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Advantages and Disadvantages of the SAFE Model

SAFE uses fuzzy logic that does not require an explicit mathematical model to sum up volume indicators and can process both quantitative and qualitative information. Fuzzy logic often prevents the use of weights that are illheaded or cannot be extracted by the creator of the visualization. Moreover, SAFE is a rather simplistic model that respects the non-rewarding attribute and is the only flow that evaluates sustainability taking into account the value in the time dimension.

SAFE, on the other hand, has obvious drawbacks that can also be found in other models.

F: It is somewhat subjective and does not have a mechanism to limit the number of inputs to what is actually needed. There is an irreversible overlap in the display period. For example, the number of hospital beds overlaps with public health expenditures or city gross particulates, and urban N02 concentrations overlap with mortality from respiratory diseases. However, finding a causal model linking these indicators is indescribable.

Ratio: The rule base and membership features reflect the values, knowledge, and prejudices of those who invented them. SAFE'S rule base attaches the same importance to input variables as they are organized in a different team way without consulting an expert. The subjectivity of modeling is not surprising given that sustainability is not a concept responsible for a strict definition. This is a sample with all other sustainability models.

Seed: More work remains to improve the weighting and membership functions of non-delete indicators such as C02 emissions, nuclear and hazardous waste, biodiversity loss, government debt internals, etc. to capture new sustainability issues as reality changes.

Sample Study for the SAFE Model

SAFE for Energy Sustainability

It cannot be supported that a country's overall energy sustainability (OSUS) is a combination of two major components: ecological sustainability (ECOS) and human sustainability (HUMS). Ecological inputs consist of two auxiliary elements: air quality (AIR) and soil quality (LAND). The human component of energy sustainability is social (accessibility) and economic (production, consumption, security). Each secondary component is evaluated using a mandatory, non-delectable indicator that is an input to the system.

The order of data processing is similar to the original SAFE model.

  • • Misogynist data collection
  • • Normalization of [0,1]
  • • Exponential smoothing
  • • Data replacement
  • • Fuzzy
  • • Create sensitivity tweaks and visualizations
 
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