The simulations and potential forecasting of dust storms are of significant interest to public health and environment sciences. Dust storms have interannual variabilities and are typical disruptive events. The computing platform for a dust storm forecasting operational system should support a disruptive fashion by scaling up to enable high-resolution forecasting and massive public access when d...

The American Planning Association recently endorsed a new forecasting method called reference class forecasting, which is based on theories of planning and decision-making that won the 2002 Nobel prize in economics. This paper details the method and describes the first instance of reference class forecasting in planning practice. First, the paper documents that inaccurate projections of costs, ...

The scientific evaluation methodology for the forecast accuracy of wind power forecasting models is an important issue in the domain of wind power forecasting. However, traditional forecast evaluation criteria, such as Mean Squared Error (MSE) and Mean Absolute Error (MAE), have limitations in application to some degree. In this paper, a modern evaluation criterion, the Diebold-Mariano (DM) tes...

a r t i c l e i n f o Keywords: Cost-sensitive regression Model trees Evolutionary algorithms Asymmetric costs Loan charge-off forecasting Regression learning methods in real world applications often require cost minimization instead of the reduction of various metrics of prediction errors. Currently in the literature, there is a lack of white box solutions that can deal with forecasting proble...

We explored the average cost of 94,197 total knee and 78,541 total hip arthroplasties (TKA and THA) using the New York State Hospital Inpatient Cost Transparency database to evaluate the effect of beneficiary health status on hospital reported cost for the two operations. Using the 3M APR-DRG severity of illness index as a measure of patient's health status, we found a significant increase in c...

In a competitive market environment, supply chain management (SCM) has been critical for companies to survive. Demand planning plays an important role in SCM, for it provides accurate demand forecasts which may achieve customer satisfaction by offering benefits such as low inventory level, short lead time, efficient resource allocation, and quick response. To obtain more accurate forecasts, thi...

Fish forecasting technology has been applied successfully in many countries. However, most of the forecasting methods used in temperate water were unsuitable to be applied in this region. A fish forecasting model suitable to tropical environment has to be developed. This major project involving several objectives and phases to meet the goal of developing a satellite-based fishery forecasting sy...

Forecasting of electricity demand has become one of the most important areas of research in the electric power industry, as it is a critical component of cost-efficient power system management and planning. In this context, accurate and robust load forecasting is supposed to play a key role in reducing generation costs, and deals with the reliability of the power system. However, due to demand ...

Contingency is a ubiquitous component of project cost estimating. This paper provides a review of the literature pertaining to the estimating of project cost contingency. It describes the flaws of the tradition percentage method for estimating project cost contingency and sets out more robust estimation methods regression analysis, Monte Carlo simulation and artificial neutral networks. In part...

The problem of assessing the quality of an operational forecasting system that produces probabilistic forecasts is addressed using information theory. A measure of the quality of the forecasting scheme, based on the amount of a data compression it allows, is outlined. This measure, called ignorance, is a logarithmic scoring rule that is a modified version of relative entropy and can be calculat...