Optimized Adaptive Fuzzy Forecasting System with Application

In this paper, a fuzzy forecasting system is designed and implemented by which an original forecasting model can be obtained by data learning. The model parameters can then be adaptively optimized through gradient information of real-time data. Thus, the system is of extinguished adaptive feature and self-learning capability. Afterwards, experimental research efforts are put forward to carry out electric power load forecasting. Experimental results demonstrate the satisfactory performances of the intelligent forecasting system.

Economic forecasting with big data:A literature review

Big data technology has revolutionized the research paradigm of economic forecasting regardless of the data source,forecasting method,or forecasting result.This study evaluates the current literature on economic forecasting using big data and employs bibliometric approaches to offer a comprehensive analysis.Additionally,utilizing the advanced structural variation analysis technique,we can identify papers with transformative potential in this domain.This study provides valuable suggestions for enhancing scholars'understanding of significant research,novel breakthroughs,and emerging trends in the role of big data in economic forecasting.

An Analysis of the COVID-19 Consequences on the Uncertainty Socio-economic Indicators of Sub-Saharan Africa

This study aims to investigate the main sectors of economic development before and the current situation of COVID-19 for Sub-Saharan African countries by demonstrating country experiences,the role of vaccines,and the SSA economy forecast.The study has four main sections,including an introduction,an overview of socioeconomic indicators before the pandemic,methods,results findings,and discussion.The study used mixed methods,including an approach based on secondary data.The quantitative results were analysed using both empirical methods and the researcher’s prior expertise.The analysis of the effects of the COVID-19 pandemic on SSA countries was based on long-term data collected by several international financial institutions.The research findings demonstrated conclusively that COVID-19 is causing the collapse of the SSA economy,the first economic recession in 25 years,$37-79 billion in lost GDP by 2020,and an export decrease of 10.6%.In education,for example,64%of primary and 50%of secondary students lack ICT training,89%(216 million)do not have access to a home computer,and 82%(199 million)do not have an Internet connection missed classes during the COVID-19 period.The agricultural sector in SSA is also impacted by over 239 million hungry people.COVID-19 mass vaccinations and public debt amount to over$154 billion in obligations to get the SSA economy back on its feet with zero tolerance for embezzlement of public funds.These results can be used to make the economies of SSA countries resilient to the current crises and to address some thematic issues,such as the implementation of the African Continental Free Trade Area(AfCFTA)in all SSA countries,which will save time and money by getting rid of border taxes.Therefore,policymakers can use the findings to begin formulating plans to address issues like economic development,education,and food insecurity.

China Economic Forecast 2012

THE likelihood of double-digit growth has dissolved in China, and the risk of a sub-7 percent growth rate in one of the quarters next year has increased meaningfully.

CHINA'S 2008 ECONOMIC FORECAST

In 2008,the Chinese economy will re- main stable and retain high growth.It is expected that the growth of the gross domestic product will drop slightly,the increase of the consumer price index (CPI)will slow,fixed assets investment will cool down and the growth of the trade sur- plus will fall,according to a report issued by the State Information Center.

Energy Management System Design and Testing for Smart Buildings Under Uncertain Generation (Wind/Photovoltaic) and Demand

This study provides details of the energy management architecture used in the Goldwind microgrid test bed. A complete mathematical model, including all constraints and objectives, for microgrid operational management is first described using a modified prediction interval scheme. Forecasting results are then achieved every 10 min using the modified fuzzy prediction interval model, which is trained by particle swarm optimization.A scenario set is also generated using an unserved power profile and coverage grades of forecasting to compare the feasibility of the proposed method with that of the deterministic approach. The worst case operating points are achieved by the scenario with the maximum transaction cost. In summary, selection of the maximum transaction operating point from all the scenarios provides a cushion against uncertainties in renewable generation and load demand.

Measuring Nonlinear Dependence Between Time Series Based on Correlation Dimension

In this paper, it is proved that the correlation dimension estimate of a nonlinear dynamical system with its multivariate observation series is the same as that with its univariate observation series. Based on this result, an inference method is presented, and the Nonlinear Dependence Coefficient is defined. This method is designed for testing nonlinear dependence between time series, and can be used in economic analysis and forecasting. Numerical results show the method is effective.