A novel approach for instance selection in classification problems is presented. This adaptive instance selection is designed to simultaneously decrease the amount of computation resources required and increase the classification quality achieved. The approach generates new training samples during the evolutionary process and changes the training set for the algorithm. The instance selection is guided by means of changing probabilities, so that the algorithm concentrates on problematic examples which are difficult to classify. The hybrid fuzzy classification algorithm with a self-configuration procedure is used as a problem solver. The classification quality is tested upon 9 problem data sets from the KEEL repository. A special balancing strategy is used in the instance selection approach to improve the classification quality on imbalanced datasets. The results prove the usefulness of the proposed approach as compared with other classification methods.
W pracy omówiono trzyetapową procedurę modelowania dyskretnych systemów produkcyjnych. Na jej podstawie zaproponowano koncepcję samokonfiguracji systemów sterowania wytwarzaniem. Koncepcja ta umożliwi budowanie rozproszonych systemów sterowania wytwarzaniem działających zgodnie z zasadą włącz i produkuj. Wymaga to zastosowania jednolitych, konfigurowalnych, inteligentnych agentów. Do badania procesu samokonfiguracji użyto oprogramowania symulacyjnego Arena firmy Rockwell Automation.
EN
The paper describes the modelling process of a discrete manufacturing system as a three-stage procedure. It also presents the self-configuration procedure for distributed manufacturing control system. It will allow for the construction of the plug and produce distributed manufacturing control system, which require the integration of unified, easy to reconfigure, intelligent and cooperative agents. Arena Simulation Environment (Rockwell Automation) is used for examining the procedure.
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We propose a collaborative filtering (CF) method that uses behavioral data provided as propositions having the RDF-compliant form of (user X, likes, item Y ) triples. The method involves the application of a novel self-configuration technique for the generation of vector-space representations optimized from the information-theoretic perspective. The method, referred to as Holistic Probabilistic Modus Ponendo Ponens (HPMPP), enables reasoning about the likelihood of unknown facts. The proposed vector-space graph representation model is based on the probabilistic apparatus of quantum Information Retrieval and on the compatibility of all operators representing subjects, predicates, objects and facts. The dual graph-vector representation of the available propositional data enables the entropy-reducing transformation and supports the compositionality of mutually compatible representations. As shown in the experiments presented in the paper, the compositionality of the vector-space representations allows an HPMPP-based recommendation system to identify which of the unknown facts having the triple form (user X, likes, item Y ) are the most likely to be true in a way that is both effective and, in contrast to methods proposed so far, fully automatic.
W pracy przedstawiono procedurę samokonfiguracji wieloagentowego systemu sterowania umożliwiającą integrację podsystemu wytwarzania z podsystemem transportu międzyoperacyjnego złożonym z automatycznie sterowanych pojazdów. Wykorzystując oprogramowanie Arena do symulacji procesów dyskretnych, omówiono na prostym przykładzie, sposób budowy modelu symulacyjnego pozwalającego na badanie procesu samokonfiguracji oraz docelowo sterowanie systemem produkcyjnym.
EN
The paper presents an idea of self-configuration of a multi–agent control system integrating manufacturing subsystem with automated guided vehicles transportation subsystem used for work-in-process movement in a production system. Using Arena a discrete event simulation software, on a simple example, the concept of self–configuration of a distributed production control system is presented. Such a simulation model may be applied for examining self–configuration process and ultimately control of production system.
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