This paper presents a feasibility study of evolutionary scheduling for gas pipeline operations. The problem is complex because of several constraints that must be taken into consideration during the optimization process. The objective of gas pipeline operations is to transfer sufficient gas from gas stations to consumers so as to satisfy customer demand with minimum costs. The scheduling involv...

BACKGROUND Periods of anomalously warm ocean temperatures can lead to mass coral bleaching. Past studies have concluded that anthropogenic climate change may rapidly increase the frequency of these thermal stress events, leading to declines in coral cover, shifts in the composition of corals and other reef-dwelling organisms, and stress on the human populations who depend on coral reef ecosyste...

Elastic waves are generated when brittle materials are subjected to increasing strain. Their number and energy increase non-linearly, ending in a system-sized catastrophic failure event. Accelerating rates of geophysical signals (e.g., seismicity and deformation) preceding large-scale dynamic failure can serve as proxies for damage accumulation in the Failure Forecast Method (FFM). Here we test...

Gas concentration, which is a chaotic time series in essence, is a key factor of the coal mine safety. An accurate forecast of gas concentration is required to guarantee safety and has very highly social and economic benefits. Least squares support vector machine (LS-SVM) has been receiving increasing interest in areas ranging from its original application in pattern recognition to other applic...

We explain that revisions to successive density forecasts of the same outcome, as measured by the Kullback-Leibler Information Criterion, need not be unpredictable, unlike those to conditional mean forecasts, even when the forecaster uses information efficiently. However one can still test the efficiency of fixed-event conditional density forecasts, similarly to conditional mean forecasts, by t...

In the paper a model to predict the concentrations of particulate matter PM10, PM2.5, SO2, NO, CO and O3 for a chosen number of hours forward is proposed. The method requires historical data for a large number of points in time, particularly weather forecast data, actual weather data and pollution data. The idea is that by matching forecast data with similar forecast data in the historical data...

We present a model intended to predict mainly the residential and commercial natural gas consumption in urban areas, for the short and intermediate ranges of time. In the short range, the model has been successfully used to forecast the daily gas consumption of major cities of Argentina. It is able to predict the consumption 1 to 5 days in advance with 10% of uncertainty. In the intermediate ra...

energy price forecast is the key information for generating companies to prepare their bids in the electricity markets. however, this forecasting problem is complex due to nonlinear, non-stationary, and time variant behavior of electricity price time series. accordingly, in this paper a new strategy is proposed for electricity price forecast. the forecast strategy includes wavelet transform (wt...