131 research outputs found
Application of Relevance Feedback in Content Based Image Retrieval Using Gaussian Mixture Models
Feature extraction and identification techniques for the alignment of perturbation simulations with power plant measurements
In this work, a methodology is proposed for the comparison of the measured and simulated neutron noise signals in nuclear power plants, with the simulation sets having been generated by the CORE SIM+ diffusion-based reactor noise simulator. More specifically, the method relies on the computation of the Cross-Power Spectral Density of the detector signals and the subsequent comparison with their simulated counterparts, which involves specific frequency values corresponding to the signals’ high energy content. The different simulated perturbations considered are (i) axially traveling perturbations, (ii) fuel assembly vibrations, (iii) core barrel vibrations, and finally (iv) generic “absorber of variable strength” types. The reactor core used for the current study is a German 4-loop pre-Konvoi Pressurized Water Reactor
PSM: software tool for simulating, prototyping, and monitoring of multiprocessor systems
Group updates and multiscaling: An efficient neural network approach to combinatorial optimization
Efficient evolution of accurate classification rules using a combination of gene expression programming and clonal selection
Memory-based classification with dynamic feature selection using self-organizing maps for pattern evaluation
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