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Micro/Nano Manufacturing

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ISBN: 9783039211692 9783039211708 Year: Pages: 208 DOI: 10.3390/books978-3-03921-170-8 Language: English
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Technology (General)
Added to DOAB on : 2019-12-09 11:49:15
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Abstract

Micro manufacturing involves dealing with the fabrication of structures in the size range of 0.1 to 1000 µm. The scope of nano manufacturing extends the size range of manufactured features to even smaller length scales—below 100 nm. A strict borderline between micro and nano manufacturing can hardly be drawn, such that both domains are treated as complementary and mutually beneficial within a closely interconnected scientific community. Both micro and nano manufacturing can be considered as important enablers for high-end products. This Special Issue of Applied Sciences is dedicated to recent advances in research and development within the field of micro and nano manufacturing. The included papers report recent findings and advances in manufacturing technologies for producing products with micro and nano scale features and structures as well as applications underpinned by the advances in these technologies.

Keywords

fluid jet polishing --- deterministic polishing --- variable pitch path --- residual error optimization --- path adaptability --- chatter identification --- three-dimensional elliptical vibration cutting --- empirical mode decomposition --- intrinsic mode function --- feature extraction --- micro-EDM molds --- micro-lens array --- contactless embossing --- friction coefficient --- micro 3D printing --- micro stereolithography --- process parameter optimization --- Taguchi’s method --- multi-objective particle swarm optimization --- flow control --- culture dish adapter --- small recess structure --- closed environment --- perfusion culture --- optical encoder --- grating --- blaze --- injection molding --- micro assembly --- active alignment --- opto-ASIC --- wafer-level optics --- antireflection nanostructure --- microlens array mold --- ultraprecision machining --- anodic aluminum oxide --- spatial uncertainty modeling --- additive manufacturing --- uncertainty quantification --- Image segmentation --- gaussian process modeling --- additive manufacturing --- selective laser melting --- surface roughness --- design of experiments --- Ti6Al4V --- SERS --- Surface-enhanced Raman scattering --- nanosphere array --- nanocone array --- hot embossing --- nanoimprinting --- plasma nitriding --- micro-nozzle --- micro-spring --- nitrogen supersaturation --- hardening --- hydrophobicity --- stiffness control --- product development --- conceptual design --- micro assembly --- data structure --- design for manufacturability --- low PC clinker --- Portland limestone ternary fiber–cement nanohybrids --- flexural strength --- TGA/dTG --- XRD --- MIP --- water impermeability tests --- micro and nano manufacturing --- micro-fluidics --- micro-optics --- micro and nano additive manufacturing --- micro-assembly --- surface engineering and interface nanotechnology --- micro factories --- micro reactors --- micro sensors --- micro actuators

Intelligent Optimization Modelling in Energy Forecasting

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ISBN: 9783039283644 9783039283651 Year: Pages: 262 DOI: 10.3390/books978-3-03928-365-1 Language: English
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Computer Science
Added to DOAB on : 2020-04-07 23:07:09
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Accurate energy forecasting is important to facilitate the decision-making process in order to achieve higher efficiency and reliability in power system operation and security, economic energy use, contingency scheduling, the planning and maintenance of energy supply systems, and so on. In recent decades, many energy forecasting models have been continuously proposed to improve forecasting accuracy, including traditional statistical models (e.g., ARIMA, SARIMA, ARMAX, multi-variate regression, exponential smoothing models, Kalman filtering, Bayesian estimation models, etc.) and artificial intelligence models (e.g., artificial neural networks (ANNs), knowledge-based expert systems, evolutionary computation models, support vector regression, etc.). Recently, due to the great development of optimization modeling methods (e.g., quadratic programming method, differential empirical mode method, evolutionary algorithms, meta-heuristic algorithms, etc.) and intelligent computing mechanisms (e.g., quantum computing, chaotic mapping, cloud mapping, seasonal mechanism, etc.), many novel hybrid models or models combined with the above-mentioned intelligent-optimization-based models have also been proposed to achieve satisfactory forecasting accuracy levels. It is important to explore the tendency and development of intelligent-optimization-based modeling methodologies and to enrich their practical performances, particularly for marine renewable energy forecasting.

Keywords

short-term load forecasting --- weighted k-nearest neighbor (W-K-NN) algorithm --- comparative analysis --- empirical mode decomposition (EMD) --- particle swarm optimization (PSO) algorithm --- intrinsic mode function (IMF) --- support vector regression (SVR) --- short term load forecasting --- crude oil price forecasting --- time series forecasting --- hybrid model --- complementary ensemble empirical mode decomposition (CEEMD) --- sparse Bayesian learning (SBL) --- multi-step wind speed prediction --- Ensemble Empirical Mode Decomposition --- Long Short Term Memory --- General Regression Neural Network --- Brain Storm Optimization --- substation project cost forecasting model --- feature selection --- data inconsistency rate --- modified fruit fly optimization algorithm --- deep convolutional neural network --- multi-objective grey wolf optimizer --- long short-term memory --- fuzzy time series --- LEM2 --- combination forecasting --- wind speed --- electrical power load --- crude oil prices --- time series forecasting --- improved complete ensemble empirical mode decomposition with adaptive noise (ICEEMDAN) --- kernel learning --- kernel ridge regression --- differential evolution (DE) --- artificial intelligence techniques --- energy forecasting --- condition-based maintenance --- asset management --- renewable energy consumption --- Gaussian processes regression --- state transition algorithm --- five-year project --- forecasting --- Markov-switching --- Markov-switching GARCH --- energy futures --- commodities --- portfolio management --- active investment --- diversification --- institutional investors --- energy price hedging --- metamodel --- ensemble --- individual --- regression --- interpolation

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MDPI - Multidisciplinary Digital Publishing Institute (2)


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CC by-nc-nd (2)


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english (2)


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2020 (1)

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