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Goal Model Evaluation Based on State-Space Representation
DOI:10.1109/ACCESS.2020.3037210.png)
摘要
En 中文
Goal models have been used for the last two decades in various disciplines to represent business, organizations, and individuals' objectives. Several methodologies and standards have emerged, and various goal analysis and evaluation algorithms have been introduced serving different sectors, including decision support. In contrast to most researches which are based mainly on simulation to predict the satisfaction levels of final goals, this research proposes a new framework for evaluating goal models based on the state-space representation that is used extensively in control systems. This new approach brings the theories and literature of state-space representation of systems to goal models, opening a new direction for using its available mature techniques and tools, for goal model analysis and evaluation. A hypothetical goal model, which can be used for policymaking after the COVID-19 pandemic, is presented as an example of how the proposed framework can be used, and the results that can be obtained.
Keyword:
Goal model
goal modeling
goal model evaluation
goal model reasoning
AI总结
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期刊
IF:
3.6
论文数:
9.8W
被引数:
29.4W
机构
引用论文
SciPy 1.0: fundamental algorithms for scientific computing in PythonSciPy 1.0: Python中科学计算的基本算法
NATURE METHODS
IF32.1

