Estimation of PM10-Bound As, Cd, Ni and Pb Levels by Means of Statistical Modelling: PLSR and ANN Approaches

Water, Air, and Soil Pollution

Volumn 226, Issue 8, 2015, Pages

  Santos, Germán ^a   Fernández Olmo, Ignacio ^a   Irabien, Ángel ^a  

^a UNIVERSITY OF CANTABRIA   (Spain)

Author keywords

ANN; Metals; PLSR; PM10; Statistical modelling

Indexed keywords

AIR QUALITY; LEAST SQUARES APPROXIMATIONS; METALS; NEURAL NETWORKS; URBAN GROWTH;

AIR QUALITY ASSESSMENT; ANALYTICAL DETERMINATION; METALS AND METALLOIDS; OBJECTIVE ESTIMATIONS; PARTIAL LEAST SQUARES REGRESSIONS (PLSR); PLSR; PM10; STATISTICAL MODELLING;

PRINCIPAL COMPONENT ANALYSIS;

ARSENIC; CADMIUM; LEAD; NICKEL;

AIR QUALITY; ARSENIC; ARTIFICIAL NEURAL NETWORK; ATMOSPHERIC POLLUTION; CADMIUM; EUROPEAN UNION; LEAD; NICKEL; NUMERICAL MODEL; PARTICULATE MATTER;

AIR ANALYSIS; AIR POLLUTION; AIR QUALITY; ARTICLE; ARTIFICIAL NEURAL NETWORK; CHEMICAL ANALYSIS; CONCENTRATION (PARAMETERS); CONTROLLED STUDY; ENVIRONMENTAL MONITORING; GEOGRAPHIC DISTRIBUTION; MATHEMATICAL COMPUTING; PARTIAL LEAST SQUARES REGRESSION; PARTICULATE MATTER; PRINCIPAL COMPONENT ANALYSIS; PROCESS DEVELOPMENT; STATISTICAL MODEL; UNCERTAINTY; URBAN AREA; VALIDATION PROCESS;

CANTABRIA; SPAIN;

EID: 84938060791     PISSN: 00496979     EISSN: 15732932     Source Type: Journal    
DOI: 10.1007/s11270-015-2526-z     Document Type: Article

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