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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.
rough set theory --- water quality --- attribute reduction --- core attribute --- rule extraction --- climate extreme indices (CEIs) --- ClimPACT --- GLDAS --- Expert Team on Climate Change Detection and Indices (ETCCDI) --- Expert Team on Sector-specific Climate Indices (ET-SCI) --- Dataset Licensedatabase --- geophysical monitoring --- magnetotelluric monitoring --- processing --- arthropod vector --- invasive species --- microhabitat --- species distribution modeling --- remote sensing --- data assimilation --- 3D-Var --- multi-class classification --- soil texture calculator --- k-Nearest Neighbors --- support vector machines --- decision trees --- ensemble learning --- earth-science data --- data scarcity --- missing data --- data quality --- data imputation --- statistical methods --- machine learning --- environmental modeling --- environmental observations
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This book presents interesting samples of theoretical and practical advances of symmetry in multidisciplinary engineering applications. It covers several applications, such as accessibility and traffic congestion management, path planning for mobile robots, analysis of shipment service networks, fault diagnosis methods in electrical circuits and electrical machines, geometrical issues in architecture, geometric modeling and virtual reconstruction, design of noise detectors, filters, and segmentation methods for image processing, and cyclic symmetric structures in turbomachinery applications, to name but a few. The contributions included in this book depict the state of the art in this field and lay the foundation for the possibilities that the study of symmetry has in multidisciplinary applications in the field of engineering.
express shipment --- service network design --- linearization technique --- railway network --- path planning --- mobile robot --- environmental modeling --- optimization criteria --- path search --- aged --- high order urban hospitals (HOUHs) --- accessibility --- evaluation model --- trip impedance based on public transportation --- urban traffic planning --- 3D slicer --- classification --- extension --- random forest --- segmentation --- sensitivity analysis --- support vector machine --- tumor --- thin-walled gear --- ring damper --- vibration --- energy dissipation --- friction damping --- fault diagnosis --- lifting wavelet --- local preserving projection --- Fisher linear discriminant analysis --- semi-supervised random forest --- adaptive threshold --- clustering --- edge preserving --- noise detector --- random value impulse noise --- weighted mean filter --- anomaly detection --- local data features --- BP neural network --- local monotonicity --- convexity/concavity --- local inflection --- peaks distribution --- inclined plane --- Coalbrookdale (Shropshire) --- Agustín de Betancourt --- geometric modeling --- virtual reconstruction --- industrial heritage --- industrial archaeology --- symmetry --- rampant arch --- geometry --- optimum --- flying buttresses --- cathedral --- rolling bearings --- fault diagnosis --- broad learning model --- variational mode decomposition --- Hilbert transform --- railway transportation --- time-space network --- A* algorithm --- traffic congestion --- traffic forecasting --- traffic control --- railcar flow distribution --- asymmetry --- synchronization --- topology --- electrical circuits --- electronic devices --- mechanical structures --- robots --- graphic modelling --- complex networks --- optimization --- computing applications --- feature selection --- conditional mutual information --- feature interaction --- classification --- computer engineering
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