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"Balance of power Forecasting."
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Strategic vision : America and the crisis of global power
In 1991, the United States was the only global superpower. It seemed that the 21st century, like the 20th, would belong to America. Then came the stock market bubble, the costly foreign unilateralism of the younger Bush presidency, and the financial catastrophe of 2008. Meanwhile, China was rising and the Middle East was awakening politically. Today it is clear that America is vulnerable--to domestic and international decline and unregulated greed. Speaking from decades of experience, Brzezinski considers the implications of the changing distribution of global power, ponders why America's global appeal is waning, speculates on the likely geopolitical consequences if America declines by 2025 (will China assume America's central role in world affairs?), and describes a vision of a resurgent America: responsive to challenges, strategically deliberate, and historically enlightened in its global engagement with the new East.--Publisher description.
Book
Strategic Vision
One of the wise men of American foreign policy explains America's vital role in achieving global stability and provides a long-term strategic vision for America.
eBook
Intentions in Great Power Politics
Why the future of great power politics is likely to
resemble its dismal past Can great powers be confident
that their peers have benign intentions? States that trust each
other can live at peace; those that mistrust each other are doomed
to compete for arms and allies and may even go to war. Sebastian
Rosato explains that states routinely lack the kind of information
they need to be convinced that their rivals mean them no harm. Even
in cases that supposedly involved mutual trust-Germany and Russia
in the Bismarck era; Britain and the United States during the great
rapprochement; France and Germany, and Japan and the United States
in the early interwar period; and the Soviet Union and United
States at the end of the Cold War-the protagonists mistrusted each
other and struggled for advantage. Rosato argues that the
ramifications of his argument for U.S.-China relations are
profound: the future of great power politics is likely to resemble
its dismal past.
eBook
Global powers in the 21st century : strategies and relations
Experts analyze the changing perspectives and objectives of global powers China, Japan, Russia, India, and the European Union in a strategic landscape shaped by the Iraq War.
eBook
Global Demographic Change and Its Implications for Military Power
What is the impact of demographics on the prospective production of military power and the causes of war? This monograph analyzes this issue by projecting working-age populations through 2050; assessing the influence of demographics on manpower, national income and expenditures, and human capital; and examining how changes in these factors may affect the ability of states to carry out military missions.
eBook
The Planet in 2050
In 2050, the billions of people living on Earth have found a way to manage the planetary system effectively. Everyone has access to adequate food, shelter, and clean water. Human health is no longer considered outside of the health of the ecosystems in which people live. Ecological awareness is an integral part of education. People respond effectively to social and environmental hazards, and societies care for the most vulnerable amongst them. The economy, too, has shifted. Carbon dioxide management is under control, and energy efficiency is the norm. The remaining rainforests have been preserved. Coral reefs are recovering. Fish stocks are thriving. Is any of this really possible? How can our complex social and economic systems interact with a complex planetary system undergoing rapid change to create a future we all want?
This book is a contextualised collation of ideas articulated by the 50 participants of the Planet 2050 workshop held in Lund in October 2008, as part of The Planet in 2050, an interdisciplinary Fast Track Initiative of the International Geosphere-Biosphere Programme. Participants were selected from academia and the sustainability practice community to give a wide-ranging, multi-cultural, trans-disciplinary set of perspectives.
This collection explores four broad sectoral themes: energy and technologies; development, economies and culture; environment; and land use change. By doing so, this book emphasises the importance of a social dialogue on our collective future, and our responsibility to the Earth. It makes strong statements about what needs to happen to the global economy for a sustainable future and documents a new kind of scholarly discussion, engaging people from diverse knowledge communities in a spirit of exploration and reflexivity. The book provides a focus for dialogue and further study for postgraduates and researchers interested in global change as a multi-faceted, socio-environmental
eBook
Skill of a global forecasting system in seasonal ensemble streamflow prediction
In this study we assess the skill of seasonal streamflow forecasts with the global hydrological forecasting system Flood Early Warning System (FEWS)-World, which has been set up within the European Commission 7th Framework Programme Project Global Water Scarcity Information Service (GLOWASIS). FEWS-World incorporates the distributed global hydrological model PCR-GLOBWB (PCRaster Global Water Balance). We produce ensemble forecasts of monthly discharges for 20 large rivers of the world, with lead times of up to 6 months, forcing the system with bias-corrected seasonal meteorological forecast ensembles from the European Centre for Medium-range Weather Forecasts (ECMWF) and with probabilistic meteorological ensembles obtained following the ESP procedure. Here, the ESP ensembles, which contain no actual information on weather, serve as a benchmark to assess the additional skill that may be obtained using ECMWF seasonal forecasts. We use the Brier skill score (BSS) to quantify the skill of the system in forecasting high and low flows, defined as discharges higher than the 75th and lower than the 25th percentiles for a given month, respectively. We determine the theoretical skill by comparing the results against model simulations and the actual skill in comparison to discharge observations. We calculate the ratios of actual-to-theoretical skill in order to quantify the percentage of the potential skill that is achieved. The results suggest that the performance of ECMWF S3 forecasts is close to that of the ESP forecasts. While better meteorological forecasts could potentially lead to an improvement in hydrological forecasts, this cannot be achieved yet using the ECMWF S3 dataset.
Journal Article
Methods of Forecasting Electric Energy Consumption: A Literature Review
Balancing the production and consumption of electricity is an urgent task. Its implementation largely depends on the means and methods of planning electricity production. Forecasting is one of the planning tools since the availability of an accurate forecast is a mechanism for increasing the validity of management decisions. This study provides an overview of the methods used to predict electricity supply requirements to different objects. The methods have been reviewed analytically, taking into account the forecast classification according to the anticipation period. In this way, the methods used in operative, short-term, medium-term, and long-term forecasting have been considered. Both classical and modern forecasting methods have been identified when forecasting electric energy consumption. Classical forecasting methods are based on the theory of regression and statistical analysis (regression, autoregressive models); probabilistic forecasting methods and modern forecasting methods use classical and deep-machine-learning algorithms, rank analysis methodology, fuzzy set theory, singular spectral analysis, wavelet transformations, Gray models, etc. Due to the need to take into account the specifics of each subject area characterizing an energy facility to obtain reliable forecast results, power consumption modeling remains an urgent task despite a wide variety of other methods. The review was conducted with an assessment of the methods according to the following criteria: labor intensity, requirements for the initial data set, scope of application, accuracy of the forecasting method, the possibility of application for other forecasting horizons. The above classification of methods according to the anticipation period allows highlights the fact that when predicting power consumption for different time intervals, the same methods are often used. Therefore, it is worth emphasizing the importance of classifying the forecast over the forecasting horizon not to differentiate the methods used to predict electricity consumption for each period but to consider the specifics of each type of forecasting (operative, short-term, medium-term, long-term).
Journal Article
A multivariate ensemble learning method for medium-term energy forecasting
In the contemporary context, both production and consumption of energy, being concepts intertwined through a condition of synchronicity, are pivotal for the orderly functioning of society, with their management being a building block in maintaining regularity. Hence, the pursuit to develop reliable computational tools for modeling such serial and time-dependent phenomena becomes similarly crucial. This paper investigates the use of ensemble learners for medium-term forecasting of the Greek energy system load using additional information from injected energy production from various sources. Through an extensive experimental process, over 435 regression schemes and 64 different modifications of the feature inputs were tested over five different prediction time frames, creating comparative rankings regarding two case studies: one related to methods and the other to feature setups. Evaluations according to six widely used metrics indicate an aggregate but clear dominance of a specific efficient and low-cost ensemble layout. In particular, an ensemble method that incorporates the
orthogonal matching pursuit
together with the
Huber regressor
according to an averaged combinatorial scheme is proposed. Moreover, it is shown that the use of multivariate setups improves the derived predictions.
Journal Article