Forecasting Electricity Demand in Turkey Using Optimization and Machine Learning Algorithms

Medium Neural Networks (MNN), Whale Optimization Algorithm (WAO), and Support Vector Machine (SVM) methods are frequently used in the literature for estimating electricity demand. The objective of this study was to make an estimation of the electricity demand for Turkey’s mainland with the use of mixed methods of MNN, WAO, and SVM. Imports, exports, gross domestic product (GDP), and population data are used based on input data from 1980 to 2019 for mainland Turkey, and the electricity demands up to 2040 are forecasted as an output value. The performance of methods was analyzed using statistical error metrics Root Mean Square Error (RMSE), Mean Absolute Error (MAE), R-squared, and Mean Square Error (MSE). The correlation matrix was utilized to demonstrate the relationship between the actual data and calculated values and the relationship between dependent and independent variables. The p-value and confidence interval analysis of statistical methods was performed to determine which method was more effective. It was observed that the minimum RMSE, MSE, and MAE statistical errors are 5.325 × 10⁻¹⁴, 28.35 × 10⁻²⁸, and 2.5 × 10⁻¹⁴, respectively. The MNN methods showed the strongest correlation between electricity demand forecasting and real data among all the applications tested

Electricity Demand Forecasting with Use of Artificial Intelligence: The Case of Gokceada Island

This study reviews a selection of approaches that have used Artificial Neural Networks (ANN), Particle Swarm Optimization (PSO), and Multi Linear Regression (MLR) to forecast electricity demand for Gokceada Island. Artificial Neural Networks, Particle Swarm Optimization, and Linear Regression methods are frequently used in the literature. Imports, exports, car numbers, and tourist-passenger numbers are used as based on input values from 2014 to 2020 for Gokceada Island, and the electricity energy demands up to 2040 are estimated as an output value. The results obtained were analyzed using statistical error metrics such as R2, MSE, RMSE, and MAE. The confidence interval analysis of the methods was performed. The correlation matrix is used to show the relationship between the actual value and method outputs and the relationship between independent and dependent variables. It was observed that ANN yields the highest confidence interval of 95% among the method utilized, and the statistical error metrics have the highest correlation for ANN methods between electricity demand output and actual data

Efficacy of different therapeutic regimens on hepatic osteodystrophy in chronic viral liver disease

Background and aims Metabolic bone disease is common in patients with chronic liver disease. Comparative studies on the efficacies of antiosteoporotic agents in hepatic osteodystrophy have not been conducted yet. The aim of this study was to evaluate the safety and efficacy of different therapeutic regimens on hepatic osteodystrophy

The Role of Anti-Neutrophil Antibodies in the Etiologic Classification of Childhood Neutropenia: A Cross-Sectional Study in a Tertiary Center

Infections, drugs, malignancies, immunodeficiency, and autoimmunity may cause neutropenia. In primary autoimmune neutropenia, anti-neutrophil antibodies (ANeuA) bind to membrane antigens of neutrophils, which give rise to peripheral destruction of neutrophils. However, it is not always easy to detect these antibodies. This study aims to investigate the etiology of neutropenia, and at the same time to evaluate the immune mechanisms by ANeuA testing using granulocyte indirect immunofluorescence test. In our study, 310 neutropenic patients who were between 3 months and 18 years of age were evaluated. ANeuA screening tests were performed in 108 neutropenic patients (group 1), and these patients were divided into 2 subgroups as persistent neutropenia (group 1P, n=12) and recovered neutropenia (group 1R, n=96). Besides, a control group in the same age range was formed, consisting of 39 non-neutropenic children (group 2). ANeuA serum levels were also checked in these groups, and no statistically significant difference could be found between groups 1 and 2, or between groups 1P and 1R, regarding ANeuA levels. As a conclusion, our study was the first comprehensive research in Turkey investigating the large-scale etiology of neutropenia. Moreover, while ANeuA screening tests did not provide sufficient insight for immune neutropenia, we argue that it is not necessary for routine use and that further research in the etiology of neutropenia is required

Distribution of Orthopedic Surgery Interventions: Evaluation of 6236 Cases

Objective: Epidemiological studies can provide valuable guidance for the planning and improvement of healthcare services and medical education. In developing as well as developed countries, orthopedic interventions are considered basic healthcare and there is very high demand. The aim of this study was to determine the distribution of orthopedic and traumatological surgical interventions performed at state hospitals in a province of Turkey and to calculate the number of orthopedic beds required for that population

The prevalence of childhood psychopathology in Turkey: a cross-sectional multicenter nationwide study (EPICPAT-T).

Aim: The aim of this study was to determine the prevalence of childhood psychopathologies in Turkey

The prevalence of childhood psychopathology in Turkey: a cross-sectional multicenter nationwide study (EPICPAT-T)

Conclusion: This is the largest and most comprehensive epidemiological study to determine the prevalence of psychopathologies in children and adolescents in Turkey. Our results partly higher than, and partly comparable to previous national and international studies. It also contributes to the literature by determining the independent predictors of psychopathologies in this age group

Prevalence of Childhood Affective disorders in Turkey: An epidemiological study

Aim: To determine the prevalence of affective disorders in Turkey among a representative sample of Turkish population. Methods: This study was conducted as a part of the "The Epidemiology of Childhood Psychopathology in Turkey" (EPICPAT-T) Study, which was designed by the Turkish Association of Child and Adolescent Mental Health. The inclusion criterion was being a student between the second and fourth grades in the schools assigned as study centers. The assessment tools used were the K-SADS-PL, and a sociodemographic form that was designed by the authors. Impairment was assessed via a 3 point-Likert type scale independently rated by a parent and a teacher. Results: A total of 5842 participants were included in the analyses. The prevalence of affective disorders was 2.5 % without considering impairment and 1.6 % when impairment was taken into account. In our sample, the diagnosis of bipolar disorder was lacking, thus depressive disorders constituted all the cases. Among depressive disorders with impairment, major depressive disorder (MDD) (prevalence of 1.06%) was the most common, followed by dysthymia (prevalence of 0.2%), adjustment disorder with depressive features (prevalence of 0.17%), and depressive disorder-NOS (prevalence of 0.14%). There were no statistically significant gender differences for depression. Maternal psychopathology and paternal physical illness were predictors of affective disorders with pervasive impairment. Conclusion: MDD was the most common depressive disorder among Turkish children in this nationwide epidemiological study. This highlights the severe nature of depression and the importance of early interventions. Populations with maternal psychopathology and paternal physical illness may be the most appropriate targets for interventions to prevent and treat depression in children and adolescents