Increased focus on sustainability and energy decentralization has positively impacted the adoption of nanogrids. With tremendous growth, load forecasting become crucial for their daily operation. Since loads nanogrids have large variations with sudden usage household electrical appliances, existing models, majorly focused lower volatile loads, may not work well. Moreover, abrupt operation appli...

An econometric model for the U. S. lodging market was developed from time series data. Estimates from this model were then combined with preliminary sales estimates. The resulting combination greatly improved the estimates of the "final sales" figures and also reduced the error in two forecasting tests. These improvements were achieved at a low cost.

Tactical forecasting in supply chain management supports planning for inventory, scheduling production, and raw material purchase, amongst other functions. It typically refers to forecasts up to 12 months ahead. Traditional forecasting models take into account univariate information extrapolating from the past, but cannot anticipate macroeconomic events, such as steep increases or declines in n...

This paper presents a new application of a particular machine learning technique for improving wind forecasting. The technique, known as kernel regression, is somewhat similar to fuzzy logic in that both make predictions based on the similarity of the current state to historical training states. Unlike fuzzy logic systems, kernel regression relaxes the requirement for explicit event classificat...

Highly accurate interval forecasting of a stock price index is fundamental to successfully making a profit when making investment decisions, by providing a range of values rather than a point estimate. In this study, we investigate the possibility of forecasting an interval-valued stock price index series over short and long horizons using multi-output support vector regression (MSVR). Furtherm...

Potential financial planning tools may include technical models for forecasting expenses, revenues, and risk. The Volpe Center conducted a literature review to assess the state of the financial forecasting practice and potentially to expand the body of knowledge concerning the development and use of these tools. The results of the literature scan, presented in the table below, were narrowed fro...

Careful planning of the electrical power sector is of great importance since the decisions to be taken involves the commitment of large resources, with potentially serious economic risks for the electrical utility and the economy as a whole. There are different types of techniques available for analysis and prediction of randomly varying parameters. They are classified as statistical, intellige...

Introduction Reliable and timely forecasts provide important and useful input for proper, foresighted and informed planning, more so, in agriculture which is full of uncertainties. Agriculture now-adays has become highly input and cost intensive. Under the changed scenario today, forecasting of various aspects relating to agriculture are becoming essential. But in-spite of strong need for relia...

The apparel industry is a fashion industry with short product life and more demand uncertainty. Participants in apparel supply chain bear more risk. To lower the cost and risk for participants in apparel supply chain, a framework for apparel quick response system based on collaborative forecasting was proposed. The prototype of the apparel quick response system was provided, which included thre...