This definitive textbook provides a solid introduction to discrete and continuous stochastic processes, tackling a complex field in a way that instills a deep understanding of the relevant mathematical principles, and develops an intuitive grasp of the way these principles can be applied to ...

《交通大数据理论与方法》 目录 背景 随着信息通讯技术的不断发展，各行各业都产生了海量的数据，与此同时，一门新的学科应运而生—— 数据挖掘。数据挖掘是从大量数据（包括文本数据）中挖掘出隐含的、先前未知的、对决策有潜在价值的信 息、知识和关联关系，并基于这些信息和相应规则建立可用于决策支持与优化分析的模型，提供可支持预测 性决策的方法和工具。此外，数据挖掘还可帮助企业和科研团体发现业务与学科中的新趋势，揭示已知的 事实，预测未知的结果，因此“数据挖掘”已成为其保持竞争力的必要手段。 在大数据发展的背景下，交通领域的各类大数据同样以惊人的速度产生，并被应用于各种各样的应用 场景。例如，基于手机信令数据分析城市人口分布及交通出行分布特征，从而为交通规划的进一步决策提 供量化依据；利用网约车数据分析城市路网流量，进而优化信号配时方案，提升交通控制方案的效率；利用 线圈、视频、浮动车等多源数据，实现

比较好的介绍kalman的书，Charles K.Chui，Guanrong Chen编写。第四版。

Introduction to stochastic calculus with applications.pdf Fima C.Klebaner

The book is organized in 11 chapters. Chapter 1 summarizes the historical evolution of harmonic oscillators and analysis methods. Chapters 2 to 5 deal with the most important building blocks. Following a discussion of the basic theory on semiconductor devices and large-signal parameters, the most modern devices are chosen as examples. A whole chapter is dedicated to the various types of resonators, an important subject for microstrip applications.

Cloud Computing for Machine Learning and Cognitive Applications A Machine Learning Approach Kai Hwang 17

Data-Driven Prediction for Industrial Processes and Their Applications (Information Fusion and Data Science) By 作者: Jun Zhao – Wei Wang – Chunyang Sheng ISBN-10 书号: 3319940503 ISBN-13 书号: 9783319940502 Edition 版本: 1st ed. 2018 Release Finelybook 出版日期: 2018-08-20 pages 页数: (443） Springer出版超清 This book presents modeling methods and algorithms for data-driven prediction and forecasting of practical industrial process by employing machine learning and statistics methodologies. Related case studies, especially on energy systems in the steel industry are also addressed and analyzed. The case studies in this volume are entirely rooted in both classical data-driven prediction problems and industrial practice requirements. Detailed figures and tables demonstrate the effectiveness and generalization of the methods addressed, and the classifications of the addressed prediction problems come from practical industrial demands, rather than from academic categories. As such, readers will learn the corresponding approaches for resolving their industrial technical problems. Although the contents of this book and its case studies come from the steel industry, these techniques can be also used for other process industries. This book appeals to students, researchers, and professionals within the machine learning and data analysis and mining communities.

有限元方法与应用，适合有一定基础的有限元朋友，国外流行的有限元教程。

Go Web Development Cookbook Build full-stack web applications with Go 英文azw3 本资源转载自网络，如有侵权，请联系上传者或csdn删除 查看此书详细信息请在美国亚马逊官网搜索此书

陆吾生教授关于优化理论、压缩感知课程的讲义来源!经典教材！