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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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Some of the most beautiful studies in Mathematics are related to Symmetry and Geometry. For this reason, we select here some contributions about such aspects and Discrete Geometry. As we know, Symmetry in a system means invariance of its elements under conditions of transformations. When we consider network structures, symmetry means invariance of adjacency of nodes under the permutations of node set. The graph isomorphism is an equivalence relation on the set of graphs. Therefore, it partitions the class of all graphs into equivalence classes. The underlying idea of isomorphism is that some objects have the same structure if we omit the individual character of their components. A set of graphs isomorphic to each other is denominated as an isomorphism class of graphs. The automorphism of a graph will be an isomorphism from G onto itself. The family of all automorphisms of a graph G is a permutation group.

strongly regular graph --- automorphism group --- orbit matrix --- binary polyhedral group --- icosahedron --- dodecahedron --- 600-cell --- Electric multiple unit trains --- high-level maintenance planning --- time window --- 0–1 programming model --- particle swarm algorithm --- fixed point --- split-quaternion --- quadratic polynomial --- split-octonion --- neutrosophic set --- neutrosophic rough set --- pessimistic (optimistic) multigranulation neutrosophic approximation operators --- complete lattice --- rough set --- matroid --- operator --- attribute reduction --- graded rough sets --- rough intuitionistic fuzzy sets --- dominance relation --- logical conjunction operation --- logical disjunction operation --- multi-granulation --- planar point set --- convex polygon --- disjoint holes --- fuzzy logic --- pseudo-BCI algebra --- quasi-maximal element --- KG-union --- quasi-alternating BCK-algebra --- quality function deployment --- engineering characteristics --- group decision making --- 2-tuple --- metro station --- emergency routes --- graph partitioning --- graph clustering --- invariant measures --- partition comparison --- finite automorphism groups --- graph automorphisms --- Fuzzy sets --- ring --- normed space --- fuzzy normed ring --- fuzzy normed ideal --- fuzzy implication --- quantum B-algebra --- q-filter --- quotient algebra --- basic implication algebra --- Detour–Harary index --- maximum --- unicyclic --- bicyclic --- cacti --- three-way decisions --- intuitionistic fuzzy sets --- multi-granulation rough intuitionistic fuzzy sets --- granularity importance degree --- complexity --- Chebyshev polynomials --- gear graph --- pyramid graphs --- edge detection --- Laplacian operation --- regularization --- parameter selection --- performance evaluation --- aggregation operator --- triangular norm --- ?-convex set --- atom-bond connectivity index --- geometric arithmetic index --- line graph --- generalized bridge molecular graph --- graceful labeling --- edge graceful labeling --- edge even graceful labeling --- polar grid graph --- graph --- good drawing --- crossing number --- join product --- cyclic permutation --- nonlinear --- synchronized --- linear discrete --- chaotic system --- algorithm --- generalized permanental polynomial --- coefficient --- co-permanental --- isoperimetric number --- random graph --- intersection graph --- social network --- Abel–Grassmann’s groupoid (AG-groupoid) --- Abel–Grassmann’s group (AG-group) --- involution AG-group --- commutative group --- filter --- graceful labeling --- edge even graceful labeling --- cylinder grid graph --- selective maintenance --- multi-state system --- human reliability --- optimization --- genetic algorithm --- hypernear-ring --- multitransformation --- embedding --- distance matrix (spectrum) --- distance signlees Laplacian matrix (spectrum) --- (generalized) distance matrix --- spectral radius --- transmission regular graph --- graph --- good drawing --- crossing number --- join product --- cyclic permutation --- cyclic associative groupoid (CA-groupoid) --- cancellative --- variant CA-groupoids --- decomposition theorem --- construction methods