Women Entrepreneurship Index Prediction Model with Automated Statistical Analysis

Recently, gender equality and women’s entrepreneurship have gained considerable attention in global economic development. Prior to the design of any policy interventions increase entrepreneurship, it is significant comprehend factors motivating women become entrepreneurs. The non-understanding can result endurance low living standards expensive ineffectual policies. But female involvement becomes higher developing economies compared developed economies. Women Entrepreneurship Index (WEI) plays a vital role determining that enable flourishment high potential entrepreneurs which enhances welfare contributes social fabric society. Therefore, needed an automated accurate WEI prediction model improve entrepreneurship. In this view, article develops statistical analysis enabled predictive (ASA-WEIP) model. proposed ASA-WEIP technique aims effectually determine WEI. encompasses series sub-processes such as pre-processing, prediction, parameter optimization. For WEI, makes use Deep Belief Network (DBN) model, optimization process takes place using Squirrel Search Algorithm (SSA). performance validation was executed benchmark dataset from Kaggle repository. experimental outcomes stated better over other existing techniques.