银行家算法实验（包括系统安全性检验） 文档附录附有代码。

实验代码加分析，东北大学软件学院实验报告模板，精确解释加注释。

回归分析与实验设计 design and analysis of experiments

The Design and Analysis of Computer Experiments (Springer Series in Statistics) By 作者: Thomas J. Santner – Brian J. Williams – William I. Notz ISBN-10 书号: 149398845X ISBN-13 书号: 9781493988457 Edition 版本: 2nd ed. 2018 出版日期: 2019-01-09 pages 页数: (436 ) $119.99 This book describes methods for designing and analyzing experiments that are conducted using a computer code, a computer experiment, and, when possible, a physical experiment. Computer experiments continue to increase in popularity as surrogates for and adjuncts to physical experiments. Since the publication of the first edition, there have been many methodological advances and software developments to implement these new methodologies. The computer experiments literature has emphasized the construction of algorithms for various data analysis tasks (design construction, prediction, sensitivity analysis, calibration among others), and the development of web-based repositories of designs for immediate application. While it is written at a level that is accessible to readers with Masters-level training in Statistics, the book is written in sufficient detail to be useful for practitioners and researchers. New to this revised and expanded edition: An expanded presentation of basic material on computer experiments and Gaussian processes with additional simulations and examples A new comparison of plug-in prediction methodologies for real-valued simulator output An enlarged discussion of space-filling designs including Latin Hypercube designs (LHDs), near-orthogonal designs, and nonrectangular regions A chapter length description of process-based designs for optimization, to improve good overall fit, quantile estimation, and Pareto optimization A new chapter describing graphical and numerical sensitivity analysis tools Substantial new material on calibration-based prediction and inference for calibration parameters Lists of software that can be used to fit models discussed in the book to aid practitioners

不可多得的，全面的讲解各种概率分布的手册。主要用于科研实验人员使用时查询

数据结构Experiment 5 Europe by Rail（4 hours）实验的实验提交报告和RailSystem.cpp代码

Experiment 2 Europe by Rail RailSystem.cpp 可运行

Noise and Vibration Analysis is a complete and practical guide that combines both signal processing and modal analysis theory with their practical application in noise and vibration analysis. It provides an invaluable, integrated guide for practicing engineers as well as a suitable introduction for students new to the topic of noise and vibration. Taking a practical learning approach, Brandt includes exercises that allow the content to be developed in an academic course framework or as supplementary material for private and further study.

Statistics for Experimenters, Design, Innovation, and Discovery, Second Edition

最大流/最小割算法的简介，理解常用最大流最小割概念的文献，值得学习。 minimum cut/maximum flow algorithms on graphs emerged as an increasingly useful tool for exact or approximate energy minimization in low-level vision. The combinatorial optimization literature provides many min-cut/max-flow algorithms with different polynomial time complexity. Their practical efficiency, however, has to date been studied mainly outside the scope of computer vision. The goal of this paper is to provide an experimental comparison of the efficiency of min-cut/max flow algorithms for applications in vision. We compare the running times of several standard algorithms, as well as a new algorithm that we have recently developed. The algorithms we study include both Goldberg-Tarjan style “push-relabel” methods and algorithms based on Ford- Fulkerson style “augmenting paths.” We benchmark these algorithms on a number of typical graphs in the contexts of image restoration, stereo, and segmentation. In many cases, our new algorithm works several times faster than any of the other methods, making near real-time performance possible. An implementation of our max-flow/min-cut algorithm is available upon request for research purposes.