Search results: Found 3

Listing 1 - 3 of 3
Sort by
Intelligent Optimization Modelling in Energy Forecasting

Author:
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
License:

Loading...
Export citation

Choose an application

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

Deep Learning Applications with Practical Measured Results in Electronics Industries

Authors: --- --- ---
ISBN: 9783039288632 / 9783039288649 Year: Pages: 272 DOI: 10.3390/books978-3-03928-864-9 Language: eng
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Technology (General) --- General and Civil Engineering
Added to DOAB on : 2020-06-09 16:38:57
License:

Loading...
Export citation

Choose an application

Abstract

This book collects 14 articles from the Special Issue entitled “Deep Learning Applications with Practical Measured Results in Electronics Industries” of Electronics. Topics covered in this Issue include four main parts: (1) environmental information analyses and predictions, (2) unmanned aerial vehicle (UAV) and object tracking applications, (3) measurement and denoising techniques, and (4) recommendation systems and education systems. These authors used and improved deep learning techniques (e.g., ResNet (deep residual network), Faster-RCNN (faster regions with convolutional neural network), LSTM (long short term memory), ConvLSTM (convolutional LSTM), GAN (generative adversarial network), etc.) to analyze and denoise measured data in a variety of applications and services (e.g., wind speed prediction, air quality prediction, underground mine applications, neural audio caption, etc.). Several practical experiments were conducted, and the results indicate that the performance of the presented deep learning methods is improved compared with the performance of conventional machine learning methods.

Keywords

computational intelligence --- offshore wind --- forecasting --- machine learning --- neural networks --- neuro-fuzzy systems --- humidity sensor --- data fusion --- nonlinear optimization --- multiple linear regression --- GSA-BP --- geometric errors correction --- kinematic modelling --- lateral stage errors --- Imaging Confocal Microscope --- K-means clustering --- data partition --- Least Squares method --- deep learning --- multivariate time series forecasting --- multivariate temporal convolutional network --- CNN --- hyperspectral image classification --- information measure --- transfer learning --- neighborhood noise reduction --- visual tracking --- update occasion --- update mechanism --- background model --- network layer contribution --- saliency information --- geometric errors --- rigid body kinematics --- lateral stage errors --- imaging confocal microscope --- MCM uncertainty evaluation --- dot grid target --- smart grid --- foreign object --- binary classification --- convolutional network --- image inpainting --- content reconstruction --- instance segmentation --- underground mines --- intelligent surveillance --- residual networks --- compressed sensing --- image compression --- image restoration --- discrete wavelet transform --- intelligent tire manufacturing --- digital shearography --- faster region-based CNN --- tire bubble defects --- tire quality assessment --- unmanned aerial vehicle --- UAV --- trajectory planning --- GA --- A* --- multiple constraints --- recommender system --- human computer interaction --- eye-tracking device --- deep learning --- oral evaluation --- generative adversarial network --- neural audio caption --- gated recurrent unit --- long short-term memory --- deep learning --- machine learning --- supervised learning --- unsupervised learning --- reinforcement learning --- optimization techniques

Planning, Development and Management of Sustainable Cities

Authors: ---
ISBN: 9783038979067 9783038979074 Year: Pages: 440 DOI: 10.3390/books978-3-03897-907-4 Language: English
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Technology (General) --- General and Civil Engineering --- Environmental Engineering
Added to DOAB on : 2019-05-09 17:16:14
License:

Loading...
Export citation

Choose an application

Abstract

The concept of ‘sustainable urban development’ has been pushed to the forefront of policymaking and politics as the world wakes up to the impacts of climate change and the destructive effects of the Anthropocene. Climate change has emerged to be one of the biggest challenges faced by our planet today, threatening both built and natural systems with long-term consequences, which may be irreversible. While there is a vast body of literature on sustainability and sustainable urban development, there is currently limited focus on how to cohesively bring together the vital issues of the planning, development, and management of sustainable cities. Moreover, it has been widely stated that current practices and lifestyles cannot continue if we are to leave a healthy living planet to not only the next generation, but also to the generations beyond. The current global school strikes for climate action (known as Fridays for Future) evidences this. The book advocates the view that the focus needs to rest on ways in which our cities and industries can become green enough to avoid urban ecocide. This book fills a gap in the literature by bringing together issues related to the planning, development, and management of cities and focusing on a triple-bottom-line approach to sustainability.

Keywords

spatial decision support systems --- urban planning --- sustainability indicators --- urban metabolism --- sustainable regional development --- land use governance --- regional stakeholder involvement --- precision farming (PF) --- wood fuel --- technology roadmapping (TRM) --- open innovation (OI) --- Germany --- sustainability assessment --- sustainable urban development --- neighborhood sustainability --- neighborhood sustainability assessment index --- sustainable city --- Ipoh --- Malaysia --- scaling-up strategy --- sustainable development --- local new town --- neoliberal capitalism --- Wujin --- China --- low-energy transport --- carbon --- energy consumption --- sociotechnical transition --- innovation --- cities --- United Kingdom --- sustainability --- tree --- urban forest --- forest values --- urban transport --- sustainable transport --- developing cities --- medium-sized cities --- infrastructure --- transport projects --- sustainability --- knowledge management --- practitioner perceptions --- frames --- framing processes --- low carbon cities --- visioning --- urban resilience --- sustainability --- sustainability literacy --- urban development --- public participation --- urban planning --- civic engagement --- green economy --- built environment sector --- eco-cities --- sustainable urban development --- green innovation --- low carbon economy --- socio-technical transition --- urban fire --- spatio-temporal features --- SDM, humidity --- GDP --- the fire assimilation effect --- fire inertia effect --- fire caution effect --- urban land development --- natural environmental impact --- driving forces-pressure-state-impact-policy and pattern (DPSIP) --- water supply --- demand --- time-series forecasting --- ARIMA --- urban water sustainability --- Istanbul --- ecosystem approach --- urban ecology --- eco-cities --- process-function ecology --- heat island mitigation --- urban forestry --- green infrastructure --- ecological landscape management --- sustainability index --- mixed land-use --- neighbourhood --- travel behaviour --- perception --- indicator --- stakeholder --- megacity --- co-design --- co-production --- bottom-up --- anthropogenic impact --- environmental threshold --- road grades --- heavy-duty vehicles --- emissions --- sustainable transportation --- China --- water asset management --- Gap analysis --- LOS (level of service) --- PIs (performance indicators) --- customer value --- noise pollution --- low-frequency noise --- DEFRA --- human well-being --- sustainability --- power poles --- City Biodiversity Index --- Satoyama Index --- land use mixture --- land cover --- GIS --- sustainability --- sustainable development --- sustainable urban development --- sustainable city --- sustainable urban ecosystems --- sustainability assessment --- smart cities

Listing 1 - 3 of 3
Sort by
Narrow your search

Publisher

MDPI - Multidisciplinary Digital Publishing Institute (3)


License

CC by-nc-nd (3)


Language

english (2)

eng (1)


Year
From To Submit

2020 (2)

2019 (1)