Artificial intelligence and parametric construction cost estimate modeling: State-of-the-art review
HH Elmousalami - Journal of Construction Engineering and …, 2020 - ascelibrary.org
This study reviews the common practices and procedures conducted to identify the cost
drivers that the past literature has classified into two main categories: qualitative and …
drivers that the past literature has classified into two main categories: qualitative and …
Time series analysis via network science: Concepts and algorithms
There is nowadays a constant flux of data being generated and collected in all types of real
world systems. These data sets are often indexed by time, space, or both requiring …
world systems. These data sets are often indexed by time, space, or both requiring …
Comparison of artificial intelligence techniques for project conceptual cost prediction: A case study and comparative analysis
HH Elmousalami - IEEE Transactions on Engineering …, 2020 - ieeexplore.ieee.org
Developing a reliable parametric cost model at the conceptual stage of the project is crucial
for project managers and decision makers. Existing methods, such as probabilistic and …
for project managers and decision makers. Existing methods, such as probabilistic and …
Visibility graph for time series prediction and image classification: a review
The analysis of time series and images is significant across different fields due to their
widespread applications. In the past few decades, many approaches have been developed …
widespread applications. In the past few decades, many approaches have been developed …
Predicting the volatility of highway construction cost index using long short-term memory
The highway construction cost index (HCCI) is a composite indicator that reflects the price
trend of the highway construction industry. Most available indexes exhibit significant …
trend of the highway construction industry. Most available indexes exhibit significant …
Natural visibility encoding for time series and its application in stock trend prediction
As a newly developed method, the natural visibility graph (NVG) has attracted great
attention. Most of the previous research focuses on exploring the time series using the NVG …
attention. Most of the previous research focuses on exploring the time series using the NVG …
A novel network-based and divergence-based time series forecasting method
Time series forecasting becomes important due to its wide application in many fields. A
variety of methods have been developed to address this problem based on different …
variety of methods have been developed to address this problem based on different …
An efficient network method for time series forecasting based on the DC algorithm and visibility relation
J Zhao, H Mo, Y Deng - IEEE Access, 2020 - ieeexplore.ieee.org
Recently time series prediction based on network analysis has become a hot research topic.
However, how to more accurately forecast time series with good efficiency is still an open …
However, how to more accurately forecast time series with good efficiency is still an open …
Forecasting the scheduling issues in engineering project management: Applications of deep learning models
S Liu, W Hao - Future Generation Computer Systems, 2021 - Elsevier
Since project monitoring aims to make decisions, which have future impacts on a project's
success, accurate forecasting of project characteristics is of greater importance. This paper …
success, accurate forecasting of project characteristics is of greater importance. This paper …
Analysis of construction cost and investment planning using time series data
F Jiang, J Awaitey, H Xie - Sustainability, 2022 - mdpi.com
Construction costs and investment planning are the decisions made by construction
managers and financial managers. Investment in construction materials, labor, and other …
managers and financial managers. Investment in construction materials, labor, and other …