Автор: Yinyan Zhang; Shuai Li; Xuefeng Zhou Название: Deep Reinforcement Learning with Guaranteed Performance ISBN: 3030333833 ISBN-13(EAN): 9783030333836 Издательство: Springer Рейтинг: Цена: 18167.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book discusses methods and algorithms for the near-optimal adaptive control of nonlinear systems, including the corresponding theoretical analysis and simulative examples, and presents two innovative methods for the redundancy resolution of redundant manipulators with consideration of parameter uncertainty and periodic disturbances.It also reports on a series of systematic investigations on a near-optimal adaptive control method based on the Taylor expansion, neural networks, estimator design approaches, and the idea of sliding mode control, focusing on the tracking control problem of nonlinear systems under different scenarios. The book culminates with a presentation of two new redundancy resolution methods; one addresses adaptive kinematic control of redundant manipulators, and the other centers on the effect of periodic input disturbance on redundancy resolution.Each self-contained chapter is clearly written, making the book accessible to graduate students as well as academic and industrial researchers in the fields of adaptive and optimal control, robotics, and dynamic neural networks.
Автор: Nishchal K. Verma; Al Salour Название: Intelligent Condition Based Monitoring ISBN: 981150511X ISBN-13(EAN): 9789811505119 Издательство: Springer Рейтинг: Цена: 23757.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book discusses condition based monitoring of rotating machines using intelligent adaptive systems. The adaptive fault diagnostics systems presented can be used in multiple time and safety critical applications in domains such as aerospace, automotive, deep earth and deep water exploration, and energy.
Автор: Jain, Sarika Название: Understanding Semantics-Based Decision Support ISBN: 0367443139 ISBN-13(EAN): 9780367443139 Издательство: Taylor&Francis Рейтинг: Цена: 12707.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book is an attempt to establish in the readers the importance of creating interoperable data stores and writing rules for handling this data. It also covers extracts from a few project dissertations and a research funded project that the author had supervised.
Описание: Therefore, to address these issues, the book proposes control strategies that retain the simplicity of PID in terms of ease of tuning and structure, while improving on the performance of the closed-loop system with regard to stochastic network delays and mismatches.
Описание: CLIP 2020.- Optimal Targeting Visualizations for Surgical Navigation of Iliosacral Screws.- Prediction of Type II Diabetes Onset with Computed Tomography and Electronic Medical Records.- A Radiomics-based Machine Learning Approach to Assess Collateral Circulation in Stroke on Non-contrast Computed Tomography.- Image-based Subthalamic Nucleus Segmentation for Deep Brain Surgery With Electrophysiology Aided Refinement.- 3D Slicer Craniomaxillofacial Modules Support Patient-specific Decision-making for Personalized Healthcare in Dental Research.- Learning Representations of Endoscopic Videos to Detect Tool Presence Without Supervision.- Single-shot Deep Volumetric Regression for Mobile Medical Augmented Reality.- A Baseline Approach for AutoImplant: the MICCAI 2020 Cranial Implant Design Challenge.- Adversarial Prediction of Radiotherapy Treatment Machine Parameters.- ML-CDS 2020.- Soft Tissue Sarcoma Co-Segmentation in Combined MRI and PET/CT Data.- Towards Automated Diagnosis with Attentive Multi-Modal Learning Using Electronic Health Records and Chest X-rays.- LUCAS: LUng CAncer Screening with Multimodal Biomarkers.- Automatic Breast Lesion Classification by Joint Neural Analysis of Mammography and Ultrasound.
Описание: A series of problems are solved with new approaches of design, analysis and synthesis of fuzzy systems, including stabilization control and stability analysis, dynamic output feedback control, fault detection filter design, and reduced-order model approximation.
Автор: Marina V. Sokolova; Antonio Fern?ndez Caballero Название: Decision Making in Complex Systems ISBN: 364244444X ISBN-13(EAN): 9783642444449 Издательство: Springer Рейтинг: Цена: 15672.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: The study of complex systems involves researchers in diverse fields, with some systems such as epidemiology possessing an emergency priority. This volume collates existing methods for creating decision-support systems and places them in a more coherent system.
Автор: Gloria Phillips-Wren; Nikhil Ichalkaranje Название: Intelligent Decision Making: An AI-Based Approach ISBN: 3642095534 ISBN-13(EAN): 9783642095535 Издательство: Springer Рейтинг: Цена: 26120.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Intelligent Decision Support Systems have the potential to transform human decision making by combining research in artificial intelligence, information technology, and systems engineering.
Описание: A typical prediction is based on observing similar situations in the past, knowing the outcomes of these past situations, and expecting that the future outcome of the current situation will be similar to these past observed outcomes.
Описание: This book discusses computer-supported medical diagnosis with a particular focus on ovarian tumor diagnosis – since ovarian cancer is difficult to diagnose and has high mortality rates, especially in Central and Eastern Europe. It presents the theoretical foundations (both medical and mathematical) of the intelligent OvaExpert system, which supports decision-making in tumor diagnosis. OvaExpert was created primarily to help gynecologists predict the malignancy of ovarian tumors by applying the existing diagnostic models and using modern methods of computational intelligence that accommodate imprecise and imperfect medical data, both of which are common features of everyday medical practice. The book presents novel methods based on interval-valued fuzzy sets and the theory of their cardinalities.
Автор: Ke Zhang; Bin Jiang; Peng Shi; Vincent Cocquempot Название: Observer-Based Fault Estimation Techniques ISBN: 3319884387 ISBN-13(EAN): 9783319884387 Издательство: Springer Рейтинг: Цена: 18167.00 р. Наличие на складе: Нет в наличии.
Описание: This book investigates observer-fault estimation techniques in detail, while also highlighting recent research and findings regarding fault estimation. Many practical control systems are subject to possible malfunctions, which may cause significant performance loss or even system instability. To improve the reliability, performance and safety of dynamical systems, fault diagnosis techniques are now receiving considerable attention, both in research and applications, and have been the subject of intensive investigations. Fault detection – the essential first step in fault diagnosis – is a binary decision-making process used to determine whether or not a fault has occurred. In turn, fault isolation is used to identify the location of the faulty component, while fault estimation is used to identify the size of the fault online. Compared with the problems involved in fault detection and isolation, fault estimation is considerably more challenging.
Описание: The research presented in this book shows how combining deep neural networks with a special class of fuzzy logical rules and multi-criteria decision tools can make deep neural networks more interpretable - and even, in many cases, more efficient.
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