197 © Springer International Publishing AG 2018 C.M. Botero et al. (eds.), Beach Management Tools - Concepts, Methodologies and Case Studies, Coastal Research Library 24, https://doi.org/10.1007/978-3-319-58304-4_10 Chapter 10 A Hybrid CA-ANN-Fuzzy Model for Simulating Coastal Changing Patterns Jorge Rocha, Francisco Gutierres, Pedro Gomes, and Ana Cláudia Teodoro Abstract Shoreline erosion is a problem that causes major concerns to coastal cit- ies worldwide. About 70% of the world’s sandy beaches retreated at a rate of 0.5– 1.0 m.year -1 . Therefore, the protection against beach loss and appropriate land management along the shoreline are critical issues that need to be addressed. The modelling and simulation of dynamic and complex systems, such as coastal areas, are important for the defnition of an innovative planning and management strategy. To explore sandy beaches threatened by shoreline retreat, this works aims to develop a geosimulation hybrid model. The geosimulation (geocomputation) is an emergent feld of analysis embracing heuristic search, artifcial neural networks and cellular automata, among others. In this chapter we present a method to simulate both the coast line and the land use/cover evolution in a developed costal area reality, by coupling cellular automata (CA) and multi-layer perceptron (MLP) artifcial neural network (ANN) with fuzzy set theory (CA–ANN-Fuzzy) in a GIS environment. Such alterations simulation solely by means of cellular automata isn’t suitable, because these models, in its more conventional structure, comprise limitations in the space parameters and transition rules. In this work a neural network is used to J. Rocha Institute of Geography and Spatial Planning, Universidade de Lisboa, Rua Branca Edmée Marques, 1600-276, Lisboa, Portugal e-mail: jorge.rocha@campus.ul.pt F. Gutierres () Big Data Analytics Unit, Eurecat – Technology Centre of Catalonia, núm. 54-56. Edifci A, Camí Antic de València, 08005 Barcelona, Spain e-mail: francisco.sacramento@eurecat.org P. Gomes Department of Environment and Agriculture, National Statistics Institute, Avenida António José de Almeida, 1000-043 Lisbon, Portugal e-mail: pedro.gomes@ine.pt A.C. Teodoro Earth Sciences Institute (ICT) and Department of Geosciences, Environment and Land Planning, Faculty of Sciences, University of Porto, Rua do Campo Alegre, 4169-007 Porto, Portugal e-mail: amteodor@fc.up.pt