Quantitative Analysis of Ecological Networks

Quantitative Analysis of Ecological Networks
Author: Mark R. T. Dale
Publisher: Cambridge University Press
Total Pages: 250
Release: 2021-04-15
Genre: Nature
ISBN: 1108632971
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Network thinking and network analysis are rapidly expanding features of ecological research. Network analysis of ecological systems include representations and modelling of the interactions in an ecosystem, in which species or factors are joined by pairwise connections. This book provides an overview of ecological network analysis including generating processes, the relationship between structure and dynamic function, and statistics and models for these networks. Starting with a general introduction to the composition of networks and their characteristics, it includes details on such topics as measures of network complexity, applications of spectral graph theory, how best to include indirect species interactions, and multilayer, multiplex and multilevel networks. Graduate students and researchers who want to develop and understand ecological networks in their research will find this volume inspiring and helpful. Detailed guidance to those already working in network ecology but looking for advice is also included.

Long Short-Term Memory Networks With Python

Long Short-Term Memory Networks With Python
Author: Jason Brownlee
Publisher: Machine Learning Mastery
Total Pages: 245
Release: 2017-07-20
Genre: Computers
ISBN:
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The Long Short-Term Memory network, or LSTM for short, is a type of recurrent neural network that achieves state-of-the-art results on challenging prediction problems. In this laser-focused Ebook, finally cut through the math, research papers and patchwork descriptions about LSTMs. Using clear explanations, standard Python libraries and step-by-step tutorial lessons you will discover what LSTMs are, and how to develop a suite of LSTM models to get the most out of the method on your sequence prediction problems.

Recurrent Neural Networks for Short-Term Load Forecasting

Recurrent Neural Networks for Short-Term Load Forecasting
Author: Filippo Maria Bianchi
Publisher: Springer
Total Pages: 74
Release: 2017-11-09
Genre: Computers
ISBN: 3319703382
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The key component in forecasting demand and consumption of resources in a supply network is an accurate prediction of real-valued time series. Indeed, both service interruptions and resource waste can be reduced with the implementation of an effective forecasting system. Significant research has thus been devoted to the design and development of methodologies for short term load forecasting over the past decades. A class of mathematical models, called Recurrent Neural Networks, are nowadays gaining renewed interest among researchers and they are replacing many practical implementations of the forecasting systems, previously based on static methods. Despite the undeniable expressive power of these architectures, their recurrent nature complicates their understanding and poses challenges in the training procedures. Recently, new important families of recurrent architectures have emerged and their applicability in the context of load forecasting has not been investigated completely yet. This work performs a comparative study on the problem of Short-Term Load Forecast, by using different classes of state-of-the-art Recurrent Neural Networks. The authors test the reviewed models first on controlled synthetic tasks and then on different real datasets, covering important practical cases of study. The text also provides a general overview of the most important architectures and defines guidelines for configuring the recurrent networks to predict real-valued time series.

Forecasting commodity prices using long-short-term memory neural networks

Forecasting commodity prices using long-short-term memory neural networks
Author: Ly, Racine
Publisher: Intl Food Policy Res Inst
Total Pages: 26
Release: 2021-02-10
Genre: Political Science
ISBN:
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This paper applies a recurrent neural network (RNN) method to forecast cotton and oil prices. We show how these new tools from machine learning, particularly Long-Short Term Memory (LSTM) models, complement traditional methods. Our results show that machine learning methods fit reasonably well with the data but do not outperform systematically classical methods such as Autoregressive Integrated Moving Average (ARIMA) or the naïve models in terms of out of sample forecasts. However, averaging the forecasts from the two type of models provide better results compared to either method. Compared to the ARIMA and the LSTM, the Root Mean Squared Error (RMSE) of the average forecast was 0.21 and 21.49 percent lower, respectively, for cotton. For oil, the forecast averaging does not provide improvements in terms of RMSE. We suggest using a forecast averaging method and extending our analysis to a wide range of commodity prices.

Ethernet Networking for the Small Office and Professional Home Office

Ethernet Networking for the Small Office and Professional Home Office
Author: Jan L. Harrington
Publisher: Elsevier
Total Pages: 353
Release: 2010-07-28
Genre: Computers
ISBN: 0080553605
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In a local area network (LAN) or intranet, there are many pieces of hardare trying to gain access to the network transmission media at the same time (i.e., phone lines, coax, wireless, etc.). However, a network cable or wireless transmission frequency can physically only allow one node to use it at a given time. Therefore, there must be some way to regulate which node has control of the medium (a media access control, or MAC, protocol). Ethernet is a MAC protocol; it is one way to regulate physical access to network tranmission media. Ethernet networking is used primarily by networks that are contained within a single physical location. If you need to design, install, and manage a network in such an envronment, i.e., home or small business office, then Ethernet Networking for the Small Office and Professional Home Office will give you an in-depth understanding of the technology involved in an Ethernet network. One of the major goals of this book is to demystify the jargon of networks so that the reader gains a working familiarity with common networking terminology and acronyms. In addition, this books explains not only how to choose and configure network hardware but also provides practical information about the types of network devices and software needed to make it all work. Tips and direction on how to manage an Ethernet network are also provided. This book therefore goes beyond the hardware aspects of Ethernet to look at the entire network from bottom to top, along with enough technical detail to enable the reader to make intelligent choices about what types of transmission media are used and the way in which the various parts of the network are interconnected. - Explains how the Ethernet works, with emphasis on current technologies and emerging trends in gigabit and fast Ethernet, WiFi, routers, and security issues - Teaches how to design and select complementary components of Ethernet networks with a focus on home and small business applications - Discuses the various types of cables, software, and hardware involved in constructing, connecting, operating and monitoring Ethernet networks

Security in Fixed and Wireless Networks

Security in Fixed and Wireless Networks
Author: Guenter Schaefer
Publisher: John Wiley & Sons
Total Pages: 624
Release: 2016-08-05
Genre: Computers
ISBN: 1119040760
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Introduces aspects on security threats and their countermeasures in both fixed and wireless networks, advising on how countermeasures can provide secure communication infrastructures. Enables the reader to understand the risks of inappropriate network security, what mechanisms and protocols can be deployed to counter these risks, and how these mechanisms and protocols work.