Qualitative analysis of cost risk using WEKA program

Naji, Hafeth I.; Ali, Rouwaida Hussein

doi:10.1109/isces.2018.8340566

Cited by 2 publications

(2 citation statements)

References 1 publication

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“…Additionally, quoting a high bid price for a tender and including all necessary criteria in the bid, choosing an alternative construction technique to maintain the construction schedule, and changing the plans and designs can all be considered as effective risk avoidance strategies in the construction industry (Ahmadi et al, 2017;Yoon et al, 2015). Further, risks can also be accepted by minimising unnecessary delays in decision-making, accepting all the results arising due to risks, and keeping a contingency plan (Naji and Ali, 2018;Perera et al, 2020). Since some of the risks are predictable, they can be mitigated through measures such as effective communication with other contractual parties and providing education and training to the workers of the organization.…”

Section: Risk Response Measuresmentioning

confidence: 99%

Management of environmental risks in highway construction projects in Sri Lanka

Abhayantha,

Perera,

Perera

et al. 2023

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Purpose Environmental risks (ERs) are critical to any highway construction project (HCP). One of the main contracting parties responsible for ERs is the contractor. Hence, it has been crucial to look into ways to control ERs in HCPs from the contractor’s perspective. This study aims to investigate how ERs can be managed in HCP in Sri Lanka. Design/methodology/approach A quantitative research approach with three rounds of Delphi was used. Statistical techniques were used to analyse and validate the ERs, the parties to whom the risks were to be allocated, and risk management measures identified from the empirical data collection. Findings The study reveals the 11 most significant ERs for HCP. Further, the most significant ERs in HCP were mainly found to be the responsibility of contractors in Sri Lanka. Twenty-four most appropriate risk response measures were determined; 13 were found to be common measures that could be used to manage two or more risks, while the remaining 11 were unique to specific risks. Originality/value Overall, this research determines the most significant ERs in HCP, the best risk allocation among the parties and appropriate risk-handling strategies and measures for each significant ERs. Additionally, the study addresses the demand for ERs management in HCP.

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Section: Risk Response Measuresmentioning

confidence: 99%

Management of environmental risks in highway construction projects in Sri Lanka

Abhayantha,

Perera,

Perera

et al. 2023

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“…The training process was carried out in WEKA software, which is an applicable tool for classification utilization and data mining. Note that many scholars have employed WEKA before for various simulating objectives [36,37]. To evaluate the efficiency of the implemented model, five statistical indices, namely the coefficient of determination (R 2 ), mean absolute error (MAE), root mean square error (RMSE), relative absolute error (RAE in %), and root relative squared error (RRSE in %), were used to develop a color intensity ranking and present a visualized comparison of the results.…”

Section: Appl Sci 2019 9 4638 3 Of 26mentioning

confidence: 99%

Machine-Learning-Based Classification Approaches toward Recognizing Slope Stability Failure

et al. 2019

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In this paper, the authors investigated the applicability of combining machine-learning-based models toward slope stability assessment. To do this, several well-known machine-learning-based methods, namely multiple linear regression (MLR), multi-layer perceptron (MLP), radial basis function regression (RBFR), improved support vector machine using sequential minimal optimization algorithm (SMO-SVM), lazy k-nearest neighbor (IBK), random forest (RF), and random tree (RT), were selected to evaluate the stability of a slope through estimating the factor of safety (FOS). In the following, a comparative classification was carried out based on the five stability categories. Based on the respective values of total scores (the summation of scores obtained for the training and testing stages) of 15, 35, 48, 15, 50, 60, and 57, acquired for MLR, MLP, RBFR, SMO-SVM, IBK, RF, and RT, respectively, it was concluded that RF outperformed other intelligent models. The results of statistical indexes also prove the excellent prediction from the optimized structure of the ANN and RF techniques.

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Qualitative analysis of cost risk using WEKA program

Cited by 2 publications

References 1 publication

Management of environmental risks in highway construction projects in Sri Lanka

Management of environmental risks in highway construction projects in Sri Lanka

Machine-Learning-Based Classification Approaches toward Recognizing Slope Stability Failure

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