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Book
Overcoming Data Scarcity in Earth Science
Authors: --- --- ---
ISBN: 3039282115 3039282107 Year: 2020 Publisher: MDPI - Multidisciplinary Digital Publishing Institute

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Abstract

heavily Environmental mathematical models represent one of the key aids for scientists to forecast, create, and evaluate complex scenarios. These models rely on the data collected by direct field observations. However, assembly of a functional and comprehensive dataset for any environmental variable is difficult, mainly because of i) the high cost of the monitoring campaigns and ii) the low reliability of measurements (e.g., due to occurrences of equipment malfunctions and/or issues related to equipment location). The lack of a sufficient amount of Earth science data may induce an inadequate representation of the response’s complexity in any environmental system to any type of input/change, both natural and human-induced. In such a case, before undertaking expensive studies to gather and analyze additional data, it is reasonable to first understand what enhancement in estimates of system performance would result if all the available data could be well exploited. Missing data imputation is an important task in cases where it is crucial to use all available data and not discard records with missing values. Different approaches are available to deal with missing data. Traditional statistical data completion methods are used in different domains to deal with single and multiple imputation problems. More recently, machine learning techniques, such as clustering and classification, have been proposed to complete missing data. This book showcases the body of knowledge that is aimed at improving the capacity to exploit the available data to better represent, understand, predict, and manage the behavior of environmental systems at all practical scales.


Book
Machine Learning for Energy Systems
Author:
Year: 2020 Publisher: Basel, Switzerland MDPI - Multidisciplinary Digital Publishing Institute

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Abstract

This volume deals with recent advances in and applications of computational intelligence and advanced machine learning methods in power systems, heating and cooling systems, and gas transportation systems. The optimal coordinated dispatch of the multi-energy microgrids with renewable generation and storage control using advanced numerical methods is discussed. Forecasting models are designed for electrical insulator faults, the health of the battery, electrical insulator faults, wind speed and power, PV output power and transformer oil test parameters. The loads balance algorithm for an offshore wind farm is proposed. The information security problems in the energy internet are analyzed and attacked using information transmission contemporary models, based on blockchain technology. This book will be of interest, not only to electrical engineers, but also to applied mathematicians who are looking for novel challenging problems to focus on.

Keywords

History of engineering & technology --- vacuum tank degasser --- rule extraction --- extreme learning machine --- classification and regression trees --- wind power: wind speed: T–S fuzzy model: forecasting --- linearization --- machine learning --- photovoltaic output power forecasting --- hybrid interval forecasting --- relevance vector machine --- sample entropy --- ensemble empirical mode decomposition --- high permeability renewable energy --- blockchain technology --- energy router --- QoS index of energy flow --- MOPSO algorithm --- scheduling optimization --- Adaptive Neuro-Fuzzy Inference System --- insulator fault forecast --- wavelet packets --- time series forecasting --- power quality --- harmonic parameter --- harmonic responsibility --- monitoring data without phase angle --- parameter estimation --- blockchain --- energy internet --- information security --- forecasting --- clustering --- energy systems --- classification --- integrated energy system --- risk assessment --- component accident set --- vulnerability --- hybrid AC/DC power system --- stochastic optimization --- renewable energy source --- Volterra models --- wind turbine --- maintenance --- fatigue --- power control --- offshore wind farm --- Interfacial tension --- transformer oil parameters --- harmonic impedance --- traction network --- harmonic impedance identification --- linear regression model --- data evolution mechanism --- cast-resin transformers --- abnormal defects --- partial discharge --- pattern recognition --- hierarchical clustering --- decision tree --- industrial mathematics --- inverse problems --- intelligent control --- artificial intelligence --- energy management system --- smart microgrid --- optimization --- Volterra equations --- energy storage --- load leveling --- cyber-physical systems --- vacuum tank degasser --- rule extraction --- extreme learning machine --- classification and regression trees --- wind power: wind speed: T–S fuzzy model: forecasting --- linearization --- machine learning --- photovoltaic output power forecasting --- hybrid interval forecasting --- relevance vector machine --- sample entropy --- ensemble empirical mode decomposition --- high permeability renewable energy --- blockchain technology --- energy router --- QoS index of energy flow --- MOPSO algorithm --- scheduling optimization --- Adaptive Neuro-Fuzzy Inference System --- insulator fault forecast --- wavelet packets --- time series forecasting --- power quality --- harmonic parameter --- harmonic responsibility --- monitoring data without phase angle --- parameter estimation --- blockchain --- energy internet --- information security --- forecasting --- clustering --- energy systems --- classification --- integrated energy system --- risk assessment --- component accident set --- vulnerability --- hybrid AC/DC power system --- stochastic optimization --- renewable energy source --- Volterra models --- wind turbine --- maintenance --- fatigue --- power control --- offshore wind farm --- Interfacial tension --- transformer oil parameters --- harmonic impedance --- traction network --- harmonic impedance identification --- linear regression model --- data evolution mechanism --- cast-resin transformers --- abnormal defects --- partial discharge --- pattern recognition --- hierarchical clustering --- decision tree --- industrial mathematics --- inverse problems --- intelligent control --- artificial intelligence --- energy management system --- smart microgrid --- optimization --- Volterra equations --- energy storage --- load leveling --- cyber-physical systems


Book
Machine Learning for Energy Systems
Author:
Year: 2020 Publisher: Basel, Switzerland MDPI - Multidisciplinary Digital Publishing Institute

Loading...
Export citation

Choose an application

Bookmark

Abstract

This volume deals with recent advances in and applications of computational intelligence and advanced machine learning methods in power systems, heating and cooling systems, and gas transportation systems. The optimal coordinated dispatch of the multi-energy microgrids with renewable generation and storage control using advanced numerical methods is discussed. Forecasting models are designed for electrical insulator faults, the health of the battery, electrical insulator faults, wind speed and power, PV output power and transformer oil test parameters. The loads balance algorithm for an offshore wind farm is proposed. The information security problems in the energy internet are analyzed and attacked using information transmission contemporary models, based on blockchain technology. This book will be of interest, not only to electrical engineers, but also to applied mathematicians who are looking for novel challenging problems to focus on.

Keywords

History of engineering & technology --- vacuum tank degasser --- rule extraction --- extreme learning machine --- classification and regression trees --- wind power: wind speed: T–S fuzzy model: forecasting --- linearization --- machine learning --- photovoltaic output power forecasting --- hybrid interval forecasting --- relevance vector machine --- sample entropy --- ensemble empirical mode decomposition --- high permeability renewable energy --- blockchain technology --- energy router --- QoS index of energy flow --- MOPSO algorithm --- scheduling optimization --- Adaptive Neuro-Fuzzy Inference System --- insulator fault forecast --- wavelet packets --- time series forecasting --- power quality --- harmonic parameter --- harmonic responsibility --- monitoring data without phase angle --- parameter estimation --- blockchain --- energy internet --- information security --- forecasting --- clustering --- energy systems --- classification --- integrated energy system --- risk assessment --- component accident set --- vulnerability --- hybrid AC/DC power system --- stochastic optimization --- renewable energy source --- Volterra models --- wind turbine --- maintenance --- fatigue --- power control --- offshore wind farm --- Interfacial tension --- transformer oil parameters --- harmonic impedance --- traction network --- harmonic impedance identification --- linear regression model --- data evolution mechanism --- cast-resin transformers --- abnormal defects --- partial discharge --- pattern recognition --- hierarchical clustering --- decision tree --- industrial mathematics --- inverse problems --- intelligent control --- artificial intelligence --- energy management system --- smart microgrid --- optimization --- Volterra equations --- energy storage --- load leveling --- cyber-physical systems


Book
Machine Learning for Energy Systems
Author:
Year: 2020 Publisher: Basel, Switzerland MDPI - Multidisciplinary Digital Publishing Institute

Loading...
Export citation

Choose an application

Bookmark

Abstract

This volume deals with recent advances in and applications of computational intelligence and advanced machine learning methods in power systems, heating and cooling systems, and gas transportation systems. The optimal coordinated dispatch of the multi-energy microgrids with renewable generation and storage control using advanced numerical methods is discussed. Forecasting models are designed for electrical insulator faults, the health of the battery, electrical insulator faults, wind speed and power, PV output power and transformer oil test parameters. The loads balance algorithm for an offshore wind farm is proposed. The information security problems in the energy internet are analyzed and attacked using information transmission contemporary models, based on blockchain technology. This book will be of interest, not only to electrical engineers, but also to applied mathematicians who are looking for novel challenging problems to focus on.

Keywords

vacuum tank degasser --- rule extraction --- extreme learning machine --- classification and regression trees --- wind power: wind speed: T–S fuzzy model: forecasting --- linearization --- machine learning --- photovoltaic output power forecasting --- hybrid interval forecasting --- relevance vector machine --- sample entropy --- ensemble empirical mode decomposition --- high permeability renewable energy --- blockchain technology --- energy router --- QoS index of energy flow --- MOPSO algorithm --- scheduling optimization --- Adaptive Neuro-Fuzzy Inference System --- insulator fault forecast --- wavelet packets --- time series forecasting --- power quality --- harmonic parameter --- harmonic responsibility --- monitoring data without phase angle --- parameter estimation --- blockchain --- energy internet --- information security --- forecasting --- clustering --- energy systems --- classification --- integrated energy system --- risk assessment --- component accident set --- vulnerability --- hybrid AC/DC power system --- stochastic optimization --- renewable energy source --- Volterra models --- wind turbine --- maintenance --- fatigue --- power control --- offshore wind farm --- Interfacial tension --- transformer oil parameters --- harmonic impedance --- traction network --- harmonic impedance identification --- linear regression model --- data evolution mechanism --- cast-resin transformers --- abnormal defects --- partial discharge --- pattern recognition --- hierarchical clustering --- decision tree --- industrial mathematics --- inverse problems --- intelligent control --- artificial intelligence --- energy management system --- smart microgrid --- optimization --- Volterra equations --- energy storage --- load leveling --- cyber-physical systems

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