Andere Kunden interessierten sich auch für
![Policy-based Data Sharing for Event-driven Services in B2B Networks]( "Policy-based Data Sharing for Event-driven Services in B2B Networks")
Policy-based Data Sharing for Event-driven Services in B2B Networks40,99 €![Practical Insights into Data-Driven Urban Development]( "Practical Insights into Data-Driven Urban Development")
Practical Insights into Data-Driven Urban Development56,99 €![Model-Driven Validation Approach for Enterprise Architectures]( "Model-Driven Validation Approach for Enterprise Architectures")
Model-Driven Validation Approach for Enterprise Architectures58,99 €![Data-Driven Alexa Skills]( "Data-Driven Alexa Skills")
Data-Driven Alexa Skills53,99 €![Landscape Simulation Modeling]( "Landscape Simulation Modeling")
Landscape Simulation Modeling39,99 €![Building the e-World Ecosystem]( "Building the e-World Ecosystem")
Building the e-World Ecosystem42,99 €![Geo-Informatics in Resource Management and Sustainable Ecosystem]( "Geo-Informatics in Resource Management and Sustainable Ecosystem")
Geo-Informatics in Resource Management and Sustainable Ecosystem40,99 €
Data-driven modelling is the area of hydro informatics undergoing fast development. This book reviews the main concepts and approaches of data-driven modelling, which is based on computational intelligence and machine-learning methods. A brief overview of the main methods - neural networks, fuzzy rule-based systems and genetic algorithms. Recent developments in machine learning have expanded data-driven modelling (DDM) capabilities, allowing artificial intelligence to infer the behavior of a system by computing and exploiting correlations between observed variables within it. Machine learning algorithms may enable the use of increasingly available 'big data' and assist applying ecosystem service models across scales, analyzing and predicting the flows of these services to disaggregated beneficiaries.