Applying Association Rules to Infer the Relationships between Physical Parameters and Operational Indices of Irrigation Networks

Document Type : Original Article

Authors

1 M. Sc. Graduate, Hydraulic Structures, Tarbiat Modares University., Tehran., Iran

2 Associate Professor, Department of Water Structure Engineering, Tarbiat Modares University., Tehran., Iran

3 Assisstant Professer, Department of Irrigation and Drainage, Abureyhan campus, Tehran University., Tehran., Iran

Abstract

Irrigation networks operation is not only affected by water delivery and water distirbution, but also is a function of physical conditions of canals and structures. According to the network physical characteristics variety, identifying those that have more impact on the network performance and degree of their impacts, Provides basis for rehabilitation strategies for existing networks, and  appropriate performance-based design approach for similar networks. Applying intellectual data mining methods help the irrigation canal managers in finding out the hidden information. One of the most applied data mining methods is the association rules which have been used in this study to extract the performance patterns. Two groups of data have been used for this purpose, including the operational performance operational indices and the physical parameters of Qazvin irrigation network. In this way, the operational performance operational indices were considered as consequent and the physical parameters were presented as antecedents. Apriori algorithm was used to extract the rules. In single-agent relationship, results indicate that two physical parameters of:  distance of off-takes from  main canal and the type of off-takes; are the parameters affecting water delivery adequacy index with high confidence levels of 44% and 47%, respectively. In addition, water delivery stability index have been influenced by the distance of off-takes from regulating structures. Simultaneous study of several physical parameters on operational indices provides more insights in comparison with single-variable analyses. Therefore, in order to benefit the advantages of association rules method the main affecting factors must be considered together.

Keywords


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