The aim of this paper is to propose the generalized version of the multipolar neutrosophic soft set with operations and basic properties. Here, we define the AND, OR, Truth-Favorite, and False-Favorite operators along with their properties. Also, we define the necessity and possibility of operations for them. Later on, to extend it to solve the decision-making problems, we define some information measures such as distance, similarity, and correlation coefficient for the generalized multipolar neutrosophic soft set. Several desirable properties and their relationship between them are derived. Finally, based on these information measures, a decision-making algorithm is stated under the neutrosophic environment to tackle the uncertain and vague information. The applicability of the proposed algorithm is demonstrated through a case study of the medical-diagnosis and the decision-making problems. A comparative analysis with several existing studies reveals the effectiveness of the approach.

中文翻译：

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带有信息量度的广义多极中智软集算法，用于解决医学诊断和决策问题

本文的目的是提出具有操作和基本属性的多极中智软集的广义版本。在这里，我们定义AND，OR，True-Favorite和False-Favorite运算符及其属性。另外，我们定义了对其进行操作的必要性和可能性。后来，为了扩展它来解决决策问题，我们为广义多极中智软集定义了一些信息度量，例如距离，相似性和相关系数。得出了几个理想的特性及其之间的关系。最后，基于这些信息度量，提出了一种在中智环境下的决策算法，以解决不确定和模糊的信息。通过对医学诊断和决策问题的案例研究，证明了该算法的适用性。与一些现有研究的比较分析显示了该方法的有效性。