Choose an application

• Reference Manager
• EndNote
• RefWorks (Direct export to RefWorks)

"Somewhere, there is always wind blowing or the sun shining." This maxim could lead the global shift from fossil to renewable energy sources, suggesting that there is enough energy available to be turned into electricity. But the already impressive numbers that are available today, along with the European Union's 20-20-20 goal - to power 20% of the EU energy consumption from renewables until 2020 -, might mislead us over the problem that the go-to renewables readily available rely on a primary energy source mankind cannot control: the weather. At the same time, the notion of the smart grid introduces a vast array of new data coming from sensors in the power grid, at wind farms, power plants, transformers, and consumers. The new wealth of information might seem overwhelming, but can help to manage the different actors in the power grid. This book proposes to view the problem of power generation and distribution in the face of increased volatility as a problem of information distribution and processing. It enhances the power grid by turning its nodes into agents that forecast their local power balance from historical data, using artificial neural networks and the multi-part evolutionary training algorithm described in this book. They pro-actively communicate power demand and supply, adhering to a set of behavioral rules this book defines, and finally solve the 0-1 knapsack problem of choosing offers in such a way that not only solves the disequilibrium, but also minimizes line loss, by elegant modeling in the Boolean domain. The book shows that the Divide-et-Impera approach of a distributed grid control can lead to an efficient, reliable integration of volatile renewable energy sources into the power grid.

Neural networks (Computer science) --- Artificial neural networks --- Nets, Neural (Computer science) --- Networks, Neural (Computer science) --- Neural nets (Computer science) --- Artificial intelligence --- Natural computation --- Soft computing --- Smart Grid --- Power Grid Management --- Artificial Intelligence --- Boolean Algebra

Choose an application

• Reference Manager
• EndNote
• RefWorks (Direct export to RefWorks)

In dieser Arbeit wird die Eignung des Instrumentariums der neuronalen Netze, im Konkreten der autoregressiven Neuronale-Netz-Modelle (ARNN), zur Modellierung und Prognose von makrooekonomischen Zeitreihen untersucht und mit jenen der autoregressiven (AR) und autoregressiven Moving-Average-Modelle (ARMA) verglichen. Als beispielhaftes Anwendungsgebiet werden die beiden monatlichen Zeitreihen der oesterreichischen Arbeitslosenrate und des oesterreichischen Industrieproduktionsindex herangezogen. Die Arbeit beinhaltet eine Reihe von Erweiterungen an den Methoden und Algorithmen im Zusammenhang mi

Economic forecasting. --- Neural networks (Computer science) --- Artificial neural networks --- Nets, Neural (Computer science) --- Networks, Neural (Computer science) --- Neural nets (Computer science) --- Artificial intelligence --- Natural computation --- Soft computing --- Economics --- Forecasting --- Economic indicators --- ARNN-Modelle --- Güte von Mehr-Schritt-Prognosen --- Koller --- linearer --- makroökonomischen --- makroökonomischer --- Modelle --- Netzen --- neuronalen --- Nicht-Linearität --- Prognose --- Vergleich --- Zeitreihe --- Zeitreihen --- Zeitreihenanalyse

Choose an application

• Reference Manager
• EndNote
• RefWorks (Direct export to RefWorks)

Neural computers --- Neural Networks (Computer) --- Ordinateurs neuronaux --- Neural computers. --- Neural Computation. --- Neural net computers --- Neural network computers --- Neurocomputers --- Connectionist Models --- Models, Neural Network --- Neural Network Models --- Perceptrons --- Connectionist Model --- Model, Connectionist --- Model, Neural Network --- Models, Connectionist --- Network Model, Neural --- Network Models, Neural --- Network, Neural (Computer) --- Networks, Neural (Computer) --- Neural Network (Computer) --- Neural Network Model --- Perceptron --- Electronic digital computers --- Natural computation --- Artificial intelligence --- Neurale netwerken. --- Computational Neural Networks --- Computational Neural Network --- Computer Neural Network --- Computer Neural Networks --- Network, Computational Neural --- Network, Computer Neural --- Networks, Computational Neural --- Networks, Computer Neural --- Neural Network, Computational --- Neural Network, Computer --- Neural Networks, Computational --- Neural Networks, Computer. --- Neural networks (Computer science) --- Neural Networks, Computer --- Réseaux neuronaux (Informatique) --- Artificial neural networks --- Nets, Neural (Computer science) --- Networks, Neural (Computer science) --- Neural nets (Computer science) --- Soft computing

Choose an application

• Reference Manager
• EndNote
• RefWorks (Direct export to RefWorks)

This volume is number four in a series of proceedings volumes from the International Symposia on Fractals in Biology and Medicine in Ascona, Switzerland which have been inspired by the work of Benoît Mandelbrot seeking to extend the concepts towards the life sciences. It highlights the potential that fractal geometry offers for elucidating and explaining the complex make-up of cells, tissues and biological organisms either in normal or in pathological conditions, including the structural changes that occur in tumours. It helps develop the concepts, questions and methods required in research on fractal biology and natural phenomena and to evidence the pitfalls of a too simplistic application of these principles in investigating topical subjects of biology and medicine. It discusses present and future applications of fractal geometry, bringing together cellular and molecular biology, engineering, mathematics, physics, medicine and other disciplines and allowing an interdisciplinary vision. The book should be of interest to researchers and students from molecular and cell biology, biomedicine, biomathematics, analytical morphology, immunology and neurology who are interested in the combination of mathematics and life sciences.

Medicine --- Biomathematics --- Fractals --- Mathematics --- Clinical sciences --- Medical profession --- Human biology --- Life sciences --- Medical sciences --- Pathology --- Physicians --- Physiology --- Biology --- Computer simulation. --- Mathematical Models of Cognitive Processes and Neural Networks. --- Physiological, Cellular and Medical Topics. --- Computer Appl. in Life Sciences. --- Simulation and Modeling. --- Mathematics. --- Data processing. --- Computer modeling --- Computer models --- Modeling, Computer --- Models, Computer --- Simulation, Computer --- Electromechanical analogies --- Mathematical models --- Simulation methods --- Model-integrated computing --- Animal physiology --- Animals --- Anatomy --- Neural networks (Computer science) . --- Biomathematics. --- Bioinformatics . --- Computational biology . --- Bioinformatics --- Bio-informatics --- Biological informatics --- Information science --- Computational biology --- Systems biology --- Artificial neural networks --- Nets, Neural (Computer science) --- Networks, Neural (Computer science) --- Neural nets (Computer science) --- Artificial intelligence --- Natural computation --- Soft computing --- Data processing

Choose an application

• Reference Manager
• EndNote
• RefWorks (Direct export to RefWorks)

Fuzzy Logic. --- Algorithms. --- Diagnosis, Computer-Assisted. --- Neural Networks, Computer. --- Computational Neural Networks --- Connectionist Models --- Models, Neural Network --- Neural Network Models --- Neural Networks (Computer) --- Perceptrons --- Computational Neural Network --- Computer Neural Network --- Computer Neural Networks --- Connectionist Model --- Model, Connectionist --- Model, Neural Network --- Models, Connectionist --- Network Model, Neural --- Network Models, Neural --- Network, Computational Neural --- Network, Computer Neural --- Network, Neural (Computer) --- Networks, Computational Neural --- Networks, Computer Neural --- Networks, Neural (Computer) --- Neural Network (Computer) --- Neural Network Model --- Neural Network, Computational --- Neural Network, Computer --- Neural Networks, Computational --- Perceptron --- Computer-Assisted Diagnosis --- Computer Assisted Diagnosis --- Computer-Assisted Diagnoses --- Diagnoses, Computer-Assisted --- Diagnosis, Computer Assisted --- Algorithm --- Logic, Fuzzy