Mapping Causes and Implications of India’s Skewed Sex Ratio and Poverty problem using Fuzzy & Neutrosophic Relational Maps

Abstract

Numerous studies by different researchers have confirmed that the skewed sex ratio is a critical social problem in India. This enduring problem of gender imbalance is the collective result of factors like sex-selective abortion, gender discrimination, son preference for the preservation of tribe, the emergence of new technologies in the medical field, and many more factors. Another severe problem to be addressed in India is poverty. Many factors contribute to the perpetuation of poverty such as illiteracy, bad governance, underemployment and various other reasons. Despite of India's accelerated growth rate, poverty in India is still prevalent. This paper employs a new soft computing based methodology for identifying and analyzing the relationships among the causes and implications of the two challenging problems in India: unbalanced sex ratio and poverty. The methodology proposed by au-thors is based on Linked Fuzzy Relational Maps which is a variation to Fuzzy Relational Maps and Linked Neutrosophic Relational Maps which is a variation to Neutrosophic Relational Maps. The relationships among the causes and consequences can be easily drawn through the given methodologies. The authors have implemented two models for the two social problems under study, one using Fuzzy Relational Maps and the other using Neutrosophic Relational Maps. Neutrosophic Relational Maps can support decision making on uncertain and indeterminate data. Authors have demonstrated that the model implemented using Neutrosophic Relational Maps presents more realistic and sensitive results as compared to the model using Fuzzy Relational Maps.