Results 161 to 170 of about 2,029 (212)
Digitalizing electroplating requires both domain knowledge and interoperability. This work introduces PlatOn, a domain ontology for trivalent chromium plating and coating characterization, and a hybrid pipeline that aligns it to a mid‐level reference ontology by combining eight similarity metrics with language model reasoning. Expert‐validated mappings
Janik Harter +10 more
wiley +1 more source
Multilayer Self‐Limiting Electrospray Deposition via Stepped Voltage Bias
Self‐limiting electrospray deposition (SLED) uses a high voltage to generate and deposit a charged payload on a target surface. The coating retains its charge, repelling newly arriving material. SLED thickness can be decreased by applying a secondary bias to the target.
Madhuri Deb +3 more
wiley +1 more source
Controlling the Field Assisted Sintering Technology (FAST) parameters, dwell temperature and cooling rate, significantly influences the microstructural evolution in titanium aluminide GE4822. Significant γ‐lamellar colonies develop only upon cooling through the α‐transus.
Jack Krohn, James Pepper, Martin Jackson
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Postbuild annealing systematically modifies the phase fractions and morphology of EB‐PBF processed Mo–9Si–8B. Quantitative microstructure–property correlations reveal how controlled phase evolution enhances high‐temperature compressive strength and creep resistance.
Christopher Schmidt +5 more
wiley +1 more source
Edible electronics needs integrated logic circuits for computation and control. This work presents a potentially edible printed chitosan‐gated transistor with a design optimized for integration in circuits. Its implementation in integrated logic gates and circuits operating at low voltage (0.7 V) is demonstrated, as well as the compatibility with an ...
Giulia Coco +8 more
wiley +1 more source
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Detection, mining and forecasting of impact load in power load forecasting
Applied Mathematics and Computation, 2005zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Jianzhou Wang, Zhixin Ma, Lian Li
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A Fast and Stable Forecasting Model to Forecast Power Load
International Journal of Pattern Recognition and Artificial Intelligence, 2015As the traditional gray forecasting model GM(1, 1) has poor performance in forecasting the fast-growing power load, we present a chaotic co-evolutionary particle swarm optimization (CCPSO) algorithm, one with better efficiency than the PSO algorithm. Based on the GM(1, 1) model, the CCPSO algorithm is adopted to solve the values of parameters a and b ...
Li-Zhi Tan +5 more
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Power Load Forecasting Using a Refined LSTM
Proceedings of the 2019 11th International Conference on Machine Learning and Computing, 2019The power load forecasting is based on historical energy consumption data of a region to forecast the power consumption of the region for a period of time in the future. Accurate forecasting can provide effective and reliable guidance for power construction and grid operation. This paper proposed a power load forecasting approach using a two LSTM (long-
Dedong Tang +4 more
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The Power Load Forecasting by Kernel PCA
2010We use one year's subset to train the Support Vector Machines (SVM) and the next year's data was used for testing with Kernel Principal Components Analysis (KPCA). This is clearly not optimal for a non-stationary time series such as we have here nevertheless the MAPE of peak load data set with back-propagation neural network [Chuang et al., 1998] is 3 ...
Fang-Tsung Liu +3 more
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Risk adjusted forecasting of electric power load
2014 American Control Conference, 2014Load forecasting of energy demand is usually focused on mean values in related statistical models and ignores rare peak events. This paper provides Extreme Value Theory analysis of the peak events in electrical power load demand. It estimates risk of the peak events by combining forecast of the mean with extreme value modeling of distribution tail. The
Saahil Shenoy, Dimitry M. Gorinevsky
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