基于前景理论的数据情报侦查决策研究

Research on Data Intelligence Investigation Decision Based on Prospect Theory

鉴于情报侦查决策属性指标的不确定性、有限理性情报侦查决策的局限性、情报侦查决策价值目标双边匹配的模糊性等突出数据情报侦查决策问题,引入基于前景理论的数据情报侦查决策研究范式。以前景理论数据情报侦查决策的内涵与属性为研究起点,提出其评价指标体系,构建其流程模型,并探讨了TOPSIS多属性决策算法、符号距离犹豫模糊数据决策算法、直觉模糊数据随机多准则算法、WSR偏好群决策算法、双参照点交叉决策算法和区间灰数多属性决策算法等应用方法。以帮助侦查人员提前预判数据情报侦查决策收益和损失的风险程度、动态自适应数据情报侦查决策价值目标的互相调度融合,创新和拓展不同数据情报侦查决策运算挖掘的优先级。

In view of the uncertainty of decision attribute index, the limitation of bounded rationality and the fuzziness of bilateral matching of value target of decision making of intelligence investigation, this article introduces a research paradigm of decision making of data intelligence investigation based on prospect theory. Based on the connotation and attribute of data intelligence investigation decision of prospect theory, the evaluation index system of data intelligence investigation decision of prospect theory is put forward, the flow model of data intelligence investigation decision of prospect theory is constructed, and the application method of data intelligence investigation decision of prospect theory is discussed. It aims to help investigators to predict the risk degree of profit and loss of data intelligence investigation decision in advance, and dynamically adapt to the mutual scheduling and fusion of value objectives of data intelligence investigation decision, innovate and expand the priority of different data intelligence investigation decision operation mining.