Finally, it uses a simple computer program, GAMS, to develop and solve models. This book is targeted towards university lecturers and students in economic modeling and sustainable development, but is also of particular interest to researchers at sustainable development research institutes and policy makers at international sustainable development policy institutions such the World Bank, UNDP, and UNEP.
Global warming and economic development : a holistic approach to international policy co-operation and co-ordination by Anantha K Duraiappah Book 13 editions published in in English and held by WorldCat member libraries worldwide Three questions need to be addressed when discussing the global warming issue. First, is a reduction in carbon dioxide emissions necessary? Second, if the answer is yes, what is the optimal level of CO2 emissions?
Computers play a crucial role in preserving the Earth | NSF - National Science Foundation
Third, who should be held responsible for reducing CO2 emissions? This book addresses these three questions by formulating a global economic growth model with links between the economic system and the climate system. With this formulation, feedback effects of climate change on the economic systems are captured endogenously within the model structure.
The book will be required reading for those working in the climate change field, as well as for computational economic model builders. Ecology, economy and society : essays in honour of Kanchan Chopra 6 editions published in in English and held by WorldCat member libraries worldwide This book deals with not just complex linkages, interactions and exchanges that form the relationship between the economic activities, human society and the ecosystems, but also the influences and impacts that each causes on the other.
In recent times, this ecology-economy-society interface has received unprecedented attention within the broader environment-development discourse.
The notion of sustainable development — development that meets the needs of the present without compromising the ability of future generations to meet their needs — was introduced in Our Common Future, the seminal report of the United Nations World Commission on Environment and Development, published in In this talk I will provide an overview of computational sustainability, with examples ranging from wildlife conservation and biodiversity, to poverty mitigation, to material discovery for fuel cell technology.
I will highlight overarching computational challenges at the intersection of constraint reasoning and inference, optimization, machine learning, and dynamical systems.
Recently, Gomes has become immersed in the establishment of computational sustainability, a new interdisciplinary field that aims to develop computational methods to help balance environmental, economic, and societal needs to support a sustainable future. With the imminent arrival of the exascale era, strong multidisciplinary collaborations between these diverse scientific groups are critical for the successful development of earth sciences HPC applications. The workshop facilitates communication between earth scientists, applied mathematicians, computational and computer scientists and presents a unique opportunity to exchange advanced knowledge, computational methods and science discoveries.
Work focusing emerging data and computational technologies that benefit the broader geoscience community is especially welcome. Advanced modeling and simulations on natural disaster prevention and mitigation. Parallel and distributed algorithms and programming strategies focused on issues such as performance, scalability, portability, data locality, power efficiency and reliability.
Duraiappah, Anantha K.
Software engineering and code optimizations for parallel systems with multi-core processors, GPU accelerators or Xeon Phi. Methodologies and tools designed for extreme-scale computing with emphasis on integration, interoperability and hardware-software co-design. Contact: Maciej Paszynski, paszynsk agh. Description: The aim of this workshop is to integrate results of different domains of computer science, computational science and mathematics.
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We invite papers oriented toward simulations, either hard simulations by means of finite element or finite difference methods, or soft simulations by means of evolutionary computations, particle swarm optimization and other. The workshop is most interested in simulations performed by using agent-oriented systems or by utilizing adaptive algorithms, but simulations performed by other kind of systems are also welcome.
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Agent-oriented system seems to be the attractive tool useful for numerous domains of applications. Adaptive algorithms allow significant decrease of the computational cost by utilizing computational resources on most important aspect of the problem. To give — rather flexible — guidance in the subject, the following, more detailed, topics are suggested. These of theoretical brand, like: multi-agent systems in high-performance computing, efficient adaptive algorithms for big problems, low computational cost adaptive solvers fast solvers for isogeometric finite element method, agent-oriented approach to adaptive algorithms, model reduction techniques for large problems, mathematical modeling and asymptotic analysis of large problems, finite element or finite difference methods for three dimensional or non-stationary problems, mathematical modeling and asymptotic analysis, stabilization of finite element method simulations.
And those with stress on application sphere: agents based algorithms dealing with big application of adaptive algorithms in large simulation, simulation and large multi-agent systems, applications of isogeometric finite element method, application of adaptive algorithms in three dimensional finite element and finite difference simulations, application of multi-agent systems in computational modeling, multi-agent systems in integration of different approaches.
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Contact: Stephane Louise, stephane. Description: This workshop aims at showing new way to tackle the performance out of distributed, parallel, and potentially heterogeneous systems by using a proper alchemy of any software and hardware ingredients including compilation technics and meta-programing, hardware support, specialized runtimes, specific accelerators, FPGA, etc.
Contact: Kourosh Modarresi, kouroshm alumni. Description: With the availability of large amount of data, the main challenge of our time is to get insightful information from the data. Therefore, artificial intelligence and machine learning are two main paths in getting the insights from the data we are dealing with. A major difficulty is that many of the old methods that have been developed for analyzing data during the last decades cannot be applied on modern data.
One distinct solution, to overcome this difficulty, is the application of matrix computation and factorization methods such as SVD singular value decomposition , PCA principal component analysis , and NMF non- negative matrix factorization , without which the analysis of modern data is not possible. This workshop covers the application of matrix computational science techniques in dealing with Modern Data.
Contact: Mario Cannataro, cannataro unicz. Description: Emerging technologies in biomedicine and bioinformatics are generating an increasing amount of complex data.
In order to tackle the growing complexity associated with emerging and future life science challenges, bioinformatics and computational biology researchers need to explore, develop and apply novel computational concepts, methods, tools and systems. Description: Nowadays many practical decision task require to build models on the basis of data which included serious difficulties, as imbalanced class distributions, high number of classes, high-dimensional feature, small or extremely high number of learning examples, limited access to ground truth, data incompleteness, or data in motion, to enumerate only a few.
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Such characteristics may strongly deteriorate the final model performances. Therefore, the proposition of the new learning methods which can combat the mentioned above difficulties should be the focus of intense research. The main aim of this workshop is to discuss the problems of data difficulties, to identify new issues, and to shape future directions for research. Topics include but not limited to : Learning from imbalanced data learning from data streams, including concept drift management learning with limited ground truth access learning from high dimensional data learning with a high number of classes learning from massive data, including instance and prototype selection learning on the basis of limited data sets, including one-shot learning learning from incomplete data case studies and real-world applications.
Contact: Yong Shi, yshi ucas.
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It will include but not limited to modeling, numeric computation, soft computing, algorithmic and complexity issues in arbitrage, asset pricing, future and option pricing, risk management, credit assessment, interest rate determination, insurance, foreign exchange rate forecasting, online auction, cooperative game theory, general equilibrium, information pricing, network band witch pricing, rational expectation, repeated games, etc.
Related Computational Models in the Economics of Environment and Development
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