167",
journal = "Journal of Intelligent and Fuzzy Systems",
issn = "1064-1246",
publisher = "IOS Press",
number = "3",

}

A fuzzy reasoning knowledge-based system for assessing rain impact in highway construction scheduling : Part 1. Analytical model. / Pan, Nang-Fei; Hadipriono, Fabian C.; Whitlatch, Earl.

In: Journal of Intelligent and Fuzzy Systems, Vol. 16, No. 3, 30.09.2005, p. 157-167.

Research output: Contribution to journalArticle

TY - JOUR

T1 - A fuzzy reasoning knowledge-based system for assessing rain impact in highway construction scheduling

T2 - Part 1. Analytical model

AU - Pan, Nang-Fei

AU - Hadipriono, Fabian C.

AU - Whitlatch, Earl

PY - 2005/9/30

Y1 - 2005/9/30

N2 - Rainfall is regarded as a major uncertainty factor that has adverse impacts on productivity and duration of highway construction activities. In practice, given the location, type, start date, and original duration of the activities, a common approach for construction schedulers to assess the effect of rain is by adding a certain percentage of time to tasks. However, this method depends mainly on the experience and subjective judgment of the schedulers, who may be unfamiliar with the rainfall pattern and its impact on productivity of the operations, and thus, oftentimes produces inaccurate results. This paper presents a model that uses historical daily rainfall data and experts' knowledge, and employs fuzzy set concept for assessing the impact of rain on project completion. Variables considered by the model include soil drainage, exposure level, and adverse consequence on productivity. The result of this study is a tool for use in estimating indirect rain impact on highway construction activities, and as such it can be used to make the decision to work or not to work. Examples of how to use the model are illustrated.

AB - Rainfall is regarded as a major uncertainty factor that has adverse impacts on productivity and duration of highway construction activities. In practice, given the location, type, start date, and original duration of the activities, a common approach for construction schedulers to assess the effect of rain is by adding a certain percentage of time to tasks. However, this method depends mainly on the experience and subjective judgment of the schedulers, who may be unfamiliar with the rainfall pattern and its impact on productivity of the operations, and thus, oftentimes produces inaccurate results. This paper presents a model that uses historical daily rainfall data and experts' knowledge, and employs fuzzy set concept for assessing the impact of rain on project completion. Variables considered by the model include soil drainage, exposure level, and adverse consequence on productivity. The result of this study is a tool for use in estimating indirect rain impact on highway construction activities, and as such it can be used to make the decision to work or not to work. Examples of how to use the model are illustrated.

UR - http://www.scopus.com/inward/record.url?scp=25144487170&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=25144487170&partnerID=8YFLogxK

M3 - Article

VL - 16

SP - 157

EP - 167

JO - Journal of Intelligent and Fuzzy Systems

JF - Journal of Intelligent and Fuzzy Systems

SN - 1064-1246

IS - 3

ER -