Abstract Forecasting electrical energy demand and consumption is one of the important decision-making tools in distributing companies for making contracts scheduling and purchasing electrical energy. This paper studies load consumption modeling in Hamedan city province distribution network by applying ESN neural network. Weather forecasting data such as minimum day temperature, average day temp...

Improving time series forecastingaccuracy is an important yet often difficult task.Both theoretical and empirical findings haveindicated that integration of several models is an effectiveway to improve predictive performance, especiallywhen the models in combination are quite different. In this paper,a model of the hybrid artificial neural networks andfuzzy model is proposed for time series for...

The Richards model and its generalized version are deterministic models that often implemented to fit forecast the cumulative number of infective cases in an epidemic outbreak. In this paper we employ a predict COVID-19 Spain Italy, based on available epidemiological data. To quantify uncertainty parameter estimation, use parametric bootstrapping approach construct 95% confidence interval estim...

Grey theory is a kind of grey system founded by Professor Deng Jurong, Chinese scholar in the eighties century. It new method to study uncertainty problem with few data and poor information. In recent years, modeling forecasting has been widely used industry, agriculture, science technology, economic social development planning analysis, hydrology, geology, breeding natural disaster prediction ...

In early 2012, a widespread porcine epidemic diarrhea virus (PEDV) occurred in eastern China. A cell-adapted isolate, SD-M, was at the four-passage level of virulent field strain SD, which was isolated from a 2-day-old dead suckling piglet that had suffered from severe diarrhea in Shandong Province, China. We report here the complete genome sequence of SD-M. This sequence will promote a better ...

Abstract Epidemic forecasting provides an opportunity to predict geographic disease spread and counts when outbreak occurs plays a key role in preventing or controlling their adverse impact. However, conventional prediction models based on complex mathematical modelling rely the estimation of model parameters, which yields unreliable unsustainable results. Herein, we proposed simple for predict...

Epidemiology is a domain of knowledge interconnected with many other domains, thus making it a good candidate for reusing existing ontologies that, despite having been created for different purposes, characterize information frequently manipulated by epidemiologists and public health scientists. This paper presents an evaluation of existing ontologies for the semantic annotation of epidemiologi...

Understanding urban population migration patterns is very helpful for urban operation and management, including the traffic forecasting, epidemic prevention, commercial resource allocation, emergency response and future urban planning. The large taxi fleet equipped with GPS comprises ubiquitous mobile probes in urban areas, and their trajectories reveal interesting phenomena in the city. We inv...

During an outbreak of classical swine fever (hog cholera) or African swine fever, decisions in emergency headquarters have to be made under conditions of time pressure, limited resources and uncertainty. The computer program EpiMAN-SF is designed to support decision-making in this situation by providing up-to-date information and a structured approach to choosing from among competing tasks by c...