Search - Artificial Intelligence

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[Other] yichuansuanfa--lilunyingyongyuruanjianshixian DL : 0: 遗传算法是一种借鉴生物界自然选择和进化机制发展起来的高度并行、随机、自适应搜索算法。由于其具有健壮性，特别适合于处理传统搜索算法解决不好的复杂的和非线性问题。以遗传算法为核心的进化算法已与模糊系统理论、人工神经网络等一起成为计算智能研究中的热点，受到许多学科的共同关注。本书全面系统地介绍了遗传算法的基本理论，重点介绍了遗传算法的经典应用和国内外的新-Genetic Algorithm is a kind of drawing on biological mechanisms of natural selection and evolutionary development of highly parallel, randomized, adaptive search algorithm. Due to its robustness, particularly suited to deal with traditional search algorithms are not properly solved complex and nonlinear problems. To genetic algorithms as the core of the evolutionary algorithm with fuzzy system theory, artificial neural networks, along with computational intelligence research hotspot by many subjects of common concern. This book comprehensively and systematically introduce the genetic algorithm
Date : Size : 5.94mb User : 涂满园
[Other] AdaptiveStepsizeEASIAlgorithmBas DL : 0: 粒子群优化算法是一类基于群智能的随机优化算法。因受到人工生命的研究结果启发， &’((’)* 和 +,’-./-0 1 ，!2 于 334 年提出了粒子群优化算法，并已广泛应用于函数优化，神经网络训练，模式分类、模糊系统控制以及其他的应用领域。-PSO is a kind of swarm intelligence-based stochastic optimization algorithms. Inspired by the study results due to artificial life, & ' ((' )* and+, ' -./-0 1 ,! 2 334 made in PSO, and has been widely used in function optimization, neural network training, pattern classification, fuzzy systems control and other applications.
Date : Size : 866kb User : kobe
[Other] AdvancedMethodsAndToolsforECGDataAnalysis DL : 0: 介绍心电图（ECG）的数据分析原理、方法和程序(This practical book is the first one-stop resource to offer a thorough, up-to-date treatment of the techniques and methods used in ECG data analysis, from fundamental principles to the latest tools in the field. The book places emphasis on the selection, modeling, classification, and interpretation of data based on advanced signal processing and artificial intelligence techniques.)
Date : Size : 5.04mb User : woodballhead
[Other] 机器人基础 DL : 0: 本书介绍了机器人的概况和基本机构，讨论了机器人运动学和动力学问题，以及传感技术与感觉信息的处理，同时论述了机器人人工智能的相关问题。(This book introduces the general situation and the basic mechanism of the robot, discusses the kinematics and dynamics of the robot, and the sensing technology and sensory information processing, and discusses the related issues of robot artificial intelligence.)
Date : Size : 6.69mb User : 三月M
[Books] 深度学习(最全的中文版)_2017年新书 DL : 0: 这本书对各类读者都有一定用处的，但我们是基于两个主要目标受众而写的。其中一个目标受众是学习机器学习的大学生（本科或研究生），包括那些已经开始职业生涯的深度学习和人工智能研究者(This book is useful to all types of readers, but we are based on two major target audiences. One target audience is the undergraduate (graduate or graduate) who studies machine learning, including those who have started their careers in depth learning and artificial intelligence)
Date : Size : 26.02mb User : 狼之射手
[Other] bimpb DL : 0: MIT Artificial Intelligence Laboratory identification of the target source, Achieve canonical correlation analysis, The IMC - PID is using the internal model control principle for PID parameters is calculated.
Date : Size : 8kb User : feijenhou
[Books] Python_jcjcxd(jb51.net) DL : 0: 帮助初学者入门python，进而打开人工智能的开发的大门。(Help beginners entry python, and then open the door to the development of artificial intelligence.)
Date : Size : 29.74mb User : lancer9527
[VC/MFC] mjuaa DL : 0: Ensure accurate communication is learning a good helper, Including principal component analysis, factor analysis, Bayesian analysis, MIT Artificial Intelligence Laboratory identification of the target source.
Date : Size : 147kb User : bengyanglui
[Books] PacketTracer6 DL : 0: Artificial Intelligence A Modern Approach 3e Solutions
Date : Size : 56.71mb User : lin17
[VC/MFC] 新建文件夹 DL : 0: 人工智能课程设计，里面包含了n皇后几种人工智能方法，还有罗马利亚问题的解决(Course design of artificial intelligence)
Date : Size : 2.13mb User : fanguo...
[Books] AIS-PSO DL : 0: Particle Swarm Optimization (PSO) is a newly-emerging heuristic global search algorithm based on swarm intelligence and it searches the global optimal point in the complex search space through the competition and collaboration of the particles; however, PSO is easy to get trapped in local extremum, to have premature convergence or stagnation. In order to help PSO strike a balance between individual diversity and swarm convergence, this paper proposes an artificial immune PSO based on clonal selection. It integrates the advantages of artificial immunity and PSO and introduces the idea of immunity in PSO, namely to add immune operator in PSO so as to make PSO a new algorithm with the function of immunity.
Date : Size : 245kb User : Dallaki
[Books] Python3程序开发指南(第二版) DL : 0: python3程序开发指南，适合对python有兴趣的入门级别学习书籍。目前python在人工智能和机器深度学习方面应用很广泛。(The python3 program development guide is suitable for the entry - level learning books of interest to python. At present, Python is widely used in artificial intelligence and machine depth learning.)
Date : Size : 26.02mb User : babyld
[Other] 第198期（20171028）：ITI：人工智能政策准则 DL : 0: 关于人工智能的政策；让初学者不迷茫，找到重点(Policy on artificial intelligence; let beginners not be confused and find the key)
Date : Size : 285kb User : 安琪是个男孩
[Books] Python深度学习 DL : 0: 本书由Keras之父、现任Google A工智能研究员的弗朗索瓦?肖莱（Frangois Chollet）执笔，详尽介绍了用Python和Keras进行深度学习的探索实践，涉及计算机视觉、自然语言处理、生成式模型等应用。书中包含30多个代码示例，步骤讲解详细透彻。由于本书立足于人工智能的可达性和大众化，读者无须具备机器学习相关背景知识即可展开阅读。在学习完本书后，读者将具备搭建自己的深度学习环境、建立图像识别模型、生成图像和文字等能力(This book is written by Frangois Chollet, the father of keras and the current researcher of Google a intelligence. It introduces in detail the exploration and practice of deep learning with Python and keras, involving computer vision, natural language processing, generative model and other applications. The book contains more than 30 code examples, and the steps are detailed and thorough. Because this book is based on the accessibility and popularization of artificial intelligence, readers can read it without having the background knowledge of machine learning. After learning this book, readers will have the ability to build their own deep learning environment, establish image recognition model, and generate images and characters)
Date : Size : 2.41mb User : jliop
[Other] Deep_Learning_for_Radar DL : 0: Deep Learning for Radar and Communications Automatic Target Recognition presents a comprehensive illustration of modern artificial intelligence/machine learning (AI/ML) technology for radio frequency (RF) data exploitation. While numerous textbooks focus on AI/ML technology for non-RF data such as video images, audio speech, and spoken text, there is no such book for data in the RF spectrum. Hence, there is a need for an RF machine learning (ML) book for the research community that captures state-of-the-art AI/ML and deep learning (DL) algorithms and future challenges. Our goals with this book are to provide the practitioner with (i) an overview of the important ML/DL techniques, (ii) an exposition of the technical challenges associated with developing ML methods for RF applications, and (iii) implementation of ML techniques on synthetic aperture radar (SAR) imagery and communication signals classification.
Date : 2023-03-23 Size : 7.47mb User : sadovski
[Other] Understanding deep learning DL : 0: Artificial intelligence (AI) is concerned with building systems that simulate intelligent behavior. It encompasses a wide range of approaches, including those based on logic, search, and probabilistic reasoning. Machine learning is a subset of AI that learns to make decisions by fitting mathematical models to observed data. This area has seen explosive growth and is now (incorrectly) almost synonymous with the term AI. A deep neural network is one type of machine learning model, and when this model is fitted to data, this is referred to as deep learning. At the time of writing, deep networks are the most powerful and practical machine learning models and are often encountered in day-to-day life. It is commonplace to translate text from another language using a natural language processing algorithm, to search the internet for images of a particular object using a computer vision system, or to converse with a digital assistant via a speech recognition interface. All of these applications are powered by deep learning. As the title suggests, this book aims to help a reader new to this field understand the principles behind deep learning. The book is neither terribly theoretical (there are no proofs) nor extremely practical (there is almost no code). The goal is to explain the underlying ideas; after consuming this volume, the reader will be able to apply deep learning to novel situations where there is no existing recipe for success. Machine learning methods can coarsely be divided into three areas: supervised, unsupervised, and reinforcement learning. At the time of writing, the cutting-edge methods in all three areas rely on deep learning (figure 1.1). This introductory chapter describes these three areas at a high level, and this taxonomy is also loosely reflected in the book’s organization.
Date : 2023-07-03 Size : 11.11mb User : ihaveap1

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