Numerical weather prediction (NWP) models have been widely used for wind resource assessment. Model runs with higher spatial resolution are generally more accurate, yet extremely computational expensive. An alternative approach is to use data generated by a low resolution NWP model, in conjunction with statistical methods. In order to analyze the accuracy and computational efficiency of differe...

Internet worms remain one of the major threats to the Internet infrastructure. Modeling allows forecasting the malware propagation consequences and evolution trends, planning countermeasures and many other tasks that cannot be investigated without harm to production systems in the wild. Existing malware propagation models mainly concentrate on malware epidemic consequences modeling, i.e. foreca...

Computational Intelligence techniques have been proposed as an efficient tool for modeling and forecasting in recent years and in various applications. Water is a basic need and as a result, water supply entities have the responsibility to supply clean and safe water at the rate required by the consumer. It is therefore necessary to implement mechanisms and systems that can be employed to predi...

In this work, the hourly solar radiation data collected during the period August 1, 2005–July 30, 2006 from the solar observation station in Iki Eylul campus area of Eskisehir region are studied. A two-dimensional (2-D) representation model of the hourly solar radiation data is proposed. The model provides a unique and compact visualization of the data for inspection, and enables accurate forec...

In this paper, a hybrid system is developed by evolving Case-Based Reasoning (CBR) with Genetic Algorithm (GA) for reverse sales forecasting of returning books. CBR systems have been successfully applied in several domains of artificial intelligence. However, in conventional CBR method each factor has the same weight which means each one has the same influence on the output data that does not r...

For time-series forecasting problems, there have been several prediction models to data, but the development of a more accurate model is very difficult because of high non-linear and non-stable relations between input and output data. Almost all the models at hand are not applicable online, although online prediction, especially for air quality parameters forecasting, has very important signifi...

Rational small business management necessitates the development of a system for recording important internal information. Companies are obliged to collect statistical data that mainly serves fiscal needs. Exemplary use such significant entails financial liquidity (LIQt) and debt recovery efficiency (EVINDt) measures. This work presents constructions measures manner their application when they a...

The problem of obtaining an accurate forecast is becoming more and more significant as the production possibilities and technologies evolve. The accuracy of a forecast mainly depends on the dataset used for forecasting as well as on the methods employed. This study is devoted to the time series analysis. A set of known methods and techniques are used for analysing the time series; one of them i...

Nonlinear model structure selection (MSS) is an important step in the modeling theory of the nonlinear system. The proper model structure and model parameters estimation can be used to reduce unnecessary computations and improve the model forecast accuracy. This paper mainly investigates the short-term wind speed forecasting (STWSF) by utilizing the comprehensive MSS technique based on real dat...