Conference Papers

Permanent URI for this collectionhttps://idr.nitk.ac.in/handle/123456789/28506

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Subject: search.filters.subject.Gene expression programming

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    Crop classification using gene expression programming technique
    (Springer Verlag service@springer.de, 2013) Narasipura, O.S.; John, R.L.; Choudhry, N.; Kubusada, Y.; Bhageshpur, G.
    Precise classification of agricultural crops provides vital information on the type and extent of crops cultivated in a particular area. This information plays an important role in planning further cultivation activities. Image classification forms the core of the solution to the crop coverage identification problem. In this paper we present the experimental results obtained by using Gene Expression Programming (GEP) to classify the crop data obtained from satellite images. We have adopted supervised one-against-all learning technique to perform the classification of data. Gene Expression Programming provides an efficient method for obtaining classification rules in the form of a mathematical expression for a given data set containing input and output variables. We have also compared the classification efficiencies obtained with those of other classifiers namely Support vector machines and Artificial neural networks. Sensitivity Analysis has also been carried out to determine the significance of each input variable. © 2013 Springer-Verlag.
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    A gene expression based quality of service aware routing protocol for mobile ad hoc networks
    (2013) Kubusada, Y.; Mohan, G.; Manjappa, M.; Guddeti, G.
    Mobile Ad Hoc Network (MANET) is a collection of infrastructure less multi-hop wireless mobile nodes which communicate together to achieve the global task. Despite lack of centralized control these mobile nodes still coordinate together to deliver the message to the destination node. MANET is gaining its popularity due to its easy deployment and self-organizing ability. In spite of its unique characteristics, mobility of mobile nodes causes frequent link breakups in MANET and thus makes route setup and maintenance a critical and challenging task. As real time and multimedia applications are increasing, there is a need of an efficient Quality of Service (QoS) aware routing protocol for MANET to support such applications. In the present work, the authors proposed an efficient QoS aware routing protocol for MANET based on upcoming Gene Expression Programming. In the proposed work, the information regarding the availability of resources is managed by a resource management module, which assists in selecting the resource rich path. Further, a theoretical proof is given for the proposed model for its correctness. The results are compared with the state of art artificial neural network and support vector regression methods from the performance evaluation point of view and the results are encouraging. © 2013 Springer Science+Business Media.