The paper has proposed a novel image visual saliency detection algorithm based on local and global characteristic features to detect natural images in CIELab colorful space. The algorithm has divided the image into su...
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Cell type identification is a crucial step in single-cell RNA-seq (scRNA-seq) data analysis. The supervised cell type identification method is a preferred solution due to its accuracy and efficiency. The performance o...
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In this paper we proposed a fuzzy neural network model which can embody a fuzzy Takagi-Sugeno model and carry out fuzzy inference and support structure of fuzzy rules. The algorithm of model properties improvement con...
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In this paper we proposed a fuzzy neural network model which can embody a fuzzy Takagi-Sugeno model and carry out fuzzy inference and support structure of fuzzy rules. The algorithm of model properties improvement consists of new origin procedures namely input space partition, fuzzy terms number and rule number extending, low-effective fuzzy terms and rules extraction and consequent structure identification. In the proposed fuzzy modeling method we first design a rough initial fuzzy model with complete partition of input variable space (or initial partition based on expert knowledge). Then a fuzzy neural network is constructed based on rough fuzzy model. By learning of the neural network we can tune of embedded initial fuzzy model. Next, the additional identifying procedure is introduced based on additional partition of fuzzy input space to improve the properties of initial fuzzy model and to decrease the model error. In final part of identification some low-effective terms and rules are extracted and final rule based model is formed. To apply the new identifying procedures and to introduce possibilities of variability of their properties some parameters have to be put in. The strategy of such parameter optimization is provided by new advanced genetic algorithm. Criterion and cost function has been selected as global fuzzy-neuro model error. To show the applicability of new method and to make a possibility to real systems modeling, we designed the fuzzy-neural network programme tool FUZNET. There were two case studies performed: the first case study presents the prediction of Mackey-Glass time series with using fuzzy-neural regression model (FNRM) predictor; the second case study presents task of a coke-oven gas cooler modeling.
The focus in this paper is on active fault diagnosis (AFD) in closed-loop sampleddata systems. Applying the same AFD architecture as for continuous-time systems does not directly result in the same set of closed-loop ...
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The paper presents an optimization based algorithm for stabilizing retarded systems using a state derivative feedback controller. It is shown that an application of such a controller results in neutral dynamics of the...
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The position tracking control scheme is investigated in this paper for electro-hydraulic servo system with parameter uncertainties and external disturbances. First, the total uncertainty is estimated via an extended s...
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A systems re-engineering technique to integrated control and supervision for applications to industrial multi-zone furnaces has been elaborated by using known theories on generalized predictive control and nonlinear p...
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The maintenance of the entire life cycle of wind turbines is important for a wind power project. The main reason is that whether wind turbines can perform their best during the operation period is one of the key facto...
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ISBN:
(纸本)9781665434263
The maintenance of the entire life cycle of wind turbines is important for a wind power project. The main reason is that whether wind turbines can perform their best during the operation period is one of the key factors to measure the success or failure of a wind farm investment. However, with the increasing number of installed wind turbines, how to perform the maintenance in an efficient way will become a challenging problem. To lead better services, the first step is to analyze how the maintenance process or workflow really works in real-life scenarios. Process mining is such a technique which can perform process analysis over event logs recorded by information systems. Although various process mining case studies have been reported in current literature, there is no relevant study about the maintenance of wind turbines in the domain of energy systems. As an initial investigation, in this paper, we present a brief case study on applying process mining for wind turbine maintenance process analysis, based on several real event logs. Specifically, we have given the design of our study and reported the analysis results. We believe that the study will be of value to the community to understand the merits of how process mining technique can improve wind turbine maintenance processes in practice.
The ignition voltage of micro-satellite and MEMS fuse become more and more lower, the conventional electro-explosive devices are hardly meet the requirement. In this paper, Ni-Cr metal film bridge of different size/su...
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We consider the quasispecies spectrum reconstruction problem in amplicon reads. The main contribution of this paper is several methods to reconstruct HCV quasispecies from simulated error-free amplicon reads. Our comp...
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We consider the quasispecies spectrum reconstruction problem in amplicon reads. The main contribution of this paper is several methods to reconstruct HCV quasispecies from simulated error-free amplicon reads. Our comparison with existing methods for quasispecies spectrum reconstruction both based on shotgun and amplicon reads show significant advantages of the proposed technique. In most of the cases, even low coverage allows to reconstruct majority of quasispecies and very accurately estimate their frequencies in the simulated samples. The source code for all implemented algorithms is available at https://***/nmancuso/bioa/.
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