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Reducing the sampling rate to as low as possible is a high priority for many factories to reduce production cost. Automatic-Virtual-Metrology (AVM) based Original Intelligent Sampling Decision (Original ISD) scheme had been previously developed for reducing the sampling rate and sustaining the VM accuracy. However, the desired sampling rate of the Original ISD scheme is fixed and set manually. Hence,...
One of the main difficulties in real-world data classification and analysis tasks is that the data distribution can be imbalanced. In this paper, a variant of the supervised learning neural network from the Adaptive Resonance Theory (ART) family, i.e., Fuzzy ARTMAP (FAM) which is equipped with a conflict-resolving facility, is proposed to classify an imbalanced dataset that represents a real problem...
In this work, a novel algorithm for the self-tuning PID parameters by using process operational data is proposed. A feasible data set is achieved on the basis of dynamic characteristic of PID control loop. With defined ε-insensitive loss function and identification confidence function, the valid data set for model identification is selected from the feasible data set. The valid data set is used to...
This paper presents a preliminary study on a hybrid renewable energy system at the Ostfalia University of Applied Sciences Wolfenbüttel, Germany. The test-bed is made up of solar photovoltaics (PV), a micro wind turbine (MWT), a micro-CHP, a fuel cell system (FC), and two storage devices (a battery system and an electrolyzer). All the installations are in the range of 1 to 6 kW electrical power output/input;...
In complex process of industrial production, it need deal with a large number of data, multiple dimensions, and generate complex data. If the neural network control indirect used, it is easy that lead to some shortcomings, such as inaccurate results and training stage of neural network lack convergence and so forth. In response to these circumstances, the integration model of data optimize processing...
In this paper a BISR architecture for embedded memories is presented. The proposed scheme utilises a multiple bank cache-like memory for repairs. Statistical analysis is used for minimisation of the total resources required to achieve a very high fault coverage. Simulation results show that the proposed BISR scheme is characterised by high efficiency and low area overhead, even for high defect densities...
The virtual product data model in its different stages is an essential prerequisite for the virtual modeling of processes and their virtual simulation. Product design starts with conceptual design including the concepts for the future productpsilas shape and function - the gestalt. In this stage, the designers work on fuzzy product data interpreted in so-called scribbles and applied to perception...
Building on the extensive research in Virtual Reality (VR), we are proposing a new dynamic prototype for modelling and simulating carbon emissions in a virtual village called VIRVIL. VIRVIL is a simulated settlement for the assessment of the impact of low and zero carbon technologies and measures in the built environment. The prototype will focus on the impact on the community as a whole, as well...
According to the demand of integrated production and the characteristic of charge plan in the steel industry, firstly, use graph theory to describe charge plan; secondly, a bi-objective charge plan model is introduced in detail considering weight range, flow limitation and other factors; To solve this model, a two-phase heuristic algorithm (THA) is introduced, which deals with the simple graph with...
Using historical data the identification of non -autonomous interval discrete dynamic model of realization bakery production is realized. The cyclic periodic of this model is researched.
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