... to explore the influential factors on COSC. All the data are extracted from Web sources. In addition to COVID-19, four other diseases are considered to optimize the accuracy of predictive results. A principal component analysis is deployed to reduce the number of variables. A forecasting model is developed...

... for energy load forecasting in the region southeastern Brazil. Design/methodology/approach The proposed approach defines a contribution rate of each variable as a weighted sum of the inner product between the variable and each principal component. So, the contribution rate is used for selecting the most...

...Lucas Rodrigues; Luciano Rodrigues; Mirian Rumenos Piedade Bacchi Purpose Fuel demand forecast is a fundamental tool to guide private planning actions and public policies aim to guarantee energy supply. This paper aims to evaluate different forecasting methods to project the consumption of light...

... Forecasting Renewable energies Wind Cost comparison Project economics Energy conversion Weibull distribution function Wind speed Wind power density Energy density Economic analysis List of Abbreviations and Symbols AGL = Above the Ground Level; NREL = National Renewable Energy...

... at: fpascalin20022003@yahoo.fr 15 04 2020 07 07 2020 15 12 2020 © Emerald Publishing Limited 2020 Emerald Publishing Limited Licensed re-use rights only Artificial intelligence Neural networks Forecasting Wind Wind speed forecasting Artificial neural network Multi-layer...

...-in from renewable energy sources. Hence, the purpose of this paper is to provide accurate forecasts.. Design/methodology/approach This paper aims at comparing different predictors stemming from supply-side (solar and wind power generation), demand-side, fuel-related and economic influences...

...Paria Soleimani; Bahareh Emami; Meysam Rafei; Hooman Shahrasbi Purpose Today, because of the increasing need for the energy resources and the reduction of fossil fuels, renewable energy, especially wind energy, has attracted special attention. The precise forecasting of such energy...

...Emmanuel Bannor B.; Alex O. Acheampong Purpose This paper aims to use artificial neural networks to develop models for forecasting energy demand for Australia, China, France, India and the USA. Design/methodology/approach The study used quarterly data that span over the period of 1980Q1-2015Q4...

... autoregressive distributed lag model. Lastly, we use the Campbell and Thompson (2008) forecast evaluation test to comparatively assess the predictive ability of the symmetric (restricted) and asymmetric (unrestricted) models. Findings Our results show that asymmetries matter in the oil price–inflation nexus...

...Samrad Jafarian-Namin; Alireza Goli; Mojtaba Qolipour; Ali Mostafaeipour; Amir-Mohammad Golmohammadi Purpose The purpose of this paper is to forecast wind power generation in an area through different methods, and then, recommend the most suitable one using some performance criteria. Design...

...Esam A. Hashim Alkaldy; Maythem A. Albaqir; Maryam Sadat Akhavan Hejazi Purpose Load forecasting is important to any electrical grid, but for the developing and third-world countries with power shortages, load forecasting is essential. When planed load shedding programs are implemented to face...

...Mustafa Jahangoshai Rezaee; Mojtaba Dadkhah; Masoud Falahinia Purpose This study aims to short-therm forecasting of power generation output for this purpose, an adaptive neuro-fuzzy inference system (ANFIS) is designed to forecast the output power of power plant based on climate factors...

... and then predicted for the next 20 years (2015 to 2004). Furthermore, to determine the appropriate method for forecasting, two approaches titled “trend analysis” and “double exponential smoothing” will be applied on data, collected from 1967 to 2014, and their capabilities in anticipating will be compared to each...

... Correlation analysis Forecasting Neural networks Electricity There has been an increase in the usage of electronics appliances in home. Studies show that increase in the “home appliances” is accepted to grow by 15.3 per cent of annual growth rate, resulting in a market volume of US$2,227m in 2022...

...Marc Gürtler; Thomas Paulsen Purpose Study conditions of empirical publications on time series modeling and forecasting of electricity prices vary widely, making it difficult to generalize results. The key purpose of the present study is to offer a comparison of different model types and modeling...

... the state of network in terms of LMP, generation, active power loss and voltage at each bus; control private DG owners; and maintain fair competition among DG owners. The remaining part of the paper is organized as follows: Section II presents load forecasting using ANN, computation of loss...

...Marc Gürtler; Thomas Paulsen Purpose Empirical publications on the time series modeling and forecasting of electricity prices vary widely regarding the conditions, and the findings make it difficult to generalize results. Against this background, it is surprising that there is a lack of statistics...

.... Research limitations/implications “Personalization” of the model is crucial aspect in the whole methodology. All available knowledge should be used on the forecasted phenomenon and incorporate it into the model. In case of the memory-based modeling, it is a specific design of the history searching routine...

...Hesam Nazari; Aliyeh Kazemi Purpose This paper aims to select the best scenario for energy demand forecast of residential and commercial sectors in Iran by using particle swarm optimization algorithm. Design/methodology/approach In this study, using variables affecting energy demand...

... at issue, calculated based on Black and Scholes’ (1973) option pricing methodology (Dutordoir and Van de Gucht, 2009 ; Lewis, et al. 1999). Results were, again, mixed[ 3 ]. © Emerald Group Publishing Limited 2015 Decision making Forecasting Cash flow Industry Renewable...