標(biāo)題: Titlebook: Artificial Intelligent Approaches in Petroleum Geosciences; Constantin Cranganu,Henri Luchian,Mihaela Elena Br Book 20151st edition Spring [打印本頁] 作者: 和善 時(shí)間: 2025-3-21 18:23
書目名稱Artificial Intelligent Approaches in Petroleum Geosciences影響因子(影響力)
書目名稱Artificial Intelligent Approaches in Petroleum Geosciences影響因子(影響力)學(xué)科排名
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書目名稱Artificial Intelligent Approaches in Petroleum Geosciences網(wǎng)絡(luò)公開度學(xué)科排名
書目名稱Artificial Intelligent Approaches in Petroleum Geosciences被引頻次
書目名稱Artificial Intelligent Approaches in Petroleum Geosciences被引頻次學(xué)科排名
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書目名稱Artificial Intelligent Approaches in Petroleum Geosciences年度引用學(xué)科排名
書目名稱Artificial Intelligent Approaches in Petroleum Geosciences讀者反饋
書目名稱Artificial Intelligent Approaches in Petroleum Geosciences讀者反饋學(xué)科排名
作者: alcoholism 時(shí)間: 2025-3-21 22:06
On Meta-heuristics in Optimization and Data Analysis. Application to Geosciences, 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.作者: chisel 時(shí)間: 2025-3-22 04:08 作者: FADE 時(shí)間: 2025-3-22 08:17
Application of Artificial Neural Networks in Geoscience and Petroleum Industry,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 作者: interlude 時(shí)間: 2025-3-22 09:26 作者: 偽造者 時(shí)間: 2025-3-22 15:19 作者: 灌溉 時(shí)間: 2025-3-22 17:11 作者: 要控制 時(shí)間: 2025-3-22 22:07
Improving the Accuracy of Active Learning Method via Noise Injection for Estimating Hydraulic Flow 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作者: DIS 時(shí)間: 2025-3-23 03:52 作者: 凈禮 時(shí)間: 2025-3-23 08:12 作者: 忙碌 時(shí)間: 2025-3-23 11:15
Das praktische Arbeiten mit der Feile,e samples to solve numerical and combinatorial problems are given. The fourth section is dedicated to the use of EC techniques in data analysis. Optimization of the hyper-parameters of conventional machine learning techniques is illustrated by a case study. The last section reviews applications of meta-heuristics in geosciences.作者: 雪崩 時(shí)間: 2025-3-23 15:37
On Meta-heuristics in Optimization and Data Analysis. Application to Geosciences,e samples to solve numerical and combinatorial problems are given. The fourth section is dedicated to the use of EC techniques in data analysis. Optimization of the hyper-parameters of conventional machine learning techniques is illustrated by a case study. The last section reviews applications of meta-heuristics in geosciences.作者: deceive 時(shí)間: 2025-3-23 20:00
Book 20151st editionnd petroleum industry. Written by experienced academics, this book offers state-of-the-art working examples and provides the reader with exposure to the latest developments in the field of intelligent methods applied to oil and gas research, exploration and production. It also analyzes the strengths作者: Sinus-Node 時(shí)間: 2025-3-23 22:57 作者: 屈尊 時(shí)間: 2025-3-24 02:53
Das praktische Arbeiten mit der Feile,, ANN structure), feed-forward ANN, backpropagation and learning (perceptrons and backpropagation, multilayer ANNs and backpropagation algorithm), data processing by ANN (training, over-fitting, testing, validation), ANN and statistical parameters, an applied example of ANN, and applications of ANN in geoscience and petroleum Engineering.作者: GUEER 時(shí)間: 2025-3-24 07:39
Blickrichtungen auf Potentiale des Dialogs,the relationship which may exist between the well log data and core permeability. This study overviews the different artificial intelligent methods in permeability prediction with advantage of each method. Finally, some suggestions and comments to choose the best method are introduced.作者: 到婚嫁年齡 時(shí)間: 2025-3-24 11:04 作者: 結(jié)合 時(shí)間: 2025-3-24 15:43 作者: myalgia 時(shí)間: 2025-3-24 20:51
Permeability Estimation in Petroleum Reservoir by Meta-heuristics: An Overview,the relationship which may exist between the well log data and core permeability. This study overviews the different artificial intelligent methods in permeability prediction with advantage of each method. Finally, some suggestions and comments to choose the best method are introduced.作者: Obscure 時(shí)間: 2025-3-25 02:16 作者: 舊病復(fù)發(fā) 時(shí)間: 2025-3-25 05:47
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.作者: 下船 時(shí)間: 2025-3-25 09:57
,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.作者: 騎師 時(shí)間: 2025-3-25 13:51
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作者: 半圓鑿 時(shí)間: 2025-3-25 18:26
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.作者: Frequency 時(shí)間: 2025-3-25 22:22 作者: 子女 時(shí)間: 2025-3-26 03:50
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 作者: 攤位 時(shí)間: 2025-3-26 06:40 作者: Truculent 時(shí)間: 2025-3-26 11:22 作者: 皮薩 時(shí)間: 2025-3-26 14:34
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作者: 出血 時(shí)間: 2025-3-26 19:24
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作者: Affectation 時(shí)間: 2025-3-26 22:25
Erscheinungsformen des Rassismus, genetic algorithms and simulated annealing methods offer robust and highly accurate solution to several problems in petroleum geosciences. According to experience, these methods can be used effectively in the solution of well-logging inverse problems. Traditional inversion methods are used to proce作者: 虛情假意 時(shí)間: 2025-3-27 01:10 作者: pulmonary-edema 時(shí)間: 2025-3-27 06:22 作者: CEDE 時(shí)間: 2025-3-27 11:52
http://image.papertrans.cn/b/image/162586.jpg作者: assent 時(shí)間: 2025-3-27 16:40
https://doi.org/10.1007/978-3-319-16531-8Artificial Neural Networks in Petroleum Geosciences; Genetic Algorithms in Petroleum Geosciences; Inte作者: Sinus-Rhythm 時(shí)間: 2025-3-27 19:59 作者: 排名真古怪 時(shí)間: 2025-3-28 00:34 作者: 束縛 時(shí)間: 2025-3-28 05:44 作者: Inveterate 時(shí)間: 2025-3-28 07:53 作者: Jacket 時(shí)間: 2025-3-28 12:32 作者: monogamy 時(shí)間: 2025-3-28 18:06 作者: heterodox 時(shí)間: 2025-3-28 22:15 作者: Focus-Words 時(shí)間: 2025-3-29 00:09 作者: PTCA635 時(shí)間: 2025-3-29 03:21 作者: Ccu106 時(shí)間: 2025-3-29 10:00
Schleifen von Korrigierten Zahnprofilen,The values obtained for these three quality-control parameters appear congruent, with the exception of MRE, regardless of the training set used (. vs. .). ALM performance was measured also by the time required to attain the desirable outcomes: five depth levels of investigation took a little more th作者: OTHER 時(shí)間: 2025-3-29 14:45
https://doi.org/10.1007/978-3-322-88378-0stimates the output by an interpolation. The heart of ALM is fuzzy measuring of the spread. In this paper, ALM is used to estimate missing logs in hydrocarbon reservoirs. The regression and normalized mean squared error (MSE) for estimating density log using ALM were equal to 0.9 and 0.042, respecti
