Search for dissertations about: "Forest data"
Showing result 1 - 5 of 423 swedish dissertations containing the words Forest data.
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1. Order in the random forest
Abstract : In many domains, repeated measurements are systematically collected to obtain the characteristics of objects or situations that evolve over time or other logical orderings. Although the classification of such data series shares many similarities with traditional multidimensional classification, inducing accurate machine learning models using traditional algorithms are typically infeasible since the order of the values must be considered. READ MORE
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2. Random Forest for Histogram Data : An application in data-driven prognostic models for heavy-duty trucks
Abstract : Data mining and machine learning algorithms are trained on large datasets to find useful hidden patterns. These patterns can help to gain new insights and make accurate predictions. Usually, the training data is structured in a tabular format, where the rows represent the training instances and the columns represent the features of these instances. READ MORE
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3. Constructing and contesting the legitimacy of private forest governance : The case of forest certification in Sweden
Abstract : In recent decades, political scientists have devoted substantial attention to the changing role of the state towards more inclusion of non-state actors in policymaking. This deliberative turn, or move towards governance, may signal inability to handle complex problems without cooperation with nonstate actors. READ MORE
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4. Rooting for forest resilience : Implications of climate and land-use change on the tropical rainforests
Abstract : Tropical rainforests in the Amazon and Congo River basins and their climate are mutually dependent. Evaporation from these forests help regulate the regional and global water cycle. Furthermore, these rainforests themselves depend on precipitation to sustain their structure and functions. READ MORE
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5. How can data science contribute to a greener world? : an exploration featuring machine learning and data mining for environmental facilities and energy end users
Abstract : Human society has taken many measures to address environmental issues. For example, deploying wastewater treatment plants (WWTPs) to alleviate water pollution and the shortage of usable water; using waste-to-energy (WtE) plants to recover energy from the waste and reduce its environmental impact. READ MORE