Environmental vulnerability assessment using Grey Analytic Hierarchy Process based model

Sahoo, Satiprasad; Dhar, Anirban; Kar, Amlanjyoti

doi:10.1016/j.eiar.2015.10.002

Cited by 121 publications

(61 citation statements)

References 15 publications

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“…Human bias and subjectivity in their judgments in forming pair-wise comparisons iv. Consensus measure, if context is same and a group of experts has divergent priorities To deal with above problems, AHP techniques can be extended to modified AHP -Bayesian approach, Fuzzy AHP, and Grey AHP Kar 2015;Sahoo et al 2016). Amonst these, fuzzy AHP is preferential, due to its simplicity and higher consistency (Junior et al 2014;Prakash and Barua 2015).…”

Section: Methodsmentioning

confidence: 99%

Barriers to the Development of Smart Cities in Indian Context

Luthra²,

et al. 2018

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Smart city development is gaining considerable recognition in the systematic literature and international policies throughout the world. The study aims to identify the key barriers of smart cities from a review of existing literature and views of experts in this area. This work further makes an attempt on the prioritisation of barriers to recognise the most important barrier category and ranking of specific barriers within the categories to the development of smart cities in India. Through the existing literature, this work explored 31 barriers of smart cities development and divided them into six categories. This research work employed fuzzy Analytic Hierarchy Process (AHP) technique to prioritise the selected barriers. Findings reveal that 'Governance' is documented as the most significant category of barriers for smart city development followed by 'Economic; 'Technology'; 'Social'; 'Environmental' and 'Legal and Ethical'. In this work, authors also performed sensitivity analysis to validate the findings of study. This research is useful to the government and policymakers for eradicating the potential interferences in smart city development initiatives in developing countries like India.

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Section: Methodsmentioning

confidence: 99%

Barriers to the Development of Smart Cities in Indian Context

Luthra²,

et al. 2018

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“…The weighted mapping relation need to be established between the main influence factors and the evaluation results in most of the existing methods [1][2][3][4]. The correlation studies [5][6][7][8] worked on grade evaluation of ecological environment by using fuzzy mathematics, gray theory, object-oriented theory and neural network methods. However, these methods are flawed, for example, low evaluation precision, especially it is difficult to determine a suitable network structure, and other drawbacks such as over learning and less learning problems, and local minimum problems [8].…”

Section: Introductionmentioning

confidence: 99%

The Eco-Environmental Fragility Assessment of Ningdong Base

Li¹,

Hu²,

Guo³

2017

Proceedings of the 2nd 2016 International Conference on Sustainable Development (ICSD 2016)

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Abstract-We select the Ningdong Energy and ChemistryIndustry Base (referred to as Ningdong Base) as research object and take the ecological environment as evaluating target. According to the subject and object factors, the SVM model of ecological environment vulnerability assessment is constructed by using principal component analysis method. We embed GA in SVM to optimize its structure and parameters. SVM model is simple, universal, and accurate, and it can be applied in evaluation of eco-environmental vulnerability in practice. Also, we compare our evaluation results with the the BP-ANN model's results. Then, we draw a conclusion that the ecological environment vulnerability of the Ningdong Base is the second level, which belongs to moderate vulnerability. Finally, the causes of vulnerability formation are analyzed.

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“…Wang and Li [39] adopted grey model for pavement smoothness prediction. Grey model was also used for the predictions in environmental vulnerability assessment [40], natural disasters [41] and road traffic [42], and so forth. GM (1, 1) (Grey Model First-Order One Variable) is one of the most widely used grey models in practical application [43].…”

Section: Introductionmentioning

confidence: 99%

Effects of Diatomite and SBS on Freeze-Thaw Resistance of Crumb Rubber Modified Asphalt Mixture

Wei

Jiao

2017

Advances in Materials Science and Engineering

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Asphalt mixture is susceptible to moisture damage under the effect of freeze-thaw (F-T) cycles. In this paper, crumb rubber (CR) was used to modify stone mastic asphalt (SMA) and the effects of diatomite and styrene butadiene styrene (SBS) on antifreezing performances of crumb rubber modified SMA (CRSMA) were investigated. Regression analysis and modified grey model (MGM) were used to construct the prediction models for properties of modified mixtures. CRSMA, CR and diatomite modified SMA (CRDSMA), and CR and SBS modified SMA (CRSSMA) were prepared in laboratory, respectively. Process of F-T cycles was designed. Air void, indirect tensile strength (ITS), and indirect tensile stiffness modulus (ITSM) were measured to evaluate the antifreezing performances of CRSMA, CRDSMA, and CRSSMA. Results indicate that air voids increase with the increasing of F-T cycles. ITS and ITSM all decrease with the increasing of F-T cycles. The addition of diatomite and SBS can reduce the air void and improve the ITS and ITSM of CRSMA. CRSSMA presents the lowest air void, highest tensile strength, and largest stiffness modulus, which reveals that CRSSMA has the best F-T resistance among three different kinds of mixtures. Moreover, MGM (1, 2) models present more favorable accuracy in prediction of air void and ITS compared with regression ones.

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Environmental vulnerability assessment using Grey Analytic Hierarchy Process based model

Cited by 121 publications

References 15 publications

Barriers to the Development of Smart Cities in Indian Context

Barriers to the Development of Smart Cities in Indian Context

The Eco-Environmental Fragility Assessment of Ningdong Base

Effects of Diatomite and SBS on Freeze-Thaw Resistance of Crumb Rubber Modified Asphalt Mixture

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