Flood risk zoning using a rule mining based on ant colony algorithm

Lai, Chengguang; Shao, Quanxi; Chen, Xiaohong; Wang, Zhaoli; Zhou, Xiaowen; Yang, Bing; Zhang, Lilan

doi:10.1016/j.jhydrol.2016.09.003

Cited by 85 publications

(44 citation statements)

References 44 publications

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“…The land use and land cover composition of the area was computed from remote sensing data and is shown in Table . The integrated run‐off coefficient is based on the land use pattern and the corresponding run‐off yield rate (Lai, Shao, Chen, et al, ). As seen in Table , urban areas and green land have expanded continuously over the last decades, whereas bare land and cropland have decreased, resulting in a minimal decrease in the integrated run‐off coefficient.…”

Section: Study Area and Datamentioning

confidence: 99%

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Impacts of small cascaded hydropower plants on river discharge in a basin in Southern China

Chen

Lilan

et al. 2019

Hydrological Processes

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The run‐off volume altered by the construction of hydropower plants affects ecohydrological processes in catchments. Although the impacts of large hydropower plants have been well documented in the literature, few studies have been conducted on the impacts of small cascaded hydropower plants (SCHPs). To evaluate the impacts of SCHPs on river flow, we chose a representative basin affected by hydropower projects and, to a lesser degree, by other human activities, that is, the Qiuxiang River basin in Southern China. The observed river discharge and climate data during the period of 1958–2016 were investigated. The datasets were divided into a low‐impact period and a high‐impact period based on the number of SCHPs and the capacities of the reservoirs. The daily river discharge alteration was assessed by applying the Indicators of Hydrologic Alteration. To separate the impact of the SCHPs on the local river discharge from that of climate‐related precipitation, the back‐propagation neural network was used to simulate the monthly average river discharge process. An abnormal result was found: Unlike large reservoirs in large watersheds, the SCHPs regulated the flows during the flood season but were not able to mitigate the droughts during the dry season due to their limited storage and the commonly occurring inappropriate interregulations of the SCHPs. The SCHPs also reduced the annual average river discharge in the research basin. The contribution of the SCHPs to the river discharge changes was 85.37%, much higher than the contributions of climate change (13.43%) and other human activities (1.20%). The results demonstrated that the impacts of the SCHPs were different from those of large dams and reservoirs that regulate floods and relieve droughts. It is necessary to raise the awareness of the impacts of these river barriers.

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Section: Study Area and Datamentioning

confidence: 99%

“…The land use and land cover composition of the area was computed from remote sensing data and is shown in Table 1. The integrated run-off coefficient is based on the land use pattern and the corresponding run-off yield rate (Lai, Shao, Chen, et al, 2016). As seen in (Figure 3).…”

Section: Study Area and Datamentioning

confidence: 99%

Impacts of small cascaded hydropower plants on river discharge in a basin in Southern China

Chen

Lilan

et al. 2019

Hydrological Processes

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“…The ACO based classification algorithm has some advantage over traditional statistical techniques because they do not need any information about the distribution of the data (Omkar & Karanth, 2008). Also, because of its strong robustness, adaptability and positive feedback mechanism, the ACO based classification algorithm has attracted much attention in the research community and has been successfully applied to many problems such as the hierarchical classification of proteins (Costa, Lorena, Carvalho, Freitas, & Holden, 2007), the transition rules of cellular automata (Liu, Li, Yeh, He, & Tao, 2007), the classification of acoustic emission signals (Omkar & Karanth, 2008), the classification of remote sensing images (Liu, Li, Liu, He, & Ai, 2008) and flood risk zoning (Lai et al, 2016). These applications show that the ACO based classification algorithm has great advantages in solving classification problems.…”

Section: Ant Colony Optimizationmentioning

confidence: 99%

Churn prediction in Turkey's telecommunications sector: A proposed multiobjective–cost‐sensitive ant colony optimization

Özmen

Aydoğan

Delice

et al. 2019

WIREs Data Min & Knowl

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Players in the telecommunications sector struggle against the competition to keep customers, and therefore they need effective churn management. Most classification algorithms either ignore misclassification cost or assume that the costs of all incorrect classification errors are equal. But as in real life, many classification problems have different misclassification costs and this difference cannot be ignored. For this reason, studies on cost‐sensitive classification approaches have gained importance in recent years. The characteristics of telecommunications datasets such as high dimensionality and imbalance are making it difficult to achieve the desired performance for churn prediction. By taking this into consideration, we propose a multiobjective–cost‐sensitive ant colony optimization (MOC‐ACO‐Miner) approach which integrates the cost‐based nondominated sorted genetic algorithm feature selection and multiobjective ACO based cost‐sensitive learning. MOC‐ACO‐Miner is applied to one of Turkey's top 100 information technology companies for customer churn‐prediction. Finally, experiments find out that the model performs quite well with the area under receiver operating characteristic curve values of 0.9998 for predicting churners and therefore it can be beneficial for the highly competitive telecommunications sector. This article is categorized under: Algorithmic Development > Association Rules Application Areas > Industry Specific Applications Technologies > Prediction Technologies > Data Preprocessing

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“…The index selection varies among study areas according to the specific characteristics of each location [71]. One index can have significant impacts on the landslide susceptibility in a specific area but may have a limited influence in another area.…”

Section: Data and Pre-processingmentioning

confidence: 99%

GIS-Based Random Forest Weight for Rainfall-Induced Landslide Susceptibility Assessment at a Humid Region in Southern China

Wang

Bai

et al. 2018

Water

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Landslide susceptibility assessment is presently considered an effective tool for landslide warning and forecasting. Under the assessment procedure, a credible index weight can greatly increase the rationality of the assessment result. Using the Beijiang River Basin, China, as a case study, this paper proposes a new weight-determining method based on random forest (RF) and used the weighted linear combination (WLC) to evaluate the landslide susceptibility. The RF weight and eight indices were used to construct the assessment model. As a comparison, the entropy weight (EW) and weight determined by analytic hierarchy process (AHP) were also used, respectively, to demonstrate the rationality of the proposed weight-determining method. The results show that: (1) the average error rates of training and testing based on RF are 18.12% and 15.83%, respectively, suggesting that the RF model can be considered rational and credible; (2) RF ranks the indices elevation (EL), slope (SL), maximum one-day precipitation (M1DP) and distance to fault (DF) as the Top 4 most important of the eight indices, occupying 73.24% of the total, while the indices runoff coefficient (RC), normalized difference vegetation index (NDVI), shear resistance capacity (SRC) and available water capacity (AWC) are less consequential, with an index importance degree of only 26.76% of the total; and (3) the verification of landslide susceptibility indicates that the accuracy rate based on the RF weight reaches 75.41% but are only 59.02% and 72.13% for the other two weights (EW and AHP), respectively. This paper shows the potential to provide a new weight-determining method for landslide susceptibility assessment. Evaluation results are expected to provide a reference for landslide management, prevention and reduction in the studied basin.

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Flood risk zoning using a rule mining based on ant colony algorithm

Cited by 85 publications

References 44 publications

Impacts of small cascaded hydropower plants on river discharge in a basin in Southern China

Impacts of small cascaded hydropower plants on river discharge in a basin in Southern China

Churn prediction in Turkey's telecommunications sector: A proposed multiobjective–cost‐sensitive ant colony optimization

GIS-Based Random Forest Weight for Rainfall-Induced Landslide Susceptibility Assessment at a Humid Region in Southern China

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