Timely and accurate information on the global cropland extent is critical for applications in the fields of food security, agricultural monitoring, water management, land-use change modeling and Earth system modeling. On the one hand, it gives detailed location information on where to analyze satellite image time series to assess crop condition. On the other hand, it isolates the agriculture co...

We investigate the effects of a Financial Transaction Tax (FTT) in an order-driven artificial financial market. FTTs are meant to limit short-term speculative behavior by reducing the amount of excess liquidity in the system. To quantify these effects, adjustments in trading strategies and their effects on liquidity need to be taken into account. We model an agentbased continuous double-auction...

Research on inductive process modeling combines background knowledge with time-series data to construct explanatory models, but previous work has placed few constraints on search through the model space. We present an extended formalism that organizes process knowledge in a hierarchical manner, and we describe HIPM, a system that carries out constrained search for hierarchical process models. W...

This paper draws attention to the limitations of the standard unit root/cointegration approach to economic and financial modelling, and to some of the alternatives based on the idea of fractional integration, long memory models, and the random field regression approach to nonlinearity. Following brief explanations of fractional integration and random field regression, and the methods of applyin...

The FNSGP algorithm for Gaussian process model is proposed in this paper. It reduces the time cost to accelerate the task of non-stationary time series prediction without loss of accuracy. Some experiments are verified on the real world power load data.

Forecasting of temperature and precipitation can be efficiently used in decision making and optimal use of water resources. Studies in Iran have indicated a significant increase in annual temperature. This issue should be further researched in the Ahvaz region because it is the population hub in the southwest of Iran and the pole of irrigation networks and traditional agricultural land ...

This paper applies alternative time series techniques such as General to Specific (GETS) and Johansen Maximum Likelihood (JML) to estimate the long run income and price elasticities of demand for energy for Fiji. We also test for the causal relationship between energy consumption, GDP and energy prices using the Granger causality tests. Our results imply that there is a uni-directional causalit...

Dynamic analysis of programs is one of the most promising techniques to reverse-engineer legacy code for software understanding. However, the key problem is to cope with the volume of data to process, since a single execution trace could contain millions of calls. Although many trace analysis techniques have been proposed, most of them are not very scalable. To overcome this problem, we develop...

This paper provides a selected review of the recent developments and applications of mixtures of normal (MN) distribution models in empirical finance. One attractive property of the MN model is that it is flexible enough to accommodate various shapes of continuous distributions, and able to capture leptokurtic, skewed and multimodal characteristics of financial time series data. In addition, th...

A method of predictability analysis of future values of financial time series is described. The method is based on normalized mutual information functions. In the analysis, the use of these functions allowed to refuse any restrictions on the distributions of the parameters and on the correlations between parameters. A comparative analysis of the predictability of financial time series of Tel Av...