KEYWORDS: Reliability, Probability theory, Error analysis, Defense and security, Transform theory, Statistical analysis, Analytical research, Chemical analysis, System integration, Contamination
For the simplicity and utility, the traditional analytic hierarchy process (AHP) has been widely applied for multi-criteria decision-making. However, its index weight as well as the evaluation conclusion are still affected by the expert subjectivity. To solve this problem, our paper introduces the probability statistics theory to quantify the judgment qualities from different evaluation experts, and transforms the quantified qualities into expert reliabilities, and then optimizes the index-weight integration with the transformed expert reliabilities. Specifically, our method integrates the index weights with following steps. Firstly, using the traditional AHP, it calculates the evaluation values for all index weights according to each expert judgments respectively. Secondly, employing the probability statistics theory, it quantifies the judgment qualities from all experts. The quantified qualities are then transformed into expert reliabilities and expert weights. The transform rule is as followings: the larger reliability to those experts whose judgments have high quality, while smaller reliability to those experts whose judgments have low quality. Lastly, our method replaces the equal expert weight in the traditional AHP with the reliability-based expert weights. As a result, the expert subjectivity is decreased in the index-weight integration, and the evaluation conclusion becomes more creditable. The creditability is verified by experiments.
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