On the Application of Data Mining to Official Data

Retrieving valuable knowledge and statistical patterns from official data has a great potential in supporting strategic policy making. Data Mining (DM) techniques are well-known for providing flexible and efficient analytical tools for data processing. In this paper, we provide an introduction to applications of DM to official statistics and flag the important issues and challenges. Considering recent advancements in software projects for DM, we propose intelligent data control system design and specifications as an example of DM application in official data processing.Data mining, Official data, Intelligent data control system

On the Application of Data Mining to Official Data

Retrieving valuable knowledge and statistical patterns from official data has a great potential in supporting strategic policy making. Data Mining (DM) techniques are well-known for providing flexible and efficient analytical tools for data processing. In this paper, we provide an introduction to applications of DM to official statistics and flag the important issues and challenges. Considering recent advancements in software projects for DM, we propose intelligent data control system design and specifications as an example of DM application in official data processing

On the Application of Data Mining to Official Data

Retrieving valuable knowledge and statistical patterns from official data has a great potential in supporting strategic policy making. Data Mining (DM) techniques are well-known for providing flexible and efficient analytical tools for data processing. In this paper, we provide an introduction to applications of DM to official statistics and flag the important issues and challenges. Considering recent advancements in software projects for DM, we propose intelligent data control system design and specifications as an example of DM application in official data processing

Collaborative multi-Carrier communication techniques for multi-user systems

Developing robust techniques for fast growing multi-user networks in pervasive environments is an important challenge. Multi-carrier communication is an established technique for achieving superior performance in multi-path frequency selective fading channels. In this thesis, new multi-carrier multiple access techniques using collaborative and cooperative approaches are proposed for multi-user systems in fading environments.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

Collaborative multi-Carrier communication techniques for multi-user systems

Developing robust techniques for fast growing multi-user networks in pervasive environments is an important challenge. Multi-carrier communication is an established technique for achieving superior performance in multi-path frequency selective fading channels. In this thesis, new multi-carrier multiple access techniques using collaborative and cooperative approaches are proposed for multi-user systems in fading environments.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

Trained Particle Swarm Optimization for Ad-Hoc Collaborative Computing Networks

Distributed processing is an essential part of collaborative computing techniques over ad-hoc networks. In this paper, a generalized particle swarm optimization (PSO) model for communication networks is introduced. A modified version of PSO, called trained PSO (TPSO), consisting of distributed particles that are adapted to reduce traffic and computational overhead of the optimization process is proposed. The TPSO technique is used to find the node with the highest processing load in an ad-hoc collaborative computing system. The simulation results show that the TPSO algorithm significantly reduces the traffic overhead, computation complexity and convergence time of particles, in comparison to the PSO. 1 INTRODUCTIO

Particle Swarm Optimization for Adaptive Resource Allocation in Communication Networks

A generalized model of particle swarm optimization (PSO) technique is proposed as a low complexity method for adaptive centralized and distributed resource allocation in communication networks. The proposed model is applied to adaptive multicarrier cooperative communications (MCCC) technique which utilizes the subcarriers in deep fade using a relay node in order to improve the bandwidth efficiency. Centralized PSO, based on virtual particles (VPs), is introduced for single layer and cross-layer subcarrier allocation to improve the bit error rate performance in multipath frequency selective fading channels. In the single layer strategy, the subcarriers are allocated based on the channel gains. In the cross-layer strategy, the subcarriers are allocated based on a joint measure of channel gains and distance provided by the physical layer and network layer to mitigate the effect of path loss. The concept of training particles in distributed PSO is proposed and then is applied for relay node selection. The computational complexity and traffic of the proposed techniques are investigated, and it is shown that using PSO for subcarrier allocation has a lower complexity than the techniques in the literature. Significant reduction in the traffic overhead of PSO is demonstrated when using trained particles in distributed optimizations