This paper uses minute-by-minute British electricity demand observations to evaluate methods for prediction from 10 to 30 minutes ahead. Such very short lead times are important for the real-time scheduling of electricity generation. We consider methods designed to capture both the intraday and the intraweek seasonal cycles in the data, including ARIMA modelling, an adaptation of Holt-Winters e...

Recent developments in the theory and application of the HardyLittlewood method are discussed, concentrating on aspects associated with diagonal diophantine problems. Recent efficient differencing methods for estimating mean values of exponential sums are described first, concentrating on developments involving smooth Weyl sums. Next, arithmetic variants of classical inequalities of Bessel and ...

Numerous research have been done to predict cryptocurrency prices since affect global economic and monetary systems. However, investigations using linear connection approaches technical analysis indicators frequently fall short of providing an explanation for changes in the pattern BitCoin pricing. This paper is proposed study time-varying parameters with long short-term memory (LSTM). The inve...

Journal of Energy in Southern Africa • Vol 23 No 3 • August 2012 23 Abstract In this paper, seasonal autoregressive integrated moving average (SARIMA) and regression with SARIMA errors (regression-SARIMA) models are developed to predict daily peak electricity demand in South Africa using data for the period 1996 to 2009. The performance of the developed models is evaluated by comparing them wit...

Due to the liberalization of countless electricity markets, load forecasting has become crucial to all public utilities for which electricity is a strategic variable. With the goal of contributing to the forecasting process inside public utilities, this paper addresses the issue of applying the Holt-Winters exponential smoothing technique and the time series analysis for forecasting the hourly ...

We address the problem of forecasting spatial activities on a daily basis that are subject to the types of multiple, complex calendar e€ects that arise in many applications. Our problem is motivated by applications where we generally need to produce thousands, and frequently tens of thousands, of models, as arises in the prediction of daily origin±destination freight ̄ows. Exponential smoothing...

ETFs are baskets of securities designed to track the performance of an index. They are designed to provide exposure to broad-based indexes at a lower cost. We first analyzed why ETF should be the choice for an investment. We provide a brief history of this segment, key attributes of ETFs, and investments strategies and implementations with ETFs. The article then presents data analysis and a ser...

A mobile ad hoc network (MANET) is a set of and self-organizing nodes that cooperate to create dynamic architecture establish communications. Its characteristics present critical challenges: limited residual energy transmission range, wireless links sensitivity environmental effects, the mobility aspect, which leads frequent link failure rapid changes in topology. In this paper, we propose new ...

We address the problem of forecasting spatial activities on a daily basis that are subject to the types of multiple, complex calendar e ects that arise in many applications. Our problem is motivated by applications where we generally need to produce thousands, and frequently tens of thousands, of models, as arises in the prediction of daily origin-destination freight ows. Exponential smoothingb...

We present an algorithm for computing exact expressions for the distribution of the maximum or minimum of an arbitrary nite collection of linear combinations of spacings or exponential random variables with rational coeecients. These expressions can then be manipulated or evaluated using symbolic math packages such as MAPLE. As examples, we apply this algorithm to obtain the distributions of th...