A Real-Time Electrical Load Forecasting in Jordan Using an Enhanced Evolutionary Feedforward Neural Network.

Power system planning and expansion start with forecasting the anticipated future load requirement. Load forecasting is essential for the engineering perspective and a financial perspective. It effectively plays a vital role in the conventional monopolistic operation and electrical utility planning to enhance power system operation, security, stability, minimization of operation cost, and zero emissions. Two Well-developed cases are discussed here to quantify the benefits of additional models, observation, resolution, data type, and how data are necessary for the perception and evolution of the electrical load forecasting in Jordan. Actual load data for more than a year is obtained from the leading electricity company in Jordan. These cases are based on total daily demand and hourly daily demand. This work's main aim is for easy and accurate computation of week ahead electrical system load forecasting based on Jordan's current load measurements. The uncertainties in forecasting have the potential to waste money and resources. This research proposes an optimized multi-layered feed-forward neural network using the recent Grey Wolf Optimizer (GWO). The problem of power forecasting is formulated as a minimization problem. The experimental results are compared with popular optimization methods and show that the proposed method provides very competitive forecasting results.

A deterministic model for the inventory policy of countries for procurement of vaccines.

The countries are the units that procure the vaccines during the COVID-19 pandemic. The delivered quantities are huge. The countries must bear the inventory holding cost according to the variation of stock quantities. This cost depends on the speed of the vaccination in the country. This speed is time-dependent. The vaccinated portion of the population can be approximated by the cumulative distribution function of the Cauchy distribution. A model is provided for determining the minimal-cost inventory policy and its optimality conditions are provided. The model is solved for 20 countries for different numbers of procurements. The results reveal the individual behavior of each country.

Total Demand, Use and Unmet Need for Modern Contraceptives Among Women Living in Informal Settlements in Kira Municipality, Wakiso District, Uganda. Implications for Urban Health.

Background: Update and utilization of modern contraceptives has public health benefits including reduction of unintended pregnancies, unsafe abortions, and related maternal mortality. However, paucity of evidence on key indicators of family planning in the informal settlements abounds. Data are usually collapsed within the larger urban communities that tend to mask peculiarities of informal settlements. This study determined the proportion of women using modern contraceptives, the unmet need for modern contraceptives and the total demand in informal settlements of an urban municipality. Methods: A cross-sectional study conducted among 626 women in the reproductive age (15-49 years) in the informal settlements of Kira municipality (part of metropolitan Kampala). Multi-stage sampling was applied in the selection of the respondents. Descriptive and log-binomial regression analysis were conducted to determine percentage of women using modern contraceptives, unmet need, and total demand with their associated factors. All analyses were conducted using STATA version 15.0. Results: The total demand for modern contraceptives was 84.9%, modern contraceptive prevalence was 47.4% nearly meeting the national target of 50%, however the unmet need was 37.3%, which much higher than the national target of 10%. Lower total demand for contraceptives was associated with higher women's education status and preference to have another child, while higher total demand was associated with having at least one living child. Higher modern contraceptives use was associated with older age, having at least one living child and high decision-making power, while lower modern contraceptives use was associated with higher education and undetermined fertility preference. Lower unmet need for modern contraceptives was associated with older age (PR 0.68, 95% CI: 0.48-0.97) and high decision-making power (PR 0.64, 95% CI: 0.50-0.81), while higher unmet need was found among those who having at least one living child (PR 1.40, 95% CI: 1.01-1.93) and undetermined fertility preference (PR 1.70, 95% CI: 1.24-2.34). Conclusions: Total demand and contraceptive use were found to be higher in the informal settlements of Kira municipality, however, the unmet need was much higher among this population as compared to the national urban estimates. This indicates a much higher demand for contraceptives and the need to consider the diverse socio-demographic characteristics of urban spaces. Development of Interventions need to critically consider the diverse urban space, associated explanatory variables and a collaborative systems lens to achieve sustained improvements.