D.3. Data Storage Representations
E. Fadaei-Kermani; G. A Barani; M. Ghaeini-Hessaroeyeh
Abstract
Drought is a climate phenomenon which might occur in any climate condition and all regions on the earth. Effective drought management depends on the application of appropriate drought indices. Drought indices are variables which are used to detect and characterize drought conditions. In this study, it ...
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Drought is a climate phenomenon which might occur in any climate condition and all regions on the earth. Effective drought management depends on the application of appropriate drought indices. Drought indices are variables which are used to detect and characterize drought conditions. In this study, it was tried to predict drought occurrence, based on the standard precipitation index (SPI), using k-nearest neighbor modeling. The model was tested by using precipitation data of Kerman, Iran. Results showed that the model gives reasonable predictions of drought situation in the region. Finally, the efficiency and precision of the model was quantified by some statistical coefficients. Appropriate values of the correlation coefficient (r=0.874), mean absolute error (MAE=0.106), root mean square error (RMSE=0.119) and coefficient of residual mass (CRM=0.0011) indicated that the present model is suitable and efficient
D.3. Data Storage Representations
E. Azhir; N. Daneshpour; Sh. Ghanbari
Abstract
Technology assessment and selection has a substantial impact on organizations procedures in regards to technology transfer. Technological decisions are usually made by a group of experts, and whereby integrity of these viewpoints to a single decision can be quite complex. Today, operational databases ...
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Technology assessment and selection has a substantial impact on organizations procedures in regards to technology transfer. Technological decisions are usually made by a group of experts, and whereby integrity of these viewpoints to a single decision can be quite complex. Today, operational databases and data warehouses exist to manage and organize data with specific features and henceforth, the need for a decision-aid approach is essential. The process of developing data warehouses involves time consuming steps, complex queries, slow query response rates and limited functions, which is also true for operational databases. In this regards, Fuzzy multi-criteria procedures in choosing efficient data sources (data warehouse and traditional relational databases) based on organization requirements is addressed in this paper. In proposing an appropriate selection framework the paper compares a Triangular Fuzzy Numbers (TFN) based framework and Fuzzy Analytical Hierarchy Process (AHP), based on data sources models, business logic, data access, storage and security. Results show that two procedures rank data sources in a similar manner and due to the accurate decision-making.