Hidden Link Prediction in Stochastic Social Networks, Babita Pandey, Aditya Khamparia
Автор: Shreve Название: Stochastic Calculus for Finance I ISBN: 0387401008 ISBN-13(EAN): 9780387401003 Издательство: Springer Рейтинг: Цена: 8384.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Developed for the professional Master`s program in Computational Finance at Carnegie Mellon, the leading financial engineering program in the U.S. Has been tested in the classroom and revised over a period of several yearsExercises conclude every chapter;
Автор: Kelly Название: Stochastic Networks ISBN: 1107035775 ISBN-13(EAN): 9781107035775 Издательство: Cambridge Academ Рейтинг: Цена: 10930.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Communication networks underpin our modern world, and provide fascinating and challenging examples of large-scale stochastic systems. This compact introduction to some of the stochastic models found useful in the study of communication networks is ideal for graduate students wishing to understand this important area of application.
Автор: Kelly Название: Stochastic Networks ISBN: 1107691702 ISBN-13(EAN): 9781107691704 Издательство: Cambridge Academ Рейтинг: Цена: 6019.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Communication networks underpin our modern world, and provide fascinating and challenging examples of large-scale stochastic systems. This compact introduction to some of the stochastic models found useful in the study of communication networks is ideal for graduate students wishing to understand this important area of application.
Автор: Jalal Kawash; Nitin Agarwal; Tansel ?zyer Название: Prediction and Inference from Social Networks and Social Media ISBN: 3319510487 ISBN-13(EAN): 9783319510484 Издательство: Springer Рейтинг: Цена: 16769.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book addresses the challenges of social network and social media analysis in terms of prediction and inference. These include generating realistic social network topologies, awareness of user activities, topic and trend generation, estimation of user attributes from their social content, and behavior detection.
Описание: Chapter two is dedicated to infinite horizon stochastic discrete optimal control models and Markov decision problems with average and expected total discounted optimization criteria, while Chapter three develops a special game-theoretical approach to Markov decision processes and stochastic discrete optimal control problems.
Автор: Paul Glasserman; Karl Sigman; David D. Yao Название: Stochastic Networks ISBN: 0387948287 ISBN-13(EAN): 9780387948287 Издательство: Springer Рейтинг: Цена: 14673.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: The topics of research in stochastic networks are the complementary subjects of stability and rare events. This volume aims to present a sample of research problems, methodologies, and results in these two burgeoning areas. It originated from a workshop held at Columbia University in 1995, organized by Columbia`s Center for Applied Probability.
Автор: Klaus Neumann Название: Stochastic Project Networks ISBN: 3540526641 ISBN-13(EAN): 9783540526643 Издательство: Springer Рейтинг: Цена: 10760.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book presents the state of the art of temporal analysis and cost minimization of projects, as well as project planning under limited resources where the projects are modelled by GERT networks. Basic concepts are summarized and the book is self-contained.
Автор: Duc T. Pham; Xing Liu Название: Neural Networks for Identification, Prediction and Control ISBN: 1447132467 ISBN-13(EAN): 9781447132462 Издательство: Springer Рейтинг: Цена: 6986.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: In recent years, there has been a growing interest in applying neural networks to dynamic systems identification (modelling), prediction and control. The neural network types considered in detail are the muhilayer perceptron (MLP), the Elman and Jordan networks and the Group-Method-of-Data-Handling (GMDH) network.
Автор: Cherry Bhargava Название: AI Techniques for Reliability Prediction for Electronic Components ISBN: 1799814645 ISBN-13(EAN): 9781799814641 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 30215.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: In the industry of manufacturing and design, one major constraint has been enhancing operating performance using less time. As technology continues to advance, manufacturers are looking for better methods in predicting the condition and residual lifetime of electronic devices in order to save repair costs and their reputation. Intelligent systems are a solution for predicting the reliability of these components; however, there is a lack of research on the advancements of this smart technology within the manufacturing industry.
AI Techniques for Reliability Prediction for Electronic Components provides emerging research exploring the theoretical and practical aspects of prediction methods using artificial intelligence and machine learning in the manufacturing field. Featuring coverage on a broad range of topics such as data collection, fault tolerance, and health prognostics, this book is ideally designed for reliability engineers, electronic engineers, researchers, scientists, students, and faculty members seeking current research on the advancement of reliability analysis using AI.
Описание: In the industry of manufacturing and design, one major constraint has been enhancing operating performance using less time. As technology continues to advance, manufacturers are looking for better methods in predicting the condition and residual lifetime of electronic devices in order to save repair costs and their reputation. Intelligent systems are a solution for predicting the reliability of these components; however, there is a lack of research on the advancements of this smart technology within the manufacturing industry. AI Techniques for Reliability Prediction for Electronic Components provides emerging research exploring the theoretical and practical aspects of prediction methods using artificial intelligence and machine learning in the manufacturing field. Featuring coverage on a broad range of topics such as data collection, fault tolerance, and health prognostics, this book is ideally designed for reliability engineers, electronic engineers, researchers, scientists, students, and faculty members seeking current research on the advancement of reliability analysis using AI.
Автор: Animesh Biswas, Arnab Kumar De Название: Multi-Objective Stochastic Programming in Fuzzy Environments ISBN: 1522592962 ISBN-13(EAN): 9781522592969 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 24116.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: It is frequently observed that most decision-making problems involve several objectives, and the aim of the decision makers is to find the best decision by fulfilling the aspiration levels of all the objectives. Multi-objective decision making is especially suitable for the design and planning steps and allows a decision maker to achieve the optimal or aspired goals by considering the various interactions of the given constraints. Multi-Objective Stochastic Programming in Fuzzy Environments discusses optimization problems with fuzzy random variables following several types of probability distributions and different types of fuzzy numbers with different defuzzification processes in probabilistic situations. The content within this publication examines such topics as waste management, agricultural systems, and fuzzy set theory. It is designed for academicians, researchers, and students.
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