الصفحة 14
الصفحة 14
Applied soft computing technologies : The challenge of complexity
This volume presents the proceedings of the 9th Online World Conference on Soft Computing in Industrial Applications (WSC9), September 20th - October 08th, 2004, held on the World Wide Web. It contains plenary lectures, original papers and tutorials presented during the conference. The book brings together outstanding research and developments in the field of soft computing (evolutionary computation, fuzzy logic, neural networks, and their fusion) and its applications in science and technology.
Applied Mathematics for Restructured Electric Power Systems : Optimization, Control, and Computational Intellige
Discusses the use of applied mathematics to solve challenging power system problems. This book covers such areas as: control, optimization, and computational intelligence. It follows a three-part format: a description of an important power system problem or problems; the practice and/or particular research approaches; and, research directions.
Applied Deep Learning with TensorFlow 2 : Learn to Implement Advanced Deep Learning Techniques with Python
Focuses on the fundamental concepts and at the same time on practical aspects of implementing neural networks and deep learning for your research projects. This book is designed so that you can focus on the parts you are interested in. You will explore topics as regularization, optimizers, optimization, metric analysis, and hyper-parameter tuning. In addition, you will learn the fundamentals ideas behind autoencoders and generative adversarial networks. All the code presented in the book will be available in the form of Jupyter notebooks which would allow you to try out all examples and extend them in interesting ways. A companion online book is available with the complete code for all examples discussed in the book and additional material more related to TensorFlow and Keras. All the code will be available in Jupyter notebook format and can be opened directly in Google Colab (no need to install anything locally) or downloaded on your own machine and tested locally. You will: Understand the fundamental concepts of how neural networks work / Learn the fundamental ideas behind autoencoders and generative adversarial networks / Be able to try all the examples with complete code examples that you can expand for your own projects / Have available a complete online companion book with examples and tutorials.
Applications of computational intelligence
Computational intelligence (CI) is the theory, design, application, and development of biologically and linguistically motivated computational paradigms. Traditionally, the three main pillars of CI have been neural networks, fuzzy systems, and evolutionary computation. However, in time, many nature-inspired computing paradigms have evolved. Thus, CI is an evolving field, and, at present, in addition to the three main constituents, it encompasses computing paradigms such as ambient intelligence, artificial life, cultural learning, artificial endocrine networks, social reasoning, and artificial hormone networks. CI plays a major role in developing successful intelligent systems, including games and cognitive developmental systems.
Application of power electronics converters in smart grids and renewable energy systems
Focuses on the applications of Power Electronics Converters in smart grids and renewable energy systems. The topics covered include methods to CO2 emission control, schemes for electric vehicle charging, reliable renewable energy forecasting methods, and various power electronics converters. The converters include the quasi neutral point clamped inverter, MPPT algorithms, the bidirectional DC-DC converter, and the push–pull converter with a fuzzy logic controller.
Analysis and Design of Intelligent Systems Using Soft Computing Techniques
This book comprises a selection of papers from IFSA 2007 on new methods for analysis and design of hybrid intelligent systems using soft computing techniques. Soft Computing (SC) consists of several computing paradigms, including fuzzy logic, neural networks, and genetic algorithms, which can be used to produce powerful hybrid intelligent systems for solving problems in pattern recognition, time series prediction, intelligent control, robotics and automation. Hybrid intelligent systems that combine several SC techniques are needed due to the complexity and high dimensionality of real-world problems. Hybrid intelligent systems can have different architectures, which have an impact on the efficiency and accuracy of these systems, for this reason it is very important to optimize architecture design. The architectures can combine, in different ways, neural networks, fuzzy logic and genetic algorithms, to achieve the ultimate goal of pattern recognition, time series prediction, intelligent control, or other application areas.
An Intuitive Exploration of Artificial Intelligence : Theory and Applications of Deep Learning
This book develops a conceptual understanding of Artificial Intelligence (AI), Deep Learning and Machine Learning in the truest sense of the word. It is an earnest endeavor to unravel what is happening at the algorithmic level, to grasp how applications are being built and to show the long adventurous road in the future.
Algorithms for a New World : When Big Data and Mathematical Models Meet
Algorithms, artificial neural networks, and machine learning help us discover the opportunities and pitfalls of a world governed by mathematics and artificial intelligence.
AI in drug discovery
Constitutes the refereed proceedings of the First international workshop on ai in Drug Discovery, AIDD 2024, held as a part of the 33rd International Conference on Artificial Neural Networks, ICANN 2024, in Lugano, Switzerland, on September 19, 2024. These papers focus on various aspects of the rapidly evolving field of Artificial Intelligence (AI)-driven drug discovery in chemistry, including Big Data and advanced Machine Learning, eXplainable AI (XAI), Chemoinformatics, Use of deep learning to predict molecular properties, Modeling and prediction of chemical reaction data and Generative models.
AI based Robot Safe Learning and Control
This book mainly focuses on the safe control of robot manipulators. The control schemes are mainly developed based on dynamic neural network, which is an important theoretical branch of deep reinforcement learning.
AI and UX : Why artificial intelligence needs user experience
Great effort has been put forth to continuously make AI “smarter.” But, will smarter always equal more successful AI? It is not just about getting a product to market, but about getting the product into a user’s hands in a form that will be embraced. This demands examining the product from the perspective of the user. Authors Gavin Lew and Robert Schumacher have written AI and UX to examine just how product managers and designers can best strike this balance. From exploring the history of the parallel journeys of AI and UX, to investigating past product examples and failures, to practical expert knowledge on how to best execute a positive user experience, AI and UX examines all angles of how AI can best be developed within a UX framework.
AI and law : How automation is changing the law
Provides insights into how AI is changing legal practice, government processes, and individuals’ access to those processes, encouraging each of us to consider how technological advances are changing the legal system. Particularly, and distinct from current debates on how to regulate AI, this books focuses on how the progressive merger between computational methods and legal rules changes the very structure and application of the law itself.
AI 2020 : Advances in artificial intelligence ; 33rd Australasian Joint Conference, AI 2020, Canberra, ACT, Australia, November 29–30, 2020, Proceedings
Constitutes the proceedings of the 33rd Australasian Joint Conference on Artificial Intelligence, AI 2020, held in Canberra, ACT, Australia, in November 2020.* The 36 full papers presented in this volume were carefully reviewed and selected from 57 submissions. The paper were organized in topical sections named: applications; evolutionary computation; fairness and ethics; games and swarms; and machine learning.
AI 2007: Advances in artificial intelligence ; 20th Australian Joint Conference on Artificial Intelligence, Gold Coast, Australia, December 2-6, 2007, Proceedings
The book is organized in topical sections on machine learning, neural networks, evolutionary computing, constraint satisfaction, satisfiability, automated reasoning, knowledge discovery, robotics, social intelligence, ontologies and semanti.
AI 2006 : Advances in artificial intelligence ; 19th Australian Joint Conference on Artificial Intelligence, Hobart, Australia, December 4-8, 2006, Proceedings
This volume contains the proceedings of the 19th Australian Joint Conference on Artificial Intelligence (AI 2006) held at Hobart, Australia. AI 2006 received a record number of submissions, a total of 689 submissions from 35 countries. The papers in this volume give an indication of recent advances in artificial int- ligence. The topics covered include Machine Learning, Robotics, AI Applications, Planning, Agents, Data Mining and Knowledge Discovery, Cognition and User Interface, Vision and Image Processing, Information Retrieval and Search, AI in the Web, Knowledge Representation, Knowledge-Based Systems, and Neural Networks.
AI 2005 : Advances in artificial intelligence ; 18th Australian joint conference on artificial intelligence, Sydney, Australia, December 5-9, 2005, proceedings
The 18th Australian Joint Conference on Artificial Intelligence (AI 2005) was held at the University of Technology, Sydney (UTS), Sydney, Australia from 5 to 9 December 2005. AI 2005 attracted a historical record number of submissions, a total of 535 papers. This volume of the proceedings contains the abstracts of three keynote speeches and all the full and short papers. The full papers were categorized into three broad sections, namely: AI foundations and technologies, computational intelligence, and AI in specialized domains. AI 2005 also hosted several tutorials and workshops, providing an interacting mode for specialists and scholars from Australia and other countries.
Advances of Computational Intelligence in Industrial Systems
Advances of Computational Intelligence in Industrial Systems reports the exploration of CI frontiers with an emphasis on a broad spectrum of real-world applications. Section I – Theory and Foundation presents some of the latest developments in CI.
Advances in Structural Engineering - Optimization : Emerging Trends in Structural Optimization
An up-to-date source for computation applications of optimization, prediction via artificial intelligence methods, and evaluation of metaheuristic algorithm with different structural applications. As the current interest of researcher, metaheuristic algorithms are a high interest topic area since advance and non-optimized problems via mathematical methods are challenged by the development of advance and modified algorithms. The artificial intelligence (AI) area is also important in predicting optimum results by skipping long iterative optimization processes. The machine learning used in generation of AI models also needs optimum results of metaheuristic-based approaches.
Advances in statistical methods for the health sciences : Applications to cancer and AIDS studies, genome sequence analysis, and survival analysis
This volume, an outgrowth of an "International Conference on Statistical Methods in Health Sciences," covers a wide range of topics pertaining to new statistical methods and novel applications in the health sciences.
Advances in optical fiber communications
Given the increasing importance of a globally interconnected world, driven by modern digital services and the need for fast and reliable access to digital resources, communication networks are one of the key infrastructures in today’s society. In this scenario, fiber optics and optical devices play a leading role, as they allow for unprecedented growth in our capacity to cope with the ever-increasing traffic demand. Optical transmission solutions range from high-speed networks based on coherent detection and advanced modulation formats for long-haul-level communications, to networks still relying on traditional intensity modulation and direct detection receivers for short-reach communications, down to intra-data center scenarios.
