標(biāo)題: Titlebook: Design Optimization Under Uncertainty; Weifei Hu Textbook 2023 The Editor(s) (if applicable) and The Author(s), under exclusive license to [打印本頁] 作者: OAK 時(shí)間: 2025-3-21 19:28
書目名稱Design Optimization Under Uncertainty影響因子(影響力)
書目名稱Design Optimization Under Uncertainty影響因子(影響力)學(xué)科排名
書目名稱Design Optimization Under Uncertainty網(wǎng)絡(luò)公開度
書目名稱Design Optimization Under Uncertainty網(wǎng)絡(luò)公開度學(xué)科排名
書目名稱Design Optimization Under Uncertainty被引頻次
書目名稱Design Optimization Under Uncertainty被引頻次學(xué)科排名
書目名稱Design Optimization Under Uncertainty年度引用
書目名稱Design Optimization Under Uncertainty年度引用學(xué)科排名
書目名稱Design Optimization Under Uncertainty讀者反饋
書目名稱Design Optimization Under Uncertainty讀者反饋學(xué)科排名
作者: terazosin 時(shí)間: 2025-3-21 22:40 作者: MELD 時(shí)間: 2025-3-22 02:04
Basic Concepts of Probability and Reliability,pectation, variance, and covariance are also provided. In addition, typical probability distributions are illustrated, and basic reliability concepts are briefly discussed. This chapter’s goal is to help readers conceptualize the fundamentals of probability and reliability that account for uncertain作者: 饑荒 時(shí)間: 2025-3-22 07:59 作者: 媒介 時(shí)間: 2025-3-22 10:25
https://doi.org/10.1007/978-94-011-4395-0count for various uncertainties during design optimization. This chapter aims to explore different sources and categories of uncertainties in engineering design, along with the modeling techniques used to quantify and manage uncertainties. The chapter begins by introducing the fundamental concept of作者: 冒煙 時(shí)間: 2025-3-22 13:24
Pierre Journeau,Nicolas Moh-Ellocations, such as reliability analysis and design optimization, with lower computational costs. The construction of high-accuracy and low-cost surrogate models often involves adaptive sampling. In this chapter, four common methods for constructing surrogate models are introduced. Several evaluation m作者: 冒煙 時(shí)間: 2025-3-22 18:29 作者: reptile 時(shí)間: 2025-3-23 00:35 作者: mucous-membrane 時(shí)間: 2025-3-23 02:07
Solid Mechanics and Its Applicationsrformance and uncertain parameters, which makes it very challenging to conduct time-dependent reliability analysis instantly and accurately. This chapter introduces the concept of time-dependent reliability analysis, followed by current time-dependent reliability analysis methods that are divided in作者: 責(zé)問 時(shí)間: 2025-3-23 06:56
Basic concepts of analytical dynamicsntenance costs, and has attracted attention in recent years. This chapter offers the basic concept of RBDO, the details of RBDO formulation, and two categories of RBDO methods in an easy-to-follow way. The two categories of RBDO methods are the most probable point (MPP)-based RBDO method and the sam作者: 蚊帳 時(shí)間: 2025-3-23 12:28 作者: NOMAD 時(shí)間: 2025-3-23 14:34 作者: 織布機(jī) 時(shí)間: 2025-3-23 19:05 作者: 你敢命令 時(shí)間: 2025-3-23 23:17 作者: 使殘廢 時(shí)間: 2025-3-24 04:45 作者: 法律的瑕疵 時(shí)間: 2025-3-24 08:04
Weifei HuOffers both the fundamental and the state-of-the-art theories and methods of design optimization under uncertainty.Explains the in-depth theories of design optimization under uncertainty in a lucid wi作者: debunk 時(shí)間: 2025-3-24 12:36 作者: 惡名聲 時(shí)間: 2025-3-24 18:54
Constrained systems: preliminariesysis methods, including most probable point (MPP)-based methods and sampling methods. The MPP-based methods consist of the first-order reliability method (FORM) and the second-order reliability method (SORM). The sampling methods include the Monte Carlo simulation (MCS) method and the importance sampling method, as well as other related methods.作者: 青石板 時(shí)間: 2025-3-24 19:50 作者: Decongestant 時(shí)間: 2025-3-24 23:48
Textbook 2023nalytical reliability analysis, and the state-of-the-art approaches of design optimization under uncertainty (e.g., reliability-based design optimization and robust design optimization).?The topics include basic concepts of probability and distributions, uncertainty quantification using probabilisti作者: pulmonary-edema 時(shí)間: 2025-3-25 03:35 作者: Nausea 時(shí)間: 2025-3-25 11:23
Pierre Journeau,Nicolas Moh-Elloing process. In addition, this chapter discusses the weight decision strategies for assigning weights between the evaluation metrics of global exploration and local exploitation. Finally, a new adaptive sampling method for surrogate modeling is illustrated based on Voronoi tessellation and a dynamic weight decision strategy.作者: 逗留 時(shí)間: 2025-3-25 12:31
Solid Mechanics and Its Applications-based methods are particularly explained, including confidence-based adaptive extreme response surface method, equivalent stochastic process transformation method, instantaneous response surface method t-IRS, and surrogate-based time-dependent reliability analysis.作者: Lipoprotein 時(shí)間: 2025-3-25 18:43 作者: Foment 時(shí)間: 2025-3-25 21:13 作者: patella 時(shí)間: 2025-3-26 03:19 作者: 蒼白 時(shí)間: 2025-3-26 05:58 作者: Jogging 時(shí)間: 2025-3-26 11:39
Surrogate Modeling,ing process. In addition, this chapter discusses the weight decision strategies for assigning weights between the evaluation metrics of global exploration and local exploitation. Finally, a new adaptive sampling method for surrogate modeling is illustrated based on Voronoi tessellation and a dynamic weight decision strategy.作者: HAVOC 時(shí)間: 2025-3-26 15:47
Time-Dependent Reliability Analysis,-based methods are particularly explained, including confidence-based adaptive extreme response surface method, equivalent stochastic process transformation method, instantaneous response surface method t-IRS, and surrogate-based time-dependent reliability analysis.作者: Kernel 時(shí)間: 2025-3-26 20:29 作者: exclusice 時(shí)間: 2025-3-26 22:44
Physics-Informed Neural Networks for Design Optimization Under Uncertainty,amental theories of PINN, the basics of reliability analysis based on PINN, and the PINN-based design optimization under uncertainty. Some numerical cases are added to help readers understand these methodologies.作者: SPER 時(shí)間: 2025-3-27 02:12
Engineering Applications of Design Optimization Under Uncertainty,n three areas including energy management, logistics scheduling, and closed-loop supply chain. In addition, challenges and future work of RBDO and RDO research are provided at the end of this chapter.作者: 訓(xùn)誡 時(shí)間: 2025-3-27 07:11 作者: crockery 時(shí)間: 2025-3-27 10:20
Pierre Journeau,Fabrizio Annocarot multiple validation sites. Finally, a model validation method based on limited experimental and simulation data is briefly introduced to cope with the lack of data due to expensive computational and experimental cost.作者: 容易做 時(shí)間: 2025-3-27 14:07
Model Verification & Validation,t multiple validation sites. Finally, a model validation method based on limited experimental and simulation data is briefly introduced to cope with the lack of data due to expensive computational and experimental cost.作者: 大方不好 時(shí)間: 2025-3-27 18:56
Time-Independent Reliability Analysis,ysis methods, including most probable point (MPP)-based methods and sampling methods. The MPP-based methods consist of the first-order reliability method (FORM) and the second-order reliability method (SORM). The sampling methods include the Monte Carlo simulation (MCS) method and the importance sampling method, as well as other related methods.作者: ORBIT 時(shí)間: 2025-3-28 00:20 作者: Substance 時(shí)間: 2025-3-28 05:40
Textbook 2023c methods, classical reliability analysis methods, time-variant reliability analysis methods, fundamentals of deterministic design optimization, reliability-based design optimization, robust design optimization, other methods of design optimization under uncertainty, and engineering applications of design optimization under uncertainty..作者: 魅力 時(shí)間: 2025-3-28 07:18
Basic Concepts of Probability and Reliability,y factor,” which often results in a waste of material. This kind of simplified treatment lacks detailed statistical analysis nor seriously examines the randomness of an uncertain event. A probability is the likelihood of an uncertain event occurring. To accurately evaluate uncertain events during th作者: motor-unit 時(shí)間: 2025-3-28 14:03
Uncertainty Modeling,count for various uncertainties during design optimization. This chapter aims to explore different sources and categories of uncertainties in engineering design, along with the modeling techniques used to quantify and manage uncertainties. The chapter begins by introducing the fundamental concept of作者: 不規(guī)則的跳動 時(shí)間: 2025-3-28 15:48 作者: Enrage 時(shí)間: 2025-3-28 20:51 作者: 搜集 時(shí)間: 2025-3-29 01:28 作者: Organonitrile 時(shí)間: 2025-3-29 05:54
