a r t i c l e i n f o Keywords: Multi-scale digital terrain analysis Feature selection Spatial data mining Digital soil mapping ANOVA Principal components analysis Random subsets Decision trees Terrain attributes are the most widely used predictors in digital soil mapping. Nevertheless, discussion of techniques for addressing scale issues and feature selection has been limited. Therefore, we pr...

Porosity is one of the key parameters associated with oil reservoirs. Determination of this petrophysical parameter is an essential step in reservoir characterization. Among different linear and nonlinear prediction tools such as multi-regression and polynomial curve fitting, artificial neural network has gained the attention of researchers over the past years. In the present study, two-dimensi...

The decision to recruit manpower in an organization requires clear identification of the criteria (attributes) that distinguish successful from unsuccessful performance. The choice of appropriate attributes or criteria in different levels of hierarchy in an organization is a multi-criteria decision problem and therefore multi-criteria decision making (MCDM) techniques can be used for prioritiza...

This work firstly presents an approach based on the organizational concept of business processes to identify roles and protocols as part of the analysis stage of a methodology for agent-oriented analysis and design. Secondly, the work presents an approach to help to decide when using a mobile agent in a multi-agent architecture is better than using a static one. This approach is based on both t...

127 Abstract Data in a data warehouse is organized in a multidimensional model. This multidimensional model helps in faster query processing and efficient OLAP operations for data analysis and decision making. In this paper, we introduce a framework which proposes design methodologies to map the relational database into a multidimensional model. The process starts with first cleaning the relati...

Data in a data warehouse is organized in a multidimensional model. This multidimensional model helps in faster query processing and efficient OLAP operations for data analysis and decision making. In this paper, we introduce a framework which proposes design methodologies to map the relational database into a multidimensional model. The process starts with first cleaning the relational database...

the sensitivity analysis for multi-attribute decision making (madm) problems is important for two reasons: first, the decision matrix as the source of the results of a decision problem is inaccurate because it sorts the alternatives in each criterion inaccurately. second, the decision maker may change his opinions in a time period because of changes in the importance of the criteria and in the ...