{
  "$schema": "https://ps-wiki.github.io/schema/v1/term.schema.json",
  "id": "performance-based-metrics",
  "title": "Performance-Based Metrics",
  "description": "Quantitative approaches for assessing system resilience.",
  "language": "en",
  "tags": [
    "resilience",
    "metrics",
    "ieee"
  ],
  "related": [
    "resilience",
    "non-storm-resilience-metric",
    "storm-resilience-metric"
  ],
  "aliases": [
    "Consequence-Based Metrics"
  ],
  "breaking": false,
  "dates": {
    "created": "2025-03-15",
    "last_modified": "2025-11-03"
  },
  "authors": [
    {
      "name": "Jinning Wang",
      "url": "https://jinningwang.github.io"
    }
  ],
  "content": {
    "sections": [
      {
        "order": 1,
        "id": "definition-in-an-ieee-technical-report-by-doe-gmlc",
        "title": "Definition in an IEEE Technical Report by DOE GMLC",
        "type": "definition",
        "source_keys": [
          "chiu2020resilience"
        ],
        "page": "p13",
        "body_md": "> Performance-based metrics (also known as **consequence-based metrics**) are generally quantitative approaches for answering the question, “How resilient is my system?”\n> These metrics interpret quantitative data that describe infrastructure performance during disruptive events.\n> The required data can be collected from historical events, subject matter estimates, and computational infrastructure models.\n> These metrics are suitable for benefit-cost and planning analyses because they measure the potential benefits and costs associated with proposed resilience improvements and investments.\n> Resilience metrics need to include a measure of consequences and the relevant statistical probability from the probability distribution of those consequences.\n"
      }
    ]
  }
}