The study’s goal is to evaluate how microfinance initiatives affect women’s empowerment in Bangladesh. For this study, we analyzed data on a variety of women’s empowerment-related issues, including both beneficial and detrimental elements that stand in the way of women’s empowerment. Therefore, in order to accomplish the specified goal, we choose a suitable and intentional methodology. We employ diverse data gathering approaches to examine the gathered data and achieve the primary goal of the research project. It presents the positive effects of microfinance on women, such as (1) the enhancement of women’s authority in financial affairs; and (2) the augmentation of their ability to make decisions in household; and (3) community matters following their participation in the microfinance program. This also provides an analysis of the data pertaining to the adverse effects of microfinance on women. It examines how women encounter various challenges and engage in unethical behaviors after obtaining a loan, leading to heightened levels of stress following their participation in the microfinance program. This study looks into the advantages and disadvantages of Grameen Bank’s microcredit program for women. A questionnaire gathered primary data for this study from women participating in the microfinance program in Gopalgonj. To collect information and comprehend respondent behavior, I used case study, analytical and descriptive study design. Regression analysis, correlation, and percentage are used to examine the data. The findings indicate that women’s decision-making skills have improved due to their financial stability, but they have also experienced increased life challenges and high levels of stress.

This study aims to compare investment in human capital, equality of gender education in Kuwait before and after adopting SDG 4 and SDG 5 in 2015. It also aims to assess the effect of women’s empowerment on economic growth. To achieve this objective, published data on the State of Kuwait were collected from the World Bank DataBank between 1992 and 2022 and from the Central Bank of Kuwait. The study employed autoregressive distributed lag (ARDL) to determine the impact of women’s empowerment on economic development. The analysis results revealed that the State of Kuwait provided high-quality education for both genders. The results also showed that women are more educated than men. However, this was not reflected in the role of women in the country’s politics, as their participation in parliament and government is still limited. Similarly, women’s participation in business and economic activities is still limited. Finally, the results of the ARDL test showed that women’s education and their political, business, and economic empowerment affect economic development in the short and long run.

Among contemporary computational techniques, Artificial Neural Network (ANN) and Adaptive Neuro-Fuzzy Inference System (ANFIS) are favoured because of their capacity to tackle non-linear modelling and complex stochastic datasets. Nondeterministic models involve some computational intricacies when deciphering real-life problems but always yield better outcomes. For the first time, this study utilized the ANN and ANFIS models for modelling power generation/electric power output (EPO) from databases generated in a combined cycle power plant (CCPP). The study presents a comparative study between ANNs and ANFIS to estimate the power output generation of a combined cycle power plant in Turkey. The inputs of the ANN and ANFIS models are ambient temperature (AT), ambient pressure (AP), relative humidity (RH), and exhaust vacuum (V), correlated with electric power output. Several models were developed to achieve the best architecture as the number of hidden neurons varied for the ANNs, while the training process was conducted for the ANFIS model. A comparison of the developed hybrid models was completed using statistical criteria such as the coefficient of determination (R²), mean average error (MAE), and average absolute deviation (AAD). The R² of 0.945, MAE of 3.001%, and AAD of 3.722% for the ANN model were compared to those of R² of 0.9499, MAE of 2.843% and AAD of 2.842% for the ANFIS model. Even though both ANN and ANFIS are relevant in estimating and predicting power production, the ANFIS model exhibits higher superiority compared to the ANN model in accurately estimating the EPO of the CCPP located in Turkey and its environment.