Titlebook: Agents and Data Mining Interaction; 4th International Wo Longbing Cao,Vladimir Gorodetsky,Philip S. Yu Conference proceedings 2009 Springer

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Agents Based Data Mining and Decision Support Systemroduct at the right moment in the product life cycle (PLC), lessens production, storing and other related costs. This arises such problems to be solved as defining the present a PLC phase of a product as also determining a transition point - a moment of time (period), when the PLC phase is changed..

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Agent-Enriched Data Mining Using an Extendable Frameworkand presents a rational for Agent-Enriched Data Mining (AEDM). A particular challenge of any generic, general purpose, AEDM system is the extensive scope of KDD. To address this challenge the authors suggest that any truly generic AEDM must be readily extendable and propose EMADS, The Extendable Mul

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Auto-Clustering Using Particle Swarm Optimization and Bacterial Foraging . (Auto-Clustering based on particle bacterial foraging) makes use of autonomous agents whose primary objective is to cluster chunks of data by using simplistic collaboration. Inspired by the advances in clustering using particle swarm optimization, we suggest further improvements. Moreover, we gat

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Enhancing Agent Intelligence through Data Mining: A Power Plant Case Studye combined to enhance the intelligence of the proposed application, mainly in two aspects: increase the reliability of input data (sensor validation and false measurement replacement) and generate new control monitoring rules. Various classification algorithms are compared. The performance of the ap

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