scholarly journals Diagnosis Index System Setup for Implementation Status Management in Large-Scale Construction Projects

2021 ◽  
Vol 2021 ◽  
pp. 1-9
Author(s):  
Wan-Yu Wang ◽  
Yi Wang
Keyword(s):  
Rough Set ◽  
Index System ◽  
Construction Projects ◽  
Large Scale ◽  
Mathematic Model ◽  
Scale Construction ◽  
The Index System ◽  
Set Up ◽  
Implementation Status

In order to scientifically set up the diagnosis index system for the implementation state of large-scale construction projects, this paper proposed a new method which takes into account the indicators in all level states. Different from the index system constructed by other methods, the indexes/indicators established in this paper are more systematically correlated, with a better hierarchical progression in all levels of the index system. The particular diagnosis index parameters of the management objects are firstly analysed through the mathematic model based on the Rough Set. Then, the representation of the periodical management problems is taken as the study object, and the detailed establishing process to form the index system is presented based on the evidenced theory and the Rough Set extraction. Finally, a case study is presented to validate the proposed method. It is shown that the index system set up by the proposed method can not only represent the systematic hierarchical relationships among all corresponding indexes but also diagnose the macroscopic, the mesostates, and the microstates effectively.

scholarly journals Building a rough sets-based prediction model for classifying large-scale construction projects based on sustainable success index

2018 ◽  
Vol 25 (4) ◽  
pp. 534-558 ◽  
Author(s):  
Saeed Akbari ◽  
Mostafa Khanzadi ◽  
Mohammad Reza Gholamian
Keyword(s):  
Prediction Model ◽  
Rough Set ◽  
Construction Projects ◽  
Large Scale ◽  
Construction Project ◽  
Decision Rules ◽  
Scale Construction ◽  
Classification Model ◽  
Content Type ◽  
Success Index

PurposeTo address requirements and specifications of construction project, academics need to build a project classification model. In recent years, project success concept, particularly on large-scale construction projects, has been a controversial issue, especially in developing countries. Hence, in this paper, after introducing a sustainable success index (SSI), a novel method called “rough set approach” had been adopted to induce decision rules and to classify construction projects. The paper aims to discuss these issues.Design/methodology/approachAt first, 20 effective success factors and 15 success criteria based on three pillars of sustainability of economy, society and environment had been categorized. The research data used for analysis had been collected from 26 large-scale construction projects in Iran and five other countries. After collecting data collection, observations had been analyzed and 51 decision rules were generated, and the projects were classified. Eventually, in order to evaluate the performance of the generated rules, confusion matrix was applied, and the model was validated.FindingsThe results of the present study show that rough set theory (RST) can be an effective and valuable tool for building expert systems. Practical applications of these results along with limitations and future research are described.Originality/valuePerhaps for the first time, in the present study, a number of large-scale construction projects are classified based on SSI. Applying RST for building rule-based system and classifying projects in construction project area are novel attempts undertaken in this paper. The rules induced in this study can be applied to develop a sustainable success prediction model in the future studies.

Research on Rural Planning Strategies Based on the Coordination with the Development of Large-Scale Construction Projects - A Case Study on Yanqing County in Beijing

2013 ◽  
Vol 357-360 ◽  
pp. 1882-1885 ◽  
Author(s):  
Qing Yuan ◽  
Ji Guang Zhao ◽  
Yan Yan Xia
Keyword(s):  
Rural Areas ◽  
Construction Projects ◽  
Large Scale ◽  
Scale Construction ◽  
County Level ◽  
Rural Planning ◽  
Coordinated Development ◽  
Planning Strategies

With the increase of construction in rural areas, the research on the coordinated development between large construction projects and the new rural planning has become a significant subject. Taking the rural planning in Beijing Yanqing County as an example, this paper analyzes the interactions which are between rural planning and large-scale construction projects and the current problems. On this basis, the paper proposes objectives and strategies of the rural planning based on the impacts of different large-scale construction projects, which are in order to achieve the coordinated development of rural planning and large-scale construction projects at county level.

Research on the Evaluation of the Degree of Emergency Linkage of Construction Emergencies in Large-scale Construction Projects

2021 ◽  
Author(s):  
Haoran Yan ◽  
Li Wang ◽  
Tiantian Zhang ◽  
Xiangting Jiang ◽  
Sensen Yang ◽  
...  
Keyword(s):  
Construction Projects ◽  
Large Scale ◽  
Scale Construction

Leveraging the Cloud for Large-Scale Software Testing – A Case Study

2012 ◽  
pp. 252-279 ◽  
Author(s):  
Anjan Pakhira ◽  
Peter Andras
Keyword(s):  
Large Scale ◽  
Analysis Data ◽  
System Level ◽  
Small Scale ◽  
Test Cases ◽  
Software Life Cycle ◽  
Technical Issues ◽  
Wide Scale ◽  
Set Up

Testing is a critical phase in the software life-cycle. While small-scale component-wise testing is done routinely as part of development and maintenance of large-scale software, the system level testing of the whole software is much more problematic due to low level of coverage of potential usage scenarios by test cases and high costs associated with wide-scale testing of large software. Here, the authors investigate the use of cloud computing to facilitate the testing of large-scale software. They discuss the aspects of cloud-based testing and provide an example application of this. They describe the testing of the functional importance of methods of classes in the Google Chrome software. The methods that we test are predicted to be functionally important with respect to a functionality of the software. The authors use network analysis applied to dynamic analysis data generated by the software to make these predictions. They check the validity of these predictions by mutation testing of a large number of mutated variants of the Google Chrome. The chapter provides details of how to set up the testing process on the cloud and discusses relevant technical issues.

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