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Titlebook: Valuing Chaparral; Ecological, Socio-Ec Emma C.‘Underwood,Hugh D. Safford,Jon E. Keeley Book 2018 Springer International Publishing AG, par

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發(fā)表于 2025-3-25 05:34:05 | 只看該作者
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發(fā)表于 2025-3-25 07:44:13 | 只看該作者
Summary: The Past, Present, and Future of California Chaparral,sive and locally intensive, and the variegated landscape that Spanish explorers and missionaries encountered near the coast and at lower elevations was largely the product of indigenous management, with fire being the central management tool (see Chap. 4).
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發(fā)表于 2025-3-25 15:37:19 | 只看該作者
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發(fā)表于 2025-3-25 17:21:47 | 只看該作者
Philip W. Rundeling machine learning models such as SVM, Naive Bayes, Neural Network, and Random Forest to find the most effective method. The Random Forest combined with the FastText method was highly evaluated, achieving a success rate of 82% when measured against essential evaluation criteria of accuracy, precis
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發(fā)表于 2025-3-25 23:40:55 | 只看該作者
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發(fā)表于 2025-3-26 02:03:44 | 只看該作者
Megan K. Jenningsorks. Spectral clustering, hierarchical clustering, Markov models, modularity maximization methods, etc have shown promising results in context to application domains under consideration. In this paper, the authors propose a neural network based method to identify the communities in large-scale netw
27#
發(fā)表于 2025-3-26 06:11:02 | 只看該作者
M. Kat Anderson,Jon E. Keeley the studied networks are anonymized, where no user profile or sensitive data is available, and (3) the need of scalable algorithms for user linkage task in large-scale social nateworks, and (4) users in social network are interrelated. To resolve these challenges, a noval user linkage framework bas
28#
發(fā)表于 2025-3-26 11:59:43 | 只看該作者
Char Millerounded identification of most vulnerable lines. The goals are achieved by first constructing a novel connection between cascading failures and natural languages, and then adapting the powerful transformer model in NLP to learn from cascading failure data. Our trained transformer models have good acc
29#
發(fā)表于 2025-3-26 14:30:05 | 只看該作者
30#
發(fā)表于 2025-3-26 18:41:40 | 只看該作者
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