Download or read book Synthesis and Performance Analysis of Multilayer Neural Network Architectures written by W. Schiffmann and published by . This book was released on 1992 with total page 39 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book GeoComputational Modelling written by Manfred M. Fischer and published by Springer Science & Business Media. This book was released on 2013-03-09 with total page 286 pages. Available in PDF, EPUB and Kindle. Book excerpt: Geocomputation may be viewed as the application of a computational science paradigm to study a wide range of problems in geographical systems contexts. This volume presents a clear, comprehensive and thoroughly state-of-the-art overview of current research, written by leading figures in the field. It provides important insights into this new and rapidly developing field and attempts to establish the principles, and to develop techniques for solving real world problems in a wide array of application domains with a catalyst to greater understanding of what geocomputation is and what it entails. The broad coverage makes it invaluable reading for resarchers and professionals in geography, environmental and economic sciences as well as for graduate students of spatial science and computer science.
Download or read book Advances in Neural Networks written by Fuchun Sun and published by Springer Science & Business Media. This book was released on 2008-09-08 with total page 939 pages. Available in PDF, EPUB and Kindle. Book excerpt: (Bayreuth University, Germany), Jennie Si (Arizona State University, USA), and Hang Li (MicrosoftResearchAsia, China). Besides the regularsessions andpanels, ISNN 2008 also featured four special sessions focusing on some emerging topics.
Download or read book Advances in the Evolutionary Synthesis of Intelligent Agents written by Mukesh Patel and published by MIT Press. This book was released on 2001 with total page 510 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book explores a central issue in artificial intelligence, cognitive science, and artificial life: how to design information structures and processes that create and adapt intelligent agents through evolution and learning. Among the first uses of the computer was the development of programs to model perception, reasoning, learning, and evolution. Further developments resulted in computers and programs that exhibit aspects of intelligent behavior. The field of artificial intelligence is based on the premise that thought processes can be computationally modeled. Computational molecular biology brought a similar approach to the study of living systems. In both cases, hypotheses concerning the structure, function, and evolution of cognitive systems (natural as well as synthetic) take the form of computer programs that store, organize, manipulate, and use information. Systems whose information processing structures are fully programmed are difficult to design for all but the simplest applications. Real-world environments call for systems that are able to modify their behavior by changing their information processing structures. Cognitive and information structures and processes, embodied in living systems, display many effective designs for biological intelligent agents. They are also a source of ideas for designing artificial intelligent agents. This book explores a central issue in artificial intelligence, cognitive science, and artificial life: how to design information structures and processes that create and adapt intelligent agents through evolution and learning. The book is organized around four topics: the power of evolution to determine effective solutions to complex tasks, mechanisms to make evolutionary design scalable, the use of evolutionary search in conjunction with local learning algorithms, and the extension of evolutionary search in novel directions.
Download or read book Connectionist Models of Neurons Learning Processes and Artificial Intelligence written by Jose Mira and published by Springer Science & Business Media. This book was released on 2001-06-05 with total page 862 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes, together with its companion, LNCS 2085, the refereed proceedings of the 6th International Work-Conference on Artificial and Natural Neural Networks, IWANN 2001, held in Granada, Spain, in June 2001. The 200 revised papers presented were carefully reviewed and selected for inclusion in the proceedings. The papers are organized in sections on foundations of connectionism, biophysical models of neurons, structural and functional models of neurons, learning and other plasticity phenomena, complex systems dynamics, artificial intelligence and congnitive processes, methodology for nets design, nets simulation and implementation, bio-inspired systems and engineering, and other applications in a variety of fields.
Download or read book Intelligent Systems written by Robert J. Schalkoff and published by Jones & Bartlett Learning. This book was released on 2011-08-24 with total page 787 pages. Available in PDF, EPUB and Kindle. Book excerpt: Artificial Intelligence has changed significantly in recent years and many new resources and approaches are now available to explore and implement this important technology. Intelligent Systems: Principles, Paradigms, and Pragmatics takes a modern, 21st-century approach to the concepts of Artificial Intelligence and includes the latest developments, developmental tools, programming, and approaches related to AI. The author is careful to make the important distinction between theory and practice, and focuses on a broad core of technologies, providing students with an accessible and comprehensive introduction to key AI topics.
Download or read book Computational Life Sciences written by Michael R. Berthold and published by Springer. This book was released on 2005-09-28 with total page 287 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Encyclopedia of Computer Science and Technology written by Allen Kent and published by CRC Press. This book was released on 1995-07-26 with total page 424 pages. Available in PDF, EPUB and Kindle. Book excerpt: Case-Based Reasoning to User Interface Software Tools
Download or read book Multi Objective Machine Learning written by Yaochu Jin and published by Springer Science & Business Media. This book was released on 2007-06-10 with total page 657 pages. Available in PDF, EPUB and Kindle. Book excerpt: Recently, increasing interest has been shown in applying the concept of Pareto-optimality to machine learning, particularly inspired by the successful developments in evolutionary multi-objective optimization. It has been shown that the multi-objective approach to machine learning is particularly successful to improve the performance of the traditional single objective machine learning methods, to generate highly diverse multiple Pareto-optimal models for constructing ensembles models and, and to achieve a desired trade-off between accuracy and interpretability of neural networks or fuzzy systems. This monograph presents a selected collection of research work on multi-objective approach to machine learning, including multi-objective feature selection, multi-objective model selection in training multi-layer perceptrons, radial-basis-function networks, support vector machines, decision trees, and intelligent systems.
Download or read book Artificial Intelligence and Soft Computing ICAISC 2008 written by Leszek Rutkowski and published by Springer Science & Business Media. This book was released on 2008-06-16 with total page 1275 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 9th International Conference on Artificial Intelligence and Soft Computing, ICAISC 2008, held in Zakopane, Poland, in June 2008. The 116 revised contributed papers presented were carefully reviewed and selected from 320 submissions. The papers are organized in topical sections on neural networks and their applications, fuzzy systems and their applications, evolutionary algorithms and their applications, classification, rule discovery and clustering, image analysis, speech and robotics, bioinformatics and medical applications, various problems of artificial intelligence, and agent systems.
Download or read book Growth Hormone And The Heart written by Andrea Giustina and published by Springer Science & Business Media. This book was released on 2000-11-30 with total page 538 pages. Available in PDF, EPUB and Kindle. Book excerpt: Growth Hormone and the Heart endeavors to bring together knowledge that has been accumulated in the area of GH and the heart, from basic to clinical studies, by research groups working on this topic throughout the world. Lessons from different experimental models and from several human diseases (acromegaly, adult GH deficiency, heart failure) suggest to endocrinologists and cardiologists that GH may not only have a role in the physiology and pathophysiology of heart function, but that GH itself may have a place in the treatment of primary heart diseases (such as dilated cardiomyopathy) or of cardiac complications of hypopituitarism. Growth Hormone and the Heart will be a useful update of the research produced in the field of cardiovascular endocrinology. The Editors also hope that this book will serve as the primary step in the recognition of the wide physiological and clinical significance of GH and heart interactions.
Download or read book Industrial and Engineering Applications of Artificial Intelligence and Expert Systems written by Graham F. Forsyth and published by CRC Press. This book was released on 1995-08-08 with total page 888 pages. Available in PDF, EPUB and Kindle. Book excerpt: In the areas of industry and engineering, AI techniques have become the norm in sectors including computer-aided design, intelligent manufacturing, and control. Papers in this volume represent work by both computer scientists and engineers separately and together. They directly and indirectly represent a real collaboration between computer science and engineering, covering a wide variety of fields related to intelligent systems technology ranging from neural networks, knowledge acquisition and representation, automated scheduling, machine learning, multimedia, genetic algorithms, fuzzy logic, robotics, automated reasoning, heuristic searching, automated problem solving, temporal, spatial and model-based reasoning, clustering, blackboard architectures, automated design, pattern recognition and image processing, automated planning, speech recognition, simulated annealing, and intelligent tutoring, as well as various computer applications of intelligent systems including financial analysis, artificial
Download or read book Neural Network Design written by Martin T. Hagan and published by . This book was released on 2003 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book 1995 IEEE International Conference on Neural Networks written by and published by Institute of Electrical & Electronics Engineers(IEEE). This book was released on 1995 with total page 764 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Genetic Programming Theory and Practice XVII written by Wolfgang Banzhaf and published by Springer Nature. This book was released on 2020-05-07 with total page 409 pages. Available in PDF, EPUB and Kindle. Book excerpt: These contributions, written by the foremost international researchers and practitioners of Genetic Programming (GP), explore the synergy between theoretical and empirical results on real-world problems, producing a comprehensive view of the state of the art in GP. In this year’s edition, the topics covered include many of the most important issues and research questions in the field, such as: opportune application domains for GP-based methods, game playing and co-evolutionary search, symbolic regression and efficient learning strategies, encodings and representations for GP, schema theorems, and new selection mechanisms.The volume includes several chapters on best practices and lessons learned from hands-on experience. Readers will discover large-scale, real-world applications of GP to a variety of problem domains via in-depth presentations of the latest and most significant results.
Download or read book Research Anthology on Artificial Neural Network Applications written by Management Association, Information Resources and published by IGI Global. This book was released on 2021-07-16 with total page 1575 pages. Available in PDF, EPUB and Kindle. Book excerpt: Artificial neural networks (ANNs) present many benefits in analyzing complex data in a proficient manner. As an effective and efficient problem-solving method, ANNs are incredibly useful in many different fields. From education to medicine and banking to engineering, artificial neural networks are a growing phenomenon as more realize the plethora of uses and benefits they provide. Due to their complexity, it is vital for researchers to understand ANN capabilities in various fields. The Research Anthology on Artificial Neural Network Applications covers critical topics related to artificial neural networks and their multitude of applications in a number of diverse areas including medicine, finance, operations research, business, social media, security, and more. Covering everything from the applications and uses of artificial neural networks to deep learning and non-linear problems, this book is ideal for computer scientists, IT specialists, data scientists, technologists, business owners, engineers, government agencies, researchers, academicians, and students, as well as anyone who is interested in learning more about how artificial neural networks can be used across a wide range of fields.
Download or read book Highly Efficient Deep Intelligence Via Multi Parent Evolutionary Synthesis of Deep Neural Networks written by Audrey Chung and published by . This book was released on 2020 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Machine learning methods, and particularly deep neural networks, are a rapidly growing field and are currently being employed in domains such as science, business, and government. However, the significant success of neural networks has largely been due to the increasingly large model sizes and enormous amounts of required training data. As a result, powerful neural networks are accompanied by growing storage and memory requirements, making these powerful models infeasible for practical scenarios that use small embedded devices without access to cloud computing. As such, methods for significantly reducing the memory and computational requirements of high-performing deep neural networks via sparsification and/or compression have been developed. More recently, the concept of evolutionary deep intelligence was proposed, and takes inspiration from nature and allows highly-efficient deep neural networks to organically synthesize over successive generations. However, current work in evolutionary deep intelligence has been limited to the use of asexual evolutionary synthesis where a newly synthesized offspring network is solely dependent on a single parent network from the preceding generation. In this thesis, we introduce a general framework for synthesizing efficient neural network architectures via multi-parent evolutionary synthesis. Generalized from the asexual evolutionary synthesis approach, the framework allows for a newly synthesized network to be dependent on a subset of all previously synthesized networks. By imposing constraints on this general framework, the cases of asexual evolutionary synthesis, 2-parent sexual evolutionary synthesis, and m-parent evolutionary synthesis can all be realized. We explore the computational construct used to mimic heredity, and generalize it beyond the asexual evolutionary synthesis used in current evolutionary deep intelligence works. The efficacy of incorporating multiple parent networks during evolutionary synthesis was examined first in the context of 2-parent sexual evolutionary synthesis, then generalized to m-parent evolutionary synthesis in the context of varying generational population sizes. Both experiments show that the use of multiple parent networks during evolutionary synthesis allows for increased network diversity as well as steeper trends in increasing network efficiency over generations. We also introduce the concept of gene tagging within the evolutionary deep intelligence framework as a means to enforce a like-with-like mating policy during the multi-parent evolutionary synthesis process, and evaluate the effect of architectural alignment during multi-parent evolutionary synthesis. We present an experiment exploring the quantification of network architectural similarity in populations of networks. In addition, we investigate the the computational construct used to mimic natural selection. The impact of various environmental resource models used to mimic the constraint of available computational and storage resources on network synthesis over successive generations is explored, and results clearly demonstrate the trade-off between computation time and optimal model performance. The results of m-parent evolutionary synthesis are promising, and indicate the potential benefits of incorporating multiple parent networks during evolutionary synthesis for highly-efficient evolutionary deep intelligence. Future work includes studying the effects of inheriting weight values (as opposed to random initialization) on total training time and further investigation of potential structural similarity metrics, with the goal of developing a deeper understanding of the underlying effects of network architecture on performance.
