Precipitation is one of the most relevant fields in atmospheric modeling because its environmental, social and economic implications. However, precipitation validation from weather model outputs presents substantial challenges, such as measurement uncertainties, use gridded datasets vs. direct observations, selection statistical goodness-of-fit measures. The main difficulty working with that it...

s (In the order of sessions) Stochastic Multi-time Scale Algorithm for Economic Dispatch Problems with Intermittent Energy Sources Harsha Gangammanavar Integrated Systems Engineering, The Ohio State University, Columbus, OH 43210, USA Suvrajeet Sen Department of Industrial and Systems Engineering University of Southern California, Los Angeles, CA 90089, USA Session 1 (10:00am-12:00pm, March 21,...

A major challenge confronting the scientific community is to understand both patterns of and controls over spatial and temporal variability of carbon exchange between boreal forest ecosystems and the atmosphere. An understanding of the sources of variability of carbon processes at fine scales and how these contribute to uncertainties in estimating carbon fluxes is relevant to representing these...

OBJECTIVES A rational payment system is being sought in Japanese health care-one that accurately reflects the required time and the level of technical difficulty when valuing physician activity. The objective of this study is to examine the current surgical payment system in Japan by clarifying the hourly values allocated to physician activity. METHODS This study focused on the 22 surgical pr...

rainfall spatial analysis methods are very helpful since there are not enough rainfall gauge stations and watersheds are scattered in large extent. there are many different methods for estimating average precipitation such as; arithmetic method and thiessen polygon. however, the arrangement and location of data and their correlations are not considered by classic methods. thus, geostatistical t...

Deregulated energy market participants mostly must use theHourly Price Forward Curves (HPFC) to evaluate their long term energy price contracts. We propose a new framework to estimate hourly, daily and yearly energy price profiles, based on the median estimation, instead of the widely used mean value. Hourly and daily data used for estimation are normalized in order to minimize the seasonality ...

This paper presents a comparative study of six soft computing models namely multilayer perceptron networks, Elman recurrent neural network, radial basis function network, Hopfield model, fuzzy inference system and hybrid fuzzy neural network for the hourly electricity demand forecast of Czech Republic. The soft computing models were trained and tested using the actual hourly load data obtained ...