Regression problems provide some of the most challenging research opportunities in the
area of machine learning, and more broadly intelligent systems, where the predictions of …

We consider the valuation of energy storage facilities within the framework of stochastic
control. Our two main examples are natural gas dome storage and hydroelectric pumped …

For large energy consumers transitioning to high shares of solar energy, irradiance
variability causes volatility in power generation and energy expenditures. Volatility in an end …

Variability in streamflows can lead to reduced generation from hydropower producers and
result in reductions in revenues that can be financially disruptive. This link between …

It is well known that the hedging effectiveness of weather derivatives is interfered by the
existence of geographical basis risk, ie, the deviation of weather conditions at different …

Many business people such as farmers and financial investors are affected by indirect
losses caused by scarce or abundant rainfall. Because of the high potential of insuring …

Rainfall modeling is significant for prediction and forecasting purposes in agriculture,
weather derivatives, hydrology, and risk and disaster preparedness. Normally two models …

The main objective of this paper is to present a technique for pricing weather derivatives with
payout depending on temperature. We start by using the Principle Component Analysis …

Eastern Germany is often hit by drought causing income risk for crop farmers. Index-based
risk management instruments could help crop farmers to reduce their farm income risk. Such …

Regression problems provide some of the most challenging research opportunities in the
area of machine learning, where the predictions of some target variables are critical to a …