This paper introduces an approach called Clustering and Co-evolution to Construct Neural Network Ensembles (CONE). This approach creates neural network ensembles in an innovative way, by explicitly partitioning the input space through a clustering method. The clustering method allows a reduction in the number of nodes of the neural networks that compose the ensemble, thus reducing the execution...

Document clustering is a fundamental operation used in unsupervised document organization, automatic topic extraction and information retrieval. But most clustering technologies are limited in their application on the static document collection. Intelligence analysts are currently overwhelmed with tremendous amount of text information streams generated everyday. There is a lack of comprehensive...

Parallel and distributed computing plays an important role by dividing a big process into many small processes running parallel with the help of number of processors. The communication in distributed and parallel processors takes place with the help of different API’s. In this paper the performance of two API’s i.e. PVM and LAM/MPI and three Clustering Tools OSCAR, Rocks and Knoppix is analyzed...

Distributed clustering techniques are considered effective and practical for power-saving in Wireless Sensor Networks (WSNs). In this paper, we propose a novel cluster formation scheme in WSNs, called StepWise AdapTive Clustering Hierarchy (SWATCH). SWATCH aims to solve the ClusterHead (CH) number uncertainty problem common to existing distributed clustering schemes, while keeping the desirable...

This paper presents a Distributed Efficient Clustering Approach (DECA) for mobility-resistant and energy-efficient clustering in multi-hop wireless networks. The clusterheads cover the whole network and each node in the network can exclusively determine the single cluster it belongs. DECA is fully distributed, each node transmits only one message during clustering operation, and the algorithm t...

In multiple channel environments, clustering provides a convenient framework for channel access and bandwidth allocation. Many clustering schemes, however, demand that terminals may communicate directly only if they share a common clusterhead. This requirement deactivates otherwise helpful links; those between nodes that belong to different clusters (intercluster links). Links between nodes tha...

The wireless sensor network (WSN) technology is a key component for ubiquitous computing. In order to achieve the long term operation of WSNs, communication protocols based on clustering have been extensively studied such as LEACH, ACE and HEED. In this paper, we propose two types of clustering methods for WSNs. The first type, which is based on centralized management, employs vector quantizati...

This paper presents a distributed grid based robust clustering protocol for mobile wireless sensor networks. An overwhelming majority of current research on sensor network routing protocols considers static networks only, while we consider mobile environment. grid based robust clustering is a distributed location based, energy aware clustering protocol designed for mobile sensor networks. grid ...

Advances in distributed networking have resulted in an explosion in size of modern datasets while storage and processing power continue to lag behind. This requires the need for algorithms that are efficient in terms of number of measurements and running time. To combat challenges associated with large datasets in distributed networks we propose hierarchical intuitionistic fuzzy possibilistic c...