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الصفحة 15
الصفحة 15
Advances in artificial intelligence: models, optimization, and machine learning
Contains all the articles accepted and published in the Special Issue “Advances in Artificial Intelligence: Models, Optimization, and Machine Learning” of the MDPI Mathematics journal, which covers a wide range of topics connected to the theory and applications of artificial intelligence and its subfields. These topics include, among others, deep learning and classic machine learning algorithms, neural modelling, architectures and learning algorithms, biologically inspired optimization algorithms, algorithms for autonomous driving, probabilistic models and Bayesian reasoning, intelligent agents and multiagent systems.
Advanced Techniques in Knowledge Discovery and Data Mining
This explosion is a result of the growing use of electronic media. But what is data mining (DM)? A Web search using the Google search engine retrieves many (really many) definitions of data mining. We include here a few interesting ones. One of the simpler definitions is: “As the term suggests, data mining is the analysis of data to establish relationships and identify patterns” [1]. It focuses on identifying relations in data. Our next example is more elaborate: An information extraction activity whose goal is to discover hidden facts contained in databases. Using a combination of machine learning, statistical analysis, modeling techniques and database technology, data mining finds patterns and subtle relationships in data and infers rules that allow the prediction of future results. Typical applications include market segmentation, customer profiling, fraud detection, evaluation of retail promotions, and credit risk analysis .
Advanced technique and future perspective for next generation optical fiber communications
Optical fiber communication industry has gained unprecedented opportunities and achieved rapid progress in recent years. However, with the increase of data transmission volume and the enhancement of transmission demand, the optical communication field still needs to be upgraded to better meet the challenges in the future development. Artificial intelligence technology in optical communication and optical network is still in its infancy, but the existing achievements show great application potential. In the future, with the further development of artificial intelligence technology, AI algorithms combining channel characteristics and physical properties will shine in optical communication. This reprint introduces some recent advances in optical fiber communication and optical network, and provides alternative directions for the development of the next generation optical fiber communication technology.
Advanced SharePoint Services Solutions
Whether or not youve already benefited from Scot P. Hillier's first renowned Apress book, Microsoft SharePoint: Building Office 2003 Solutions, this fantastic follow-up is sure to please! This book will cover advanced techniques for programming web parts and SharePoint Services. Hillier also covers advanced integration techniques with related products like BizTalk Server 2004 and Content Server. Intended for advanced developers who already know all of the basic SharePoint Services, this book will steer you in solving ultra-specific, advanced problems.
Advanced sensors technologies applied in mobile robot
Contains contributions on the latest developments in mobile robotic systems and related research. Various topics with different ideas and applications from mobile robotics have found their place. New ideas are presented for mobile robots that specialise in cleaning floors, power lines and HVAC systems. We also find innovative approaches for navigation path planning using local minima-free potential fields, novel path primitives and/or their parameterisation for minimum-time planning, and various control approaches ranging from visual serving to model predictive and adaptive trajectory tracking, applied to wheeled robots, humanoid manipulators and flying robots. Localisation approaches using LiDAR, motion capture systems, fingerprint-based and biomechanical gait systems are also discussed.
Advanced mathematical science for mobility society
The automotive industry has made steady progress in technological innovations under the names of Connected Autonomous-Shared-Electric (CASE) and Mobility as a Service (MaaS). Needless to say, mathematics and informatics are important to support such innovations. As the concept of cars and movement itself is diversifying, they are indispensable for grasping the essence of the future mobility society and building the foundation for the next generation. This book contains three main contents. 1. Mathematical models of flow 2. Mathematical methodsfor huge data and network analysis 3. Algorithm for mobility society The first one discusses mathematical models of pedestrian and traffic flow, as they are important for preventing accidents and achieving efficient transportation.
Advanced machine learning and deep learning approaches for remote sensing
Provides research on how technologies such as artificial intelligence-based machine learning and deep learning can be applied to remote sensing. Through this, we can see the process of solving the existing problems of image and image signal processing for remote sensing. These techniques are computationally intensive and require the help of high-performance computing devices. With the development of devices such as GPUs, remote sensing technology, and aerial sensing technology, it is possible to monitor the Earth with high-resolution images and to obtain vast amounts of Earth observation data. The papers published in this reprint describe recent advances in big data processing and artificial intelligence-based technologies for remote sensing technology.
AdvancED Flex 3
Divided into three parts. The first part discusses the architectural and design aspects of Flex 3 application development. It explains the internals of a Flex 3 application and advocates a few best practices to fine-tune your application to ensure maximum performance. It includes tutorials on creating custom components, data binding, and creating AIR-powered desktop applications. The second part concentrates on effectively integrating Flex 3 with server- and client-side technologies. Techniques for integration with Java and PHP are covered in detail, and content covering interaction with client-side technologies is also included. After reading the chapter on JavaScript integration, you will be ready to create applications that can use Ajax and Flex 3 together. The third and final part of the book is a unique and eclectic mix of some advanced topics like mash-ups, collaborative applications, 3D rendering, highly interactive visualization, and audio and video streaming.
Advanced Decision Sciences Based on Deep Learning and Ensemble Learning Algorithms : A Practical Approach Using Python
Describes the deep learning models and ensemble approaches applied to decision-making problems. The authors have addressed the concepts of deep learning, convolutional neural networks, recurrent neural networks, and ensemble learning in a practical sense providing complete code and implementation for several real-world examples. The authors of this book teach the concepts of machine learning for undergraduate and graduate-level classes and have worked with Fortune 500 clients to formulate data analytics strategies and operationalise these strategies.
Advanced Data Warehouse Design : From Conventional to Spatial and Temporal Applications
This book serves as an introduction to the state of the art on data warehouse design, with many references to more detailed sources. Providing a clear and a concise presentation of the major concepts and results of data warehouse design, it can also be used as the basis of a graduate or advanced undergraduate course.
Advanced Algorithms and Data Structures
introduces a collection of algorithms for complex programming challenges in data analysis, machine learning, and graph computing. You’ll discover cutting-edge approaches to a variety of tricky scenarios. You’ll even learn to design your own data structures for projects that require a custom solution. What's inside Build on basic data structures you already know Profile your algorithms to speed up application Store and query strings efficiently Distribute clustering algorithms with MapReduce Solve logistics problems using graphs and optimization algorithms
Advance Concepts of Image Processing and Pattern Recognition : Effective Solution for Global Challenges
Explains the important concepts and principles of image processing to implement the algorithms and techniques to discover new problems and applications. It contains numerous fundamental and advanced image processing algorithms and pattern recognition techniques to illustrate the framework. It presents essential background theory, shape methods, texture about new methods, and techniques for image processing and pattern recognition. It maintains a good balance between a mathematical background and practical implementation. This book also contains the comparison table and images that are used to show the results of enhanced techniques. This book consists of novel concepts and hybrid methods for providing effective solutions for society. It also includes a detailed explanation of algorithms in various programming languages like MATLAB, Python, etc.
Adobe® Acrobat® and PDF for Architecture, Engineering, and Construction
Adobe® Acrobat® and PDF for Architecture, Engineering, and Construction is designed to appeal to the engineering mind. The book is a practical guide focusing on the applications of PDF in the solution of "engineering" problems which may arise in a number of disciplines from architecture to construction. Using real-world examples, the authors follow a project from design through build and long-term maintenance. As the sample project evolves, suitable Acrobat® tools and techniques are identified and brought into play at each stage, showing readers how to personalize the context and processes to meet their own project development and management needs.
Adaptive-robust control with limited knowledge on systems dynamics : An artificial input delay approach and beyond
investigates the role of artificial input delay in approximating unknown system dynamics, referred to as time-delayed control (TDC), and provides novel solutions to current design issues in TDC. Its central focus is on designing adaptive-switching gain-based robust control (ARC) for a class of Euler–Lagrange (EL) systems with minimal or no knowledge of the system dynamics parameters. The newly proposed TDC-based ARC tackles the commonly observed over- and under-estimation issues in switching gain. The consideration of EL systems lends a practical perspective on the proposed methods, and each chapter is supplemented by relevant experimental data
Adaptive Learning of Polynomial Networks : Genetic Programming, Backpropagation and Bayesian Methods
This book provides theoretical and practical knowledge for develop ment of algorithms that infer linear and nonlinear models. It offers a methodology for inductive learning of polynomial neural network mod els from data. The design of such tools contributes to better statistical data modelling when addressing tasks from various areas like system identification, chaotic time-series prediction, financial forecasting and data mining. The main claim is that the model identification process involves several equally important steps: finding the model structure, estimating the model weight parameters, and tuning these weights with respect to the adopted assumptions about the underlying data distrib ution. When the learning process is organized according to these steps, performed together one after the other or separately, one may expect to discover models that generalize well.
Adaptive Business Intelligence
In the modern information era, managers must recognize the competitive opportunities represented by decision-support tools. Adaptive business intelligence systems combine prediction and optimization techniques to assist decision makers in complex, rapidly changing environments. These systems address the fundamental questions: What is likely to happen in the future? And what is the best decision right now? Adaptive Business Intelligence includes elements of data mining, predictive modeling, forecasting, optimization, and adaptability.
Active Conceptual Modeling of Learning : Next Generation Learning-Base System Development
This volume contains a collection of the papers presented during the 1st International ACM-L Workshop, which was held on November 8, 2006 during the 25th International Conference on Conceptual Modeling, ER 2006, held November 6–9,2006, in Tucson, Arizona, plus several invited papers.These papers plus the invited papers represent the current thinking in conceptual modeling research, The active model can only be realized through technology integration (e.g., AI, software engineering, information technology,cognitive science, art and sciences, philosophy, etc.)
Accessible access 2003
In that book we tried very hard not to simply list everything that we knew about the product. Instead we tried to act as intelligent filters, presenting only the essential information that you need to get started. Every screen shot has been retaken and every section has been re-checked to ensure, not only that it still works, but also that it is actually still relevant. We have re-written parts where the product has changed and also added some. For example, there is a new section on Object Dependencies and a whole new chapter about Data Access Pages - helping you to put your Access database onto an intranet.
Accelerated SQL Server 2008
The expert tuition and approach to rapid learning in Accelerated SQL Server 2008, one of the first SQL Server 2008 books available, will enable SQL Server and other database professionals to make the leap to the 2008 release of Microsoft's flagship database management system quickly. Take full advantage of the features of SQL Server 2008, know what tools are available, and quickly realize the power and ease of use that SQL Server 2008 has to offer.
Abstraction, refinement and proof for probabilistic systems
Probabilistic techniques are increasingly being employed in computer programs and systems because they can increase efficiency in sequential algorithms, enable otherwise nonfunctional distribution applications, and allow quantification of risk and safety in general. This makes operational models of how they work, and logics for reasoning about them, extremely important. Abstraction, Refinement and Proof for Probabilistic Systems presents a rigorous approach to modeling and reasoning about computer systems that incorporate probability. Its foundations lie in traditional Boolean sequential-program logic—but its extension to numeric rather than merely true-or-false judgments takes it much further, into areas such as randomized algorithms, fault tolerance, and, in distributed systems, almost-certain symmetry breaking. The presentation begins with the familiar "assertional" style of program development and continues with increasing specialization: Part I treats probabilistic program logic, including many examples and case studies; Part II sets out the detailed semantics; and Part III applies the approach to advanced material on temporal calculi and two-player games.
