Fish Forum Book of abstracts 2018


Book Description

This volume includes all the abstracts of the keynotes, oral contributions and posters presented by participants on the occasion of the Forum on Fisheries Science in the Mediterranean and the Black Sea (Fish Forum 2018). Organized by the GFCM at FAO headquarters, Rome, Italy, from 10 to 14 December 2018, in collaboration with technical partners, the Fish Forum 2018 is a first-of-the-kind event gathering scientists, researchers, engineers, academics, practitioners, managers and decision-makers from around the world to discuss and share knowledge on the latest developments in fisheries science. The material contained in this book of abstracts stems from the contributions received from participants and selected by an international scientific committee based on their technical quality and relevance. The abstracts are subdivided according to the three main themes of the Fish Forum 2018: Better science for better advice; Healthy seas and sustainable fisheries; and Economic analysis and technology for societal benefit. Each theme is introduced by a keynote presentation, followed by oral presentations and posters. These documents form the basis of the discussions held during parallel sessions and poster sessions of the Fish Forum 2018.













Artificial Reefs in European Seas


Book Description

Most European seas articifial reef (AR) programmes are included in this book. Interests in ARs are varied, ranging from the "expected" fishery enhancement through mariculture and ranching, nutrient removal and into environmental and habitat protection and nature conservation.




Neural Networks with R


Book Description

Uncover the power of artificial neural networks by implementing them through R code. About This Book Develop a strong background in neural networks with R, to implement them in your applications Build smart systems using the power of deep learning Real-world case studies to illustrate the power of neural network models Who This Book Is For This book is intended for anyone who has a statistical background with knowledge in R and wants to work with neural networks to get better results from complex data. If you are interested in artificial intelligence and deep learning and you want to level up, then this book is what you need! What You Will Learn Set up R packages for neural networks and deep learning Understand the core concepts of artificial neural networks Understand neurons, perceptrons, bias, weights, and activation functions Implement supervised and unsupervised machine learning in R for neural networks Predict and classify data automatically using neural networks Evaluate and fine-tune the models you build. In Detail Neural networks are one of the most fascinating machine learning models for solving complex computational problems efficiently. Neural networks are used to solve wide range of problems in different areas of AI and machine learning. This book explains the niche aspects of neural networking and provides you with foundation to get started with advanced topics. The book begins with neural network design using the neural net package, then you'll build a solid foundation knowledge of how a neural network learns from data, and the principles behind it. This book covers various types of neural network including recurrent neural networks and convoluted neural networks. You will not only learn how to train neural networks, but will also explore generalization of these networks. Later we will delve into combining different neural network models and work with the real-world use cases. By the end of this book, you will learn to implement neural network models in your applications with the help of practical examples in the book. Style and approach A step-by-step guide filled with real-world practical examples.