scholarly journals Risk Assessment of Drought Based on IEAPP-IDM in Qujing, Yunnan Province, China

2016 ◽  
Vol 2016 ◽  
pp. 1-10 ◽  
Author(s):  
Menghua Deng ◽  
Junfei Chen ◽  
Guiyun Liu ◽  
Huimin Wang
Keyword(s):  
Risk Assessment ◽  
Information Diffusion ◽  
Yunnan Province ◽  
Projection Pursuit ◽  
Assessment Model ◽  
Diffusion Method ◽  
Drought Risk ◽  
Risk Levels ◽  
Proposed Model ◽  
Drought Disaster

A new model for risk assessment of drought based on projection pursuit optimized by immune evolutionary algorithm and information diffusion method (IEAPP-IDM) was proposed. Due to the fact that drought risk assessment is a complex multicriteria and multilevel problem, the IEAPP-IDM model can project the multidimensional indicators of samples into one-dimension projection scores; then, the information carried by the projection scores was diffused into drought risk levels; finally, the drought disaster risk estimate was obtained. In the present study, Qujing was employed to assess the drought risk with the proposed model. The results showed that Xuanwei possessed higher risk, while Luliang and Zhanyi possessed lower risk. At the same time, the probability risk of drought in Malong and Luoping was increasing, while the probability risk of drought in in Qilin and Shizong was decreasing. The results obtained by the assessment model are consistent with the actual situation of Qujing and verify the model’s effectiveness. The study can provide scientific reference in drought risk management for Qujing and other places of China.

scholarly journals Risk Assessment of Agricultural Drought Disaster on the Huaibei Plain of China Based on the Improved Connection Number and Entropy Information Diffusion Method

Water ◽  
2020 ◽  
Vol 12 (4) ◽  
pp. 1089
Author(s):  
Menglu Chen ◽  
Shaowei Ning ◽  
Juliang Jin ◽  
Yi Cui ◽  
Chengguo Wu ◽  
...  
Keyword(s):  
Risk Assessment ◽  
Risk Management ◽  
Information Diffusion ◽  
Assessment Model ◽  
Agricultural Drought ◽  
Diffusion Method ◽  
Risk Assessment Model ◽  
Connection Number ◽  
Entropy Information ◽  
Drought Disaster

In recent years, drought disaster has occurred frequently in China, causing significant agricultural losses. It is increasingly important to assess the risk of agricultural drought disaster (ADD) and to develop a targeted risk management approach. In this study, an ADD risk assessment model was established. First, an improved fuzzy analytic hierarchy process based on an accelerated genetic algorithm (AGA-FAHP) was used to build an evaluation indicator system. Then, based on the indicators, the ADD assessment connection numbers were established using the improved connection number method. Finally, the entropy information diffusion method was used to form an ADD risk assessment model. The model was applied to the Huaibei Plain in Anhui Province (China), with the assessment showing that, in the period from 2008 to 2017, the plain was threatened continuously by ADD, especially during 2011–2013. The risk assessment showed that southern cities of the study area were nearly twice as likely to be struck by ADD as northern cities. Meanwhile, the eastern region had a higher frequency of severe and above-grade ADD events (once every 21 years) than the western region (once every 25.3 years). Therefore, Huainan was identified as a high-risk city and Huaibei as a low-risk city, with Suzhou and Bengbu more vulnerable to ADD than Fuyang and Bozhou. Understanding the spatial dynamics of risk in the study area can improve agricultural system resilience by optimizing planting structures and by enhancing irrigation water efficiency. This model could be used to provide support for increasing agricultural drought disaster resilience and risk management efficiency.

scholarly journals Dynamic Risk Assessment of Compound Hazards Based on VFS-IEM-IDM: A Case Study of Typhoon-Rainstorm Hazards in Shenzhen, China

2021 ◽  
Author(s):  
Wenwu Gong ◽  
Jie Jiang ◽  
Lili Yang
Keyword(s):  
Risk Assessment ◽  
Information Diffusion ◽  
Comprehensive Evaluation ◽  
Assessment Model ◽  
Diffusion Method ◽  
Economic Losses ◽  
Data Sets ◽  
Conditional Probability Distribution ◽  
Dynamic Risk Assessment

Abstract. Typhoons and rainstorms are types of natural hazards that can cause significant impacts. These individual hazards may also occur simultaneously to produce compound hazards, leading to increased losses. The accurate risk assessment of such compound hazards faces several challenges due to the uncertainties in multiple hazards level evaluation, and the incomplete information in historical data sets. In this paper, to deal with these challenges, we propose a risk assessment model called VFS-IEM-IDM based on the Variable Fuzzy Set and Information Diffusion Method. In particular, VFS-IEM-IDM provides a comprehensive evaluation of the compound hazards level, and a predictive cumulative logistic model is used to verify the results. Furthermore, VFS-IEM-IDM applies a normal information diffusion estimator to estimate the conditional probability distribution and the vulnerability distribution of the compound hazards based on the hazards level, the hazards occurrence time, and the corresponding losses. To examine the efficacy of VFS-IEM-IDM, a case study of the Typhoon-Rainstorm hazards that occurred in Shenzhen, China is presented. The risk assessment results indicate that hazards of level Ⅱ mostly occur in August and October, while hazards of level Ⅲ often occur in September. The risk of the Typhoon-Rainstorm hazards differs in each month and in August and September the risk gets the highest value, and the estimated economic losses are around 114 million RMB and 167 million RMB respectively.

scholarly journals Using Multiple Index Comprehensive Method to Assess Urban Rainstorm Disasters Risk in Jiangsu Province, China

2019 ◽  
Author(s):  
Junfei Chen ◽  
Mengchen Chen ◽  
Pei Zhou
Keyword(s):  
Information Diffusion ◽  
Rainfall Intensity ◽  
Jiangsu Province ◽  
Diffusion Method ◽  
Risk Level ◽  
Risk Levels ◽  
Comprehensive Method ◽  
Proposed Model ◽  
Higher Sensitivity ◽  
Variable Fuzzy Sets

A new model for risk assessment of urban rainstorm disasters, based on information diffusion method and variable fuzzy sets (IDM-VFS) was proposed. In addition, an integrated index system of urban rainstorm risk was established. In the proposed model, IDM was employed to calculate the classification standards of urban rainstorm risk levels, then the VFS was adopted to assess the dangerousness, sensitivity, vulnerability and comprehensive risk of urban rainstorm disasters. In the present study, the urban rainstorm risk of Jiangsu province was evaluated with the proposed model. The results show that Wuxi, Changzhou, Nanjing and Suzhou have higher dangerousness, due to sustained rainfall and strong rainfall intensity in short duration; Wuxi, Changzhou and Nanjing have higher sensitivity because of lower disaster resistance ability; and Wuxi and Suzhou have higher vulnerability because these cities have higher potential losses in face of urban rainstorm disasters. The comprehensive risk zoning map of urban rainstorm shows apparent regional characteristics: the northwestern cities have lower risk than the southern cities. Moreover, most cities of the Jiangsu province are of the moderate urban rainstorm risk level. The results are consistent with the actual situation of Jiangsu province, and the study can provide some decision-making references for the urban rainstorm management.

scholarly journals PROPOSING A NEW METHODOLOGY BASED ON FUZZY LOGIC FOR TUNNELLING RISK ASSESSMENT

2014 ◽  
Vol 20 (1) ◽  
pp. 82-94 ◽  
Author(s):  
Abdolreza Yazdani-Chamzini
Keyword(s):  
Risk Assessment ◽  
Fuzzy Inference ◽  
Assessment Model ◽  
Tunnel Construction ◽  
Construction Operations ◽  
Protective Measures ◽  
Inference System ◽  
Proposed Model ◽  
Mine Development ◽  
Civil Defence

Tunnels are artificial underground spaces that provide a capacity for particular goals such as storage, under-ground transportation, mine development, power and water treatment plants, civil defence. This shows that the tunnel construction is a key activity in developing infrastructure projects. In many situations, tunnelling projects find themselves involved in the situations where unexpected conditions threaten the continuity of the project. Such situations can arise from the prior knowledge limited by the underground unknown conditions. Therefore, a risk analysis that can take into account the uncertainties associated with the underground projects is needed to assess the existing risks and prioritize them for further protective measures and decisions in order to reduce, mitigate and/or even eliminate the risks involved in the project. For this reason, this paper proposes a risk assessment model based on the concepts of fuzzy set theory to evaluate risk events during the tunnel construction operations. To show the effectiveness of the proposed model, the results of the model are compared with those of the conventional risk assessment. The results demonstrate that the fuzzy inference system has a great potential to accurately model such problems.

Dynamic safety prewarning mechanism of human–machine–environment using computer vision

2020 ◽  
Vol 27 (8) ◽  
pp. 1813-1833 ◽  
Author(s):  
Wenpei Xu ◽  
Ting-Kwei Wang
Keyword(s):  
Risk Assessment ◽  
Computer Vision ◽  
Expert Knowledge ◽  
Safety Information ◽  
Assessment Model ◽  
Risk Indicators ◽  
Risk Assessment Model ◽  
Content Type ◽  
Risk Levels

PurposeThis study provides a safety prewarning mechanism, which includes a comprehensive risk assessment model and a safety prewarning system. The comprehensive risk assessment model is capable of assessing nine safety indicators, which can be categorised into workers’ behaviour, environment and machine-related safety indicators, and the model is embedded in the safety prewarning system. The safety prewarning system can automatically extract safety information from surveillance cameras based on computer vision, assess risks based on the embedded comprehensive risk assessment model, categorise risks into five levels and provide timely suggestions.Design/methodology/approachFirstly, the comprehensive risk assessment model is constructed by adopting grey multihierarchical analysis method. The method combines the Analytic Hierarchy Process (AHP) and the grey clustering evaluation in the grey theory. Expert knowledge, obtained through the questionnaire approach, contributes to set weights of risk indicators and evaluate risks. Secondly, a safety prewarning system is developed, including data acquisition layer, data processing layer and prewarning layer. Computer vision is applied in the system to automatically extract real-time safety information from the surveillance cameras. The safety information is then processed through the comprehensive risk assessment model and categorized into five risk levels. A case study is presented to verify the proposed mechanism.FindingsThrough a case study, the result shows that the proposed mechanism is capable of analyzing integrated human-machine-environment risk, timely categorising risks into five risk levels and providing potential suggestions.Originality/valueThe comprehensive risk assessment model is capable of assessing nine risk indicators, identifying three types of entities, workers, environment and machine on the construction site, presenting the integrated risk based on nine indicators. The proposed mechanism, which adopts expert knowledge through Building Information Modeling (BIM) safety simulation and extracts safety information based on computer vision, can perform a dynamic real-time risk analysis, categorize risks into five risk levels and provide potential suggestions to corresponding risk owners. The proposed mechanism can allow the project manager to take timely actions.

Developing a fuzzy risk assessment model for guaranteed maximum price and target cost contracts in South Australia

Facilities ◽  
2014 ◽  
Vol 32 (11/12) ◽  
pp. 624-646 ◽  
Author(s):  
Daniel W.M. Chan ◽  
Joseph H.L. Chan ◽  
Tony Ma
Keyword(s):  
Risk Factors ◽  
Risk Assessment ◽  
Construction Projects ◽  
South Australia ◽  
Assessment Model ◽  
Risk Assessment Model ◽  
Content Type ◽  
Risk Levels ◽  
Target Cost ◽  
Fuzzy Risk Assessment

Purpose – This paper aims to develop a fuzzy risk assessment model for construction projects procured with target cost contracts and guaranteed maximum price contracts (TCC/GMP) using the fuzzy synthetic evaluation method, based on an empirical questionnaire survey with relevant industrial practitioners in South Australia. Design/methodology/approach – A total of 34 major risk factors inherent with TCC/GMP contracts were identified through an extensive literature review and a series of structured interviews. A questionnaire survey was then launched to solicit the opinions of industrial practitioners on risk assessment of such risk factors. Findings – The most important 14 key risk factors after the computation of normalised values were selected for undertaking fuzzy evaluation analysis. Five key risk groups (KRGs) were then generated in descending order of importance as: physical risks, lack of experience of contracting parties throughout TCC/GMP procurement process, design risks, contractual risks and delayed payment on contracts. These survey findings also revealed that physical risks may be the major hurdle to the success of TCC/GMP projects in South Australia. Practical implications – Although the fuzzy risk assessment model was developed for those new-build construction projects procured by TCC/GMP contracts in this paper, the same research methodology may be applied to other contracts within the wide spectrum of facilities management or building maintenance services under the target cost-based model. Therefore, the contribution from this paper could be extended to the discipline of facilities management as well. Originality/value – An overall risk index associated with TCC/GMP construction projects and the risk indices of individual KRGs can be generated from the model for reference. An objective and a holistic assessment can be achieved. The model has provided a solid platform to measure, evaluate and reduce the risk levels of TCC/GMP projects based on objective evidence instead of subjective judgements. The research methodology could be replicated in other countries or regions to produce similar models for international comparisons, and the assessment of risk levels for different types of TCC/GMP projects (including new-build or maintenance) worldwide.

scholarly journals Population-split-based risk assessment model of venous thromboembolism in Chinese medical inpatients

2022 ◽  
Author(s):  
Xin Wang ◽  
yuqing yang ◽  
Xinyu Hong ◽  
Sihua Liu ◽  
Jianchu Li ◽  
...  
Keyword(s):  
Risk Assessment ◽  
Venous Thromboembolism ◽  
Assessment Model ◽  
Training Data ◽  
Risk Assessment Model ◽  
Medical Department ◽  
College Hospital ◽  
Medical College ◽  
Proposed Model ◽  
Medical Inpatients

Objective Inpatients with high risk of venous thromboembolism (VTE) usually face serious threats to their health and economic conditions. Many studies using machine learning (ML) models to predict VTE risk neglected an important statistical phenomenon, "fuzzy feature", and achieved inferior results. Considering the effect of "fuzzy feature", our study aims to develop a VTE risk assessment model suitable for Chinese medical inpatients. Materials and Methods Inpatients in the medical department of Peking Union Medical College Hospital (PUMCH) from January 2014 to June 2016 were collected. A new ML VTE risk assessment model was built through population splitting. First patients were classified into different groups based on values of VTE risk factors, then trustless groups were filtered out, and finally ML models were built on training data in unit of groups. Predictive performances of our method, five traditional ML models, and the Padua model were compared. Results The "fuzzy feature" was verified on the whole dataset. Compared with the Padua model, the proposed model showed higher sensitivities and specificities on training data, and higher specificities and similar sensitivities on test data. Standard deviations of predictive validity of five ML models were larger than the proposed model. Discussion The proposed model was the only one which showed advantages on both sensitivity and specificity over Padua model. Its robustness was better than traditional ML models. Conclusion This study built a population-split-based ML model of VTE for Chinese medical inpatients and it may help clinicians stratify VTE risk and guide prevention more efficiently.

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