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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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Abstract

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

Molecular Computing and Bioinformatics

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ISBN: 9783039211951 9783039211968 Year: Pages: 390 DOI: 10.3390/books978-3-03921-196-8 Language: English
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Technology (General) --- Biotechnology
Added to DOAB on : 2019-08-28 11:21:27
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This text will provide the most recent knowledge and advances in the area of molecular computing and bioinformatics. Molecular computing and bioinformatics have a close relationship, paying attention to the same object but working towards different orientations. The articles will range from topics such as DNA computing and membrane computing to specific biomedical applications, including drug R&D and disease analysis.

Keywords

prostate cancer --- Mycoplasma hominis --- endoplasmic reticulum --- systems biology --- protein targeting --- biomedical text mining --- big data --- Tianhe-2 --- parallel computing --- load balancing --- bacterial computing --- bacteria and plasmid system --- Turing universality --- recursively enumerable function --- miRNA biogenesis --- structural patterns --- DCL1 --- protein–protein interaction (PPI) --- clustering --- protein complex --- penalized matrix decomposition --- avian influenza virus --- interspecies transmission --- amino acid mutation --- machine learning --- Bayesian causal model --- causal direction learning --- K2 --- brain storm optimization --- line graph --- Cartesian product graph --- join graph --- atom-bond connectivity index --- geometric arithmetic index --- P-glycoprotein --- efflux ratio --- in silico --- machine learning --- hierarchical support vector regression --- absorption --- distribution --- metabolism --- excretion --- toxicity --- image encryption --- chaotic map --- DNA coding --- Hamming distance --- Stenotrophomonas maltophilia --- iron acquisition systems --- iron-depleted --- RAST server --- NanoString Technologies --- siderophores --- gene fusion data --- gene susceptibility prioritization --- evaluating driver partner --- gene networks --- drug-target interaction prediction --- machine learning --- drug discovery --- microRNA --- environmental factor --- structure information --- similarity network --- bioinformatics --- identification of Chinese herbal medicines --- biochip technology --- DNA barcoding technology --- DNA strand displacement --- cascade --- 8-bit adder/subtractor --- domain label --- Alzheimer’s disease --- gene coding protein --- sequence information --- support vector machine --- classification --- adverse drug reaction prediction --- heterogeneous information network embedding --- stacking denoising auto-encoder --- meta-path-based proximity --- Panax ginseng --- oligopeptide transporter --- flowering plant --- phylogeny --- transcription factor --- multiple interaction networks --- function prediction --- multinetwork integration --- low-dimensional representation --- dihydrouridine --- nucleotide physicochemical property --- pseudo dinucleotide composition --- RNA secondary structure --- ensemble classifier --- diabetes mellitus --- hypoxia-inducible factor-1? --- angiogenesis --- bone formation --- osteogenesis --- protein transduction domain --- membrane computing --- edge detection --- enzymatic numerical P system --- resolution free --- molecular computing --- molecular learning --- DNA computing --- self-organizing systems --- pattern classification --- machine learning --- laccase --- Brassica napus --- lignification --- stress --- molecular computing --- bioinformatics --- machine learning --- protein --- DNA --- RNA --- drug --- bio-inspired

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