The main goal of informal computing is to overcome the limitations of hypersensitivity to defects and uncertainty while maintaining a balance between high accuracy,accessibility,and cost-effectiveness.This paper inves...The main goal of informal computing is to overcome the limitations of hypersensitivity to defects and uncertainty while maintaining a balance between high accuracy,accessibility,and cost-effectiveness.This paper investigates the potential applications of intuitionistic fuzzy sets(IFS)with rough sets in the context of sparse data.When it comes to capture uncertain information emanating fromboth upper and lower approximations,these intuitionistic fuzzy rough numbers(IFRNs)are superior to intuitionistic fuzzy sets and pythagorean fuzzy sets,respectively.We use rough sets in conjunction with IFSs to develop several fairly aggregation operators and analyze their underlying properties.We present numerous impartial laws that incorporate the idea of proportionate dispersion in order to ensure that the membership and non-membership activities of IFRNs are treated equally within these principles.These operations lead to the development of the intuitionistic fuzzy rough weighted fairly aggregation operator(IFRWFA)and intuitionistic fuzzy rough ordered weighted fairly aggregation operator(IFRFOWA).These operators successfully adjust to membership and non-membership categories with fairness and subtlety.We highlight the unique qualities of these suggested aggregation operators and investigate their use in the multiattribute decision-making field.We use the intuitionistic fuzzy rough environment’s architecture to create a novel strategy in situation involving several decision-makers and non-weighted data.Additionally,we developed a novel technique by combining the IFSs with quaternion numbers.We establish a unique connection between alternatives and qualities by using intuitionistic fuzzy quaternion numbers(IFQNs).With the help of this framework,we can simulate uncertainty in real-world situations and address a number of decision-making problems.Using the examples we have released,we offer a sophisticated and systematically constructed illustrative scenario that is intricately woven with the complexity ofmedical evaluation i展开更多
A recent defence of the material analysis of natural indicative conditionals is examined. This defence, it is argued, is initially plausible but ultimately flawed. The empirical and logical case against the material a...A recent defence of the material analysis of natural indicative conditionals is examined. This defence, it is argued, is initially plausible but ultimately flawed. The empirical and logical case against the material analysis of natural indicative conditionals is made. The empirical and logical arguments are overwhelming and the conclusion is inevitable: natural language indicatives are not material conditionals.展开更多
This paper presents 10-elements linguistic truth-valued intuitionistic fuzzy algebra and the properties based on the linguistic truth-valued implication algebra which is fit to express both comparable and incomparable...This paper presents 10-elements linguistic truth-valued intuitionistic fuzzy algebra and the properties based on the linguistic truth-valued implication algebra which is fit to express both comparable and incomparable information.This method can also deal with the uncertain problem which has both positive evidence and negative evidence at the same time.10-elements linguistic truthvalued intuitionistic fuzzy first-order logic system has been established in the intuitionistic fuzzy algebra.展开更多
基金funded by King Khalid University through a large group research project under Grant Number R.G.P.2/449/44.
文摘The main goal of informal computing is to overcome the limitations of hypersensitivity to defects and uncertainty while maintaining a balance between high accuracy,accessibility,and cost-effectiveness.This paper investigates the potential applications of intuitionistic fuzzy sets(IFS)with rough sets in the context of sparse data.When it comes to capture uncertain information emanating fromboth upper and lower approximations,these intuitionistic fuzzy rough numbers(IFRNs)are superior to intuitionistic fuzzy sets and pythagorean fuzzy sets,respectively.We use rough sets in conjunction with IFSs to develop several fairly aggregation operators and analyze their underlying properties.We present numerous impartial laws that incorporate the idea of proportionate dispersion in order to ensure that the membership and non-membership activities of IFRNs are treated equally within these principles.These operations lead to the development of the intuitionistic fuzzy rough weighted fairly aggregation operator(IFRWFA)and intuitionistic fuzzy rough ordered weighted fairly aggregation operator(IFRFOWA).These operators successfully adjust to membership and non-membership categories with fairness and subtlety.We highlight the unique qualities of these suggested aggregation operators and investigate their use in the multiattribute decision-making field.We use the intuitionistic fuzzy rough environment’s architecture to create a novel strategy in situation involving several decision-makers and non-weighted data.Additionally,we developed a novel technique by combining the IFSs with quaternion numbers.We establish a unique connection between alternatives and qualities by using intuitionistic fuzzy quaternion numbers(IFQNs).With the help of this framework,we can simulate uncertainty in real-world situations and address a number of decision-making problems.Using the examples we have released,we offer a sophisticated and systematically constructed illustrative scenario that is intricately woven with the complexity ofmedical evaluation i
文摘A recent defence of the material analysis of natural indicative conditionals is examined. This defence, it is argued, is initially plausible but ultimately flawed. The empirical and logical case against the material analysis of natural indicative conditionals is made. The empirical and logical arguments are overwhelming and the conclusion is inevitable: natural language indicatives are not material conditionals.
基金This work is partly supported by National Nature Science Foundation of China (Grant No.61105059,61175055,61173100), International Cooperation and Exchangeof the National Natural Science Foundation of China (Grant No.61210306079),Sichuan Key Technology Research and Development Program (Grant No.2011FZ0051),Radio Administration Bureau of MIIT of China (Grant No.[2011]146), China Institution of Communications (Grant No.[2011]051), and Sichuan Key Laboratory of Intelligent Network Information Processing (Grant No.SGXZD1002-10),Liaoning Excellent Talents in University (LJQ2011116).
文摘This paper presents 10-elements linguistic truth-valued intuitionistic fuzzy algebra and the properties based on the linguistic truth-valued implication algebra which is fit to express both comparable and incomparable information.This method can also deal with the uncertain problem which has both positive evidence and negative evidence at the same time.10-elements linguistic truthvalued intuitionistic fuzzy first-order logic system has been established in the intuitionistic fuzzy algebra.
