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Titlebook: Artificial Intelligent Approaches in Petroleum Geosciences; Constantin Cranganu,Henri Luchian,Mihaela Elena Br Book 20151st edition Spring

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楼主: 和善
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https://doi.org/10.1007/978-3-663-10048-5gorithms (naive Bayes classifiers, decision trees, support vector machines, and neural networks) and the modalities to evaluate their performance. Examples of specific applications of algorithms are given using System R.
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,Intelligent Data Analysis Techniques—Machine Learning and Data Mining,gorithms (naive Bayes classifiers, decision trees, support vector machines, and neural networks) and the modalities to evaluate their performance. Examples of specific applications of algorithms are given using System R.
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https://doi.org/10.1007/978-3-663-10048-5ing several types of learning (supervised, unsupervised, semi-supervised, active and reinforcement learning) we examine several classes of learning algorithms (naive Bayes classifiers, decision trees, support vector machines, and neural networks) and the modalities to evaluate their performance. Exa
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Das praktische Arbeiten mit der Feile, briefly walks through problem solving, touching upon notions such as ., .-., ., ., and the .., and also giving very short introductions into several most popular meta-heuristics. The next two sections are dedicated to evolutionary algorithms and swarm intelligence (SI), two of the main areas of EC.
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Das praktische Arbeiten mit der Feile,m solving to geoscience and petroleum industry problems particularly in case of limited availability or lack of input data. ANN application has become widespread in engineering including geoscience and petroleum engineering because it has shown to be able to produce reasonable outputs for inputs it
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https://doi.org/10.1007/978-3-322-88378-0 petroleum industry. Pore-fluid pressures as well as estimating permeability, porosity, or fluid saturation are some of the important example of such activities. Due to various problems occurring during the measurements, e.g., incomplete logging, inappropriate data storage, or measurement errors, mi
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Minderheiten als soziale Konstruktion,e small sample size problem. Because of small sample size problem, modeling techniques commonly fail to accurately extract the true relationships between the inputs and the outputs used for reservoir properties prediction or modeling. In this paper, small sample size problem is addressed for modelin
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