Weather Forecast and Entropy in Information Theory

Economic Value of Weather Forecast Information and Use of Forecast Information in Decision Making (Theme 3)

Weather Derivatives and Seasonal Forecast

The purpose of this paper is to incorporate the CPC (Climate Prediction Center) seasonal forecast in the temperature process so that conditional means and conditional variances of both the temperature and the CDD (Cooling Degree Day) may be redetermined in accordance with the seasonal forecasting probabilities. Under the Gaussian property of the underlying process, the prices of the CDD options...

Information Theory 4.1 Entropy and Mutual Information

Neural encoding and decoding focus on the question: " What does the response of a neuron tell us about a stimulus ". In this chapter we consider a related but different question: " How much does the neural response tell us about a stimulus ". The techniques of information theory allow us to answer this question in a quantitative manner. Furthermore, we can use them to ask what forms of neural r...

Entropy (information theory)

In information theory, systems are modeled by a transmitter, channel, and receiver. The transmitter produces messages that are sent through the channel. The channel modifies the message in some way. The receiver attempts to infer which message was sent. In this context, entropy (more specifically, Shannon entropy) is the expected value (average) of the information contained in each message. 'Me...

Multilingual Weather Forecast Generation System

The MLWFA (Multilingual Weather Forecasts Assistant) system will be demonstrated. It is developed to generate the multilingual text of the weather forecasts automatically. The raw data from the weather observation can be used to generate the weather element chart. According to the weather change trend, the forecasters can directly modify the value Of the element on the chart, such as the center...