An integrated Shannon's Entropy–TOPSIS methodology for environmental risk assessment of Helleh protected area in Iran

Jozi, Seyed Ali; Shafiee, Mohsen; MoradiMajd, N.; Saffarian, Shabnam

doi:10.1007/s10661-011-2468-x

Cited by 59 publications

(15 citation statements)

References 21 publications

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“…The value of non-reliance or diversification (1-wj) was calculated. Non-reliance or diversification (1-wj) obtained from data for criterion j indicated to what extent the useful information was placed at the disposal of the decision maker for decision making 34 . The value of weight vector wj was obtained in the following way: wj = ;…”

Section: So H =mentioning

confidence: 99%

Performance Appraisal of Select Nations in Mitigation of COVID-19 Pandemic using Entropy based TOPSIS Method

Neogi

2021

Ciênc. saúde coletiva

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The present study was an effort to assess the mitigation interventions carried out, so far, by the nations to fight the pandemic COVID-19. The novelty of the study was that it had considered the issue of pandemic mitigation strategy as a decision making problem. The performances of the twenty nations were to be ranked. The problem considered in the study was essentially a Multi-Criteria Decision Analysis (MCDA) problem. The available alternatives were the 20 countries and the 8 traits were the criteria. The Technique of Order Preference Similarity to the Ideal Solution (TOPSIS) was used in the present study. The study used Entropy method for assignment of weights to all the criteria. The performance score obtained in respect of the countries considered in the study and the corresponding ranks indicated the relative performances of the countries in their efforts to mitigate the COVID-19 pandemic. The results show that New Zealand is the best performing country and India is the worst one. Brazil ranked 17th, while the rank of UK was 15. The performance of the USA stood at 18th position.

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Section: So H =mentioning

confidence: 99%

Performance Appraisal of Select Nations in Mitigation of COVID-19 Pandemic using Entropy based TOPSIS Method

Neogi

2021

Ciênc. saúde coletiva

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“…An integrated model was developed using the technique for the order of preference by similarity to ideal solution(TOPSIS), Shannon Entropy and Delphi methods for identification of environmental risk in Iran. Shannon Entropy method was used for the calculation of weights of criteria [12].…”

Section: Related Workmentioning

confidence: 99%

Multiclass Model for Agriculture Development Using Multivariate Statistical Method

et al. 2020

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Mahalanobis taguchi system (MTS) is a multi-variate statistical method extensively used for feature selection and binary classification problems. The calculation of orthogonal array and signalto-noise ratio in MTS makes the algorithm complicated when more number of factors are involved in the classification problem. Also the decision is based on the accuracy of normal and abnormal observations of the dataset. In this paper, a multiclass model using Improved Mahalanobis Taguchi System (IMTS) is proposed based on normal observations and Mahalanobis distance for agriculture development. Twentysix input factors relevant to crop cultivation have been identified and clustered into six main factors for the development of the model. The multiclass model is developed with the consideration of the relative importance of the factors. An objective function is defined for the classification of three crops, namely paddy, sugarcane and groundnut. The classification results are verified against the results obtained from the agriculture experts working in the field. The proposed classifier provides 100% accuracy, recall, precision and 0% error rate when compared with other traditional classifier models.

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“…Nonreliance or deviation ( ) obtained from data for attribute states that the relevant attribute is how much useful information is placed at the disposal of the decisionmaker for decision-making. The value of is obtained in the following equation [38]:…”

Section: Constructing and Normalizing Diagnostic Decisionmentioning

confidence: 99%

Dynamic Diagnosis Strategy for Redundant Systems Based on Reliability Analysis and Sensors under Epistemic Uncertainty

Duan

Jiang

2015

Journal of Sensors

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Fault tolerant technology is often used to improve systems reliability. However, high reliability makes it difficult to get sufficient fault samples, resulting in epistemic uncertainty, which increases significantly challenges in these systems diagnosis. A novel dynamic diagnosis strategy for complex systems is proposed to improve the diagnostic efficiency in the paper, which makes full use of dynamic fault tree, Bayesian networks (BN), fuzzy sets theory, and TOPSIS. Specifically, it uses a dynamic fault tree to model dynamic fault modes and evaluates the failure rates of the basic events using fuzzy sets to deal with epistemic uncertainty. Furthermore, it generates qualitative structure information based on zero-suppressed binary decision diagrams and calculates quantitative parameters provided by reliability analysis using a hybrid approach. Additionally, sensors data are incorporated to update the qualitative information and quantitative parameters. Qualitative information, quantitative parameters, and previous diagnosis result are taken into account to design a new dynamic diagnosis strategy which can locate the fault at the lowest cost. Finally, a case study is given to verify the developed approach and to demonstrate its effectiveness.

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An integrated Shannon's Entropy–TOPSIS methodology for environmental risk assessment of Helleh protected area in Iran

Cited by 59 publications

References 21 publications

Performance Appraisal of Select Nations in Mitigation of COVID-19 Pandemic using Entropy based TOPSIS Method

Performance Appraisal of Select Nations in Mitigation of COVID-19 Pandemic using Entropy based TOPSIS Method

Multiclass Model for Agriculture Development Using Multivariate Statistical Method

Dynamic Diagnosis Strategy for Redundant Systems Based on Reliability Analysis and Sensors under Epistemic Uncertainty

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