TracerLPM（版本2 Beta） 一个Excel工作簿程序，用于根据环境示踪数据评估地下水年龄分布 此文件夹包含用于32位和64位TracerLPM（版本2 Beta）的安装软件包（.msi）。 安装程序包必须与用户计算机上安装的Microsoft Office版本匹配。 默认情况下，即使大多数操作系统是64位，也通常会安装32位版本的Office。 如果Office版本是64位，则仅使用TracerLPM的64位安装程序包。 子文件夹包含用于开发TracerLPM的所有代码和工作簿。 Workbook文件夹包含Excel工作簿的最新版本，并使用Visual Basic for Applications（VBA）编写。 文件夹LPM_FunctionsXLL包含用C ++编写的Visual Studio（2015）解决方案代码，用于计算示踪剂浓度。 文件夹Optimization

Concepts and Applications of Finite Element Analysis

《Global Positioning System_Theory and Applications》这本书相信研究过GPS的都了解吧，号称GPS中的经典，蓝宝书。 1. 英文PDF，可取词。 2. 分为上下册，第一册800来页；第二册660多页。 3. 有书签，很清晰

《Global Positioning System_Theory and Applications》这本书相信研究过GPS的都了解吧，号称GPS中的经典，蓝宝书。 1. 英文PDF，可取词。 2. 分为上下册，第一册800来页；第二册660多页。 3. 有书签，很清晰

《》Designing Data Intensive Applications》epub版本

After the fundamental volume and the advanced technique volume, this volume focuses on R applications in the quantitative investment area. Quantitative investment has been hot for some years, and there are more and more startups working on it, combined with many other internet communities and business models. R is widely used in this area, and can be a very powerful tool. The author introduces R applications with cases from his own startup, covering topics like portfolio optimization and risk management. There are six chapters in this book, categorized into three parts: Financial Market and Financial Theory, Data Processing and High Performance Computing of R, and Financial Strategy Practice. Every chapter is a holistic knowledge system. Section One is Financial Market and Financial Theory (including Chapters 1 and 2), which starts with an understanding of finance to establish a basic idea of financial quantification. Chapter 1, Financial Market Overview, is the opening chapter of this book, which mainly introduces the ideas and methods of how to use R language to make quantitative investments. Chapter 2, Financial Theory, mainly introduces the classic theoretical models of finance and the R implementation methods. In Section Two, Data Processing and High Performance Computing of R (including Chapters 3 and 4), essential tools of R language for data processing and their usage are introduced in detail. Chapter 3, Data Processing of R, cored with the data processing technology of R, introduces the methods of processing different types of data with R language. In Chapter 4, High Performance Computing of R, three external technologies are introduced to help the performance of R language meet the production environment requirements. Section Three, Financial Strategy Practice (including Chapters 5 and 6), combines the R language technology and the financial market rules to solve the practical problems in financial quantification field. In Chapter 5, Bonds and Repurchase, readers can learn the market and the methods of low-risk investment. In Chapter 6, Quantitative Investment Strategy Cases, the investment research methods from theory to practice are introduced in whole. Since knowledge of different areas is comprehensively applied in this book, it is suggested that you read all the chapters in order. Some of the technical implementations mentioned in this book use the information from the other two books of the series, R for Programmers: Mastering the Tools and R2 for Programmers: Advanced Techniques, so it is recommended that you read those two as well.

迭代应用的最佳检查点策略 这项工作提供了一种最佳的检查点策略，可以保护迭代应用程序免受故障停止错误的影响。 我们考虑一个非常通用的框架，其中应用程序通过执行连续的迭代来重复相同的执行模式，并且每个迭代都由多个任务组成。 这些任务具有不同的执行长度和不同的检查点成本。 天真的策略和Young / Daly策略都不理想。 我们的主要贡献是证明最佳检查点策略是全局周期性的，并设计一种动态编程算法来计算最佳检查点模式。 这种模式很可能会检查许多不同的任务，并且涉及许多不同的迭代。 通过在综合和实际应用场景中进行的仿真，我们表明，最佳策略明显优于单纯策略和Young / Daly策略。 代码 gen_faults.m生成服从指数分布的故障main_GCR.m为GCR应用程序进行仿真main_gopi.m为神经科学应用程序进行仿真main_random.m对合成应用程序进行仿真Simulation_e

一本机器学习入门的好书，同时伴有大量R语言的例子，是用R语言敲开机器学习大门的不二书选！Springer出版的经典书籍，很接地气。

The theory and practice of time series analysis have developed rapidly since the appear- ance in 1970 of the seminal work of George E. P. Box and Gwilym M. Jenkins, Time Series Analysis: Forecasting and Control, now available in its third edition (1994) with co-author Gregory C. Reinsel. Many books on time series have appeared since then, but some of them give too little practical application, while others give too little theoretical background. This book attempts to present both application, and theory at a level acces- sible to a wide variety of students and practitioners. Our approach is to mix application and theory throughout the book as they are naturally needed.

qt5_applications-5.15.2.2.2-py3-none-win_amd64.whl