Forest models

Xem 1-20 trên 100 kết quả Forest models
  • Remote sensing has been defined as the detection, recognition, or evaluation of objects by means of distant sensing or recording devices. In recent decades, remote sensing technology has emerged to support data collection and analysis methods of potential interest and importance in forest management. Historically, digital remote sensing developed quickly from the technology of aerial photography and photointerpretation science. In forestry, information extracted visually from aerial photographs is well-understood, well-used, and integrated with field surveys.

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  •  Ebook 136 Best Model Essays - Các bài luận mẫu hay nhất: Phần 1 giới thiệu tới các bạn những nội dung về Life in the city, Living in a multiracial community, A visit to a famous city, Modern inventions, Adventure in a forest, An unusual opportunity I had,The value of libraries, A horrible sight, Discuss the part that money plays in our lives, Science and its effects, The rights and duties of a citizen. 

     

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  • This book provides an interdisciplinary view of how to prepare the ecological and socio-economic systems to the reality of climate change. Scientifically sound tools are needed to predict its effects on regional, rather than global, scales, as it is the level at which socio-economic plans are designed and natural ecosystem reacts. The first section of this book describes a series of methods and models to downscale the global predictions of climate change, estimate its effects on biophysical systems and monitor the changes as they occur....

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  • Analyzing future distributed real-time systems, automotive and avionic systems, is requiring compositional hard real-time analysis techniques. Well known established techniques as SymTA/S and the real-time calculus are candidates solving the mentioned problem. However both techniques use quite simple event models. SymTA/S is based on discrete events the real-time calculus on continuous functions. Such simple models has been choosen because of the computational complexity of the considered mathematical operations required for real-time analysis.

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  • Tree-to-string systems (and their forestbased extensions) have gained steady popularity thanks to their simplicity and efficiency, but there is a major limitation: they are unable to guarantee the grammaticality of the output, which is explicitly modeled in string-to-tree systems via targetside syntax. We thus propose to combine the advantages of both, and present a novel constituency-to-dependency translation model, which uses constituency forests on the source side to direct the translation, and dependency trees on the target side (as a language model) to ensure grammaticality. ...

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  • We present cdec, an open source framework for decoding, aligning with, and training a number of statistical machine translation models, including word-based models, phrase-based models, and models based on synchronous context-free grammars. Using a single unified internal representation for translation forests, the decoder strictly separates model-specific translation logic from general rescoring, pruning, and inference algorithms.

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  • This paper proposes a forest-based tree sequence to string translation model for syntaxbased statistical machine translation, which automatically learns tree sequence to string translation rules from word-aligned sourceside-parsed bilingual texts. The proposed model leverages on the strengths of both tree sequence-based and forest-based translation models.

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  • Among syntax-based translation models, the tree-based approach, which takes as input a parse tree of the source sentence, is a promising direction being faster and simpler than its string-based counterpart. However, current tree-based systems suffer from a major drawback: they only use the 1-best parse to direct the translation, which potentially introduces translation mistakes due to parsing errors. We propose a forest-based approach that translates a packed forest of exponentially many parses, which encodes many more alternatives than standard n-best lists. ...

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  • Efficient decoding has been a fundamental problem in machine translation, especially with an integrated language model which is essential for achieving good translation quality. We develop faster approaches for this problem based on k-best parsing algorithms and demonstrate their effectiveness on both phrase-based and syntax-based MT systems. In both cases, our methods achieve significant speed improvements, often by more than a factor of ten, over the conventional beam-search method at the same levels of search error and translation accuracy. ...

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  • The Context-Free backbone of some natural language analyzers produces all possible CF parses as some kind of shared forest, from which a single tree is to be chosen by a disambiguation process that may be based on the finer features of the language. We study the structure of these forests with respect to optimality of sharing, and in relation with the parsing schema used to produce them. In addition to a theoretical and experimental framework for studying these issues, the main results presented are: sophistication in chart parsing schemata (e.g.

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  • We study parsing of tree adjoining grammars with particular emphasis on the use of shared forests to represent all the parse trees deriving a well-formed string. We show that there are two distinct ways of representing the parse forest one of which involves the use of linear indexed grammars and the other the use of context-free grammars. The work presented in this paper is intended to give a general framework for studying tag parsing.

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  • Syntax-based translation models that operate on the output of a source-language parser have been shown to perform better if allowed to choose from a set of possible parses. In this paper, we investigate whether this is because it allows the translation stage to overcome parser errors or to override the syntactic structure itself. We find that it is primarily the latter, but that under the right conditions, the translation stage does correct parser errors, improving parsing accuracy on the Chinese Treebank. ...

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  • We describe Akamon, an open source toolkit for tree and forest-based statistical machine translation (Liu et al., 2006; Mi et al., 2008; Mi and Huang, 2008). Akamon implements all of the algorithms required for tree/forestto-string decoding using tree-to-string translation rules: multiple-thread forest-based decoding, n-gram language model integration, beam- and cube-pruning, k-best hypotheses extraction, and minimum error rate training.

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  • Current tree-to-tree models suffer from parsing errors as they usually use only 1best parses for rule extraction and decoding. We instead propose a forest-based tree-to-tree model that uses packed forests. The model is based on a probabilistic synchronous tree substitution grammar (STSG), which can be learned from aligned forest pairs automatically. The decoder finds ways of decomposing trees in the source forest into elementary trees using the source projection of STSG while building target forest in parallel.

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  • The minimum Bayes risk (MBR) decoding objective improves BLEU scores for machine translation output relative to the standard Viterbi objective of maximizing model score. However, MBR targeting BLEU is prohibitively slow to optimize over k-best lists for large k. In this paper, we introduce and analyze an alternative to MBR that is equally effective at improving performance, yet is asymptotically faster — running 80 times faster than MBR in experiments with 1000-best lists.

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  • In this paper, we propose forest-to-string rules to enhance the expressive power of tree-to-string translation models. A forestto-string rule is capable of capturing nonsyntactic phrase pairs by describing the correspondence between multiple parse trees and one string. To integrate these rules into tree-to-string translation models, auxiliary rules are introduced to provide a generalization level.

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  • Tham khảo sách 'rehabilitation of degraded forests to improve livelihoods', kỹ thuật - công nghệ, tự động hoá phục vụ nhu cầu học tập, nghiên cứu và làm việc hiệu quả

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  • The Ministry of Agriculture and Rural Development has entrusted the Vietnam Forestry Science Institute with research into and development of “Effective and sustainable planting of production forests in the Northern mountainous region”. This paper provides some initial results from surveys on the marketing of products from such forests in the Northern mountainous provinces.

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  • This report provides a summary of some of the existing knowledge and literature related to the production of woody biomass from bioenergy with a particular focus on the economic perspective. The most commonly discussed woody biomass feedstocks are described along with results of existing economic modeling studies related to the provision of biomass from short rotation woody crops, harvest residues, and hazardous fuel reduction efforts. Additionally, the existing social science literature is used to highlight some challenges to widespread production of biomass energy.

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  • Soil loss for erosion is a natural phenomenon in soil dynamics, influenced by climate, soil intrinsic properties, and morphology, that can both trigger and enhance the process. Anthropic activities, like inappropriate agricultural practices, deforestation, overgrazing, forest fires and construction activities, may exert a remarkable impact on erosion processes or, on the other hand, contribute to soil erosion mitigation through a sustainable management of natural resources.

    pdf200p camchuong_1 04-12-2012 28 8   Download

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