International Journal of Advanced Networking and Applications

M. Suresh Babu ¹, N. Geethanjali ², B. Satyanarayana ³

Affiliations
1 Intel Institute of Science, Anantapur, Andhra Pradesh, IN
2 Department of Computer Science, S.K. University, Anantapur, IN
3 Board of Studies, Department of Computer Science, Sri Krishnadevaraya University, Anantapur, IN

Abstract

Clustering is an adaptive procedure in which objects are clustered or grouped together, based on the principle of maximizing the intra-class similarity and minimizing the inter-class similarity. Various clustering algorithms have been developed which results to a good performance on datasets for cluster formation. This paper analyze the major clustering algorithms: K-Means, Hierarchical clustering algorithm and reverse K means and compare the performance of these three major clustering algorithms on the aspect of correctly class wise cluster building ability of algorithm. An effective clustering method, HRK (Hierarchical agglomerative and Recursive K-means clustering) is proposed, to predict the short-term stock price movements after the release of financial reports. The proposed method consists of three phases. First, we convert each financial report into a feature vector and use the hierarchical agglomerative clustering method to divide the converted feature vectors into clusters. Second, for each cluster, we recursively apply the K-means clustering method to partition each cluster into sub-clusters so that most feature vectors in each subcluster belong to the same class. Then, for each sub cluster, we choose its centroid as the representative feature vector. Finally, we employ the representative feature vectors to predict the stock price movements. The experimental results show the proposed method outperforms SVM in terms of accuracy and average profits.

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M. Neelakantappa ¹, B. Satyanarayana ², A. Damodharam ³

Affiliations
1 BITS, Kurnool, AP, IN
2 SK University, Anantapur, AP, IN
3 JNT University, Hyderabad, IN

Abstract

Ad hoc networks are autonomous systems composed of mobile hosts that are free to move around arbitrarily. Rather than relying on a network infrastructure to perform routing in an Mobile Ad hoc NETwork (MANET) each mobile host serves as a router to forward packets originated from other nodes. Proactive protocols are table driven, find routes between all source-destination pairs regardless of the actual need for such routes. Reactive protocols, on the other hand, are based on the reduction of the routing load by initiating new routing activities only in the presence of data packets in need of a route. Dynamic Source Routing (DSR) is a reactive routing method for ad-hoc wireless networks that floods route requests when the route is needed. DSR is appealing for ad hoc networks as a reactive routing protocol because of the lower routing overhead. However its performance is not ideal for the high dynamic ad hoc networks. As an optimization for the current DSR, a new adaptive routes selection scheme based on the stability of nodes was proposed in this paper, considered joint hop count and node stability. As shown with the simulations results, the enhanced-DSR has higher throughput and less end-to-end packets delay.

Keywords

DSR, Stable Adaptive, Ad Hoc Network.

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