State of the Art in Neural Networks and Their Applications

State of the Art in Neural Networks and Their Applications
Author: Ayman S. El-Baz,Jasjit S. Suri
Publsiher: Academic Press
Total Pages: 324
Release: 2021-07-21
ISBN: 0128218495
Category: Science
Language: EN, FR, DE, ES & NL

State of the Art in Neural Networks and Their Applications Book Excerpt:

State of the Art in Neural Networks and Their Applications presents the latest advances in artificial neural networks and their applications across a wide range of clinical diagnoses. Advances in the role of machine learning, artificial intelligence, deep learning, cognitive image processing and suitable data analytics useful for clinical diagnosis and research applications are covered, including relevant case studies. The application of Neural Network, Artificial Intelligence, and Machine Learning methods in biomedical image analysis have resulted in the development of computer-aided diagnostic (CAD) systems that aim towards the automatic early detection of several severe diseases. State of the Art in Neural Networks and Their Applications is presented in two volumes. Volume 1 covers the state-of-the-art deep learning approaches for the detection of renal, retinal, breast, skin, and dental abnormalities and more. Includes applications of neural networks, AI, machine learning, and deep learning techniques to a variety of imaging technologies Provides in-depth technical coverage of computer-aided diagnosis (CAD), with coverage of computer-aided classification, Unified Deep Learning Frameworks, mammography, fundus imaging, optical coherence tomography, cryo-electron tomography, 3D MRI, CT, and more. Covers deep learning for several medical conditions including renal, retinal, breast, skin, and dental abnormalities, Medical Image Analysis, as well as detection, segmentation, and classification via AI.

State of the Art in Neural Networks and Their Applications

State of the Art in Neural Networks and Their Applications
Author: Jasjit S. Suri,Ayman S. El-Baz
Publsiher: Elsevier
Total Pages: 328
Release: 2022-12-09
ISBN: 0128199121
Category: Science
Language: EN, FR, DE, ES & NL

State of the Art in Neural Networks and Their Applications Book Excerpt:

State of the Art in Neural Networks and Their Applications, Volume Two presents the latest advances in artificial neural networks and their applications across a wide range of clinical diagnoses. The book provides over views and case studies of advances in the role of machine learning, artificial intelligence, deep learning, cognitive image processing, and suitable data analytics useful for clinical diagnosis and research applications. The application of neural network, artificial intelligence and machine learning methods in biomedical image analysis have resulted in the development of computer-aided diagnostic (CAD) systems that aim towards the automatic early detection of several severe diseases. State of the Art in Neural Networks and Their Applications is presented in two volumes. Volume One: Neural Networks in Oncology Imaging covers lung cancer, prostate cancer, and bladder cancer. Volume Two: Neural Networks in Brain Disorders and Other Diseases covers autism spectrum disorder, Alzheimer’s disease, attention deficit hyperactivity disorder, hypertension, and other diseases. Written by experienced engineers in the field, these two volumes will help engineers, computer scientists, researchers, and clinicians understand the technology and applications of artificial neural networks. Includes applications of neural networks, AI, machine learning, and deep learning techniques to a variety of oncology imaging technologies Provides in-depth technical coverage of computer-aided diagnosis (CAD), including coverage of computer-aided classification, unified deep learning frameworks, 3D MRI, PET/CT, and more Covers deep learning cancer identification from histopathological images, medical image analysis, detection, segmentation and classification via AI

Complex Networks and Their Applications VIII

Complex Networks and Their Applications VIII
Author: Hocine Cherifi,Sabrina Gaito,José Fernendo Mendes,Esteban Moro,Luis Mateus Rocha
Publsiher: Springer Nature
Total Pages: 1034
Release: 2019-11-26
ISBN: 3030366839
Category: Technology & Engineering
Language: EN, FR, DE, ES & NL

Complex Networks and Their Applications VIII Book Excerpt:

This book highlights cutting-edge research in the field of network science, offering scientists, researchers, students, and practitioners a unique update on the latest advances in theory and a multitude of applications. It presents the peer-reviewed proceedings of the Eighth International Conference on Complex Networks and their Applications (COMPLEX NETWORKS 2019), which took place in Lisbon, Portugal, on December 10–12, 2019. The carefully selected papers cover a wide range of theoretical topics such as network models and measures; community structure, and network dynamics; diffusion, epidemics, and spreading processes; resilience and control as well as all the main network applications, including social and political networks; networks in finance and economics; biological and neuroscience networks; and technological networks.

Complex Networks and Their Applications VII

Complex Networks and Their Applications VII
Author: Luca Maria Aiello,Chantal Cherifi,Hocine Cherifi,Renaud Lambiotte,Pietro Lió,Luis M. Rocha
Publsiher: Springer
Total Pages: 677
Release: 2018-12-05
ISBN: 3030054144
Category: Technology & Engineering
Language: EN, FR, DE, ES & NL

Complex Networks and Their Applications VII Book Excerpt:

This book highlights cutting-edge research in the field of network science, offering scientists, researchers, students and practitioners a unique update on the latest advances in theory, together with a wealth of applications. It presents the peer-reviewed proceedings of the VII International Conference on Complex Networks and their Applications (COMPLEX NETWORKS 2018), which was held in Cambridge on December 11–13, 2018. The carefully selected papers cover a wide range of theoretical topics such as network models and measures; community structure and network dynamics; diffusion, epidemics and spreading processes; and resilience and control; as well as all the main network applications, including social and political networks; networks in finance and economics; biological and neuroscience networks; and technological networks.

Complex Networks Their Applications X

Complex Networks   Their Applications X
Author: Rosa Maria Benito,Chantal Cherifi,Hocine Cherifi,Esteban Moro,Luis M. Rocha,Marta Sales-Pardo
Publsiher: Springer Nature
Total Pages: 896
Release: 2022-01-01
ISBN: 3030934098
Category: Technology & Engineering
Language: EN, FR, DE, ES & NL

Complex Networks Their Applications X Book Excerpt:

This book highlights cutting-edge research in the field of network science, offering scientists, researchers, students, and practitioners a unique update on the latest advances in theory and a multitude of applications. It presents the peer-reviewed proceedings of the X International Conference on Complex Networks and their Applications (COMPLEX NETWORKS 2021). The carefully selected papers cover a wide range of theoretical topics such as network models and measures; community structure, network dynamics; diffusion, epidemics and spreading processes; resilience and control as well as all the main network applications, including social and political networks; networks in finance and economics; biological and neuroscience networks, and technological networks.

Reconfigurable Cellular Neural Networks and Their Applications

Reconfigurable Cellular Neural Networks and Their Applications
Author: Müştak E. Yalçın,Tuba Ayhan,Ramazan Yeniçeri
Publsiher: Springer
Total Pages: 74
Release: 2019-04-15
ISBN: 3030178404
Category: Technology & Engineering
Language: EN, FR, DE, ES & NL

Reconfigurable Cellular Neural Networks and Their Applications Book Excerpt:

This book explores how neural networks can be designed to analyze sensory data in a way that mimics natural systems. It introduces readers to the cellular neural network (CNN) and formulates it to match the behavior of the Wilson–Cowan model. In turn, two properties that are vital in nature are added to the CNN to help it more accurately deliver mimetic behavior: randomness of connection, and the presence of different dynamics (excitatory and inhibitory) within the same network. It uses an ID matrix to determine the location of excitatory and inhibitory neurons, and to reconfigure the network to optimize its topology. The book demonstrates that reconfiguring a single-layer CNN is an easier and more flexible solution than the procedure required in a multilayer CNN, in which excitatory and inhibitory neurons are separate, and that the key CNN criteria of a spatially invariant template and local coupling are fulfilled. In closing, the application of the authors’ neuron population model as a feature extractor is exemplified using odor and electroencephalogram classification.

Proceedings of the 7th IEEE International Workshop on Cellular Neural Networks and Their Applications

Proceedings of the 7th IEEE International Workshop on Cellular Neural Networks and Their Applications
Author: Ronald Tetzlaff
Publsiher: World Scientific
Total Pages: 704
Release: 2002
ISBN: 9789812776792
Category: Computers
Language: EN, FR, DE, ES & NL

Proceedings of the 7th IEEE International Workshop on Cellular Neural Networks and Their Applications Book Excerpt:

This volume covers the fundamental theory of Cellular Neural Networks as well as their applications in various fields such as science and technology. It contains all 83 papers of the 7th International Workshop on Cellular Neural Networks and their Applications. The workshop follows a biennial series of six workshops consecutively hosted in Budapest (1990), Munich, Rome, Seville, London and Catania (2000).

Advances in Neural Networks ISNN 2019

Advances in Neural Networks     ISNN 2019
Author: Huchuan Lu,Huajin Tang,Zhanshan Wang
Publsiher: Springer
Total Pages: 615
Release: 2019-06-26
ISBN: 3030228088
Category: Computers
Language: EN, FR, DE, ES & NL

Advances in Neural Networks ISNN 2019 Book Excerpt:

This two-volume set LNCS 11554 and 11555 constitutes the refereed proceedings of the 16th International Symposium on Neural Networks, ISNN 2019, held in Moscow, Russia, in July 2019. The 111 papers presented in the two volumes were carefully reviewed and selected from numerous submissions. The papers were organized in topical sections named: Learning System, Graph Model, and Adversarial Learning; Time Series Analysis, Dynamic Prediction, and Uncertain Estimation; Model Optimization, Bayesian Learning, and Clustering; Game Theory, Stability Analysis, and Control Method; Signal Processing, Industrial Application, and Data Generation; Image Recognition, Scene Understanding, and Video Analysis; Bio-signal, Biomedical Engineering, and Hardware.

Cellular Neural Networks and Their Applications

Cellular Neural Networks and Their Applications
Author: Ronald Tetzlaff
Publsiher: World Scientific
Total Pages: 700
Release: 2002-07-08
ISBN: 9814487767
Category: Computers
Language: EN, FR, DE, ES & NL

Cellular Neural Networks and Their Applications Book Excerpt:

This volume covers the fundamental theory of Cellular Neural Networks as well as their applications in various fields such as science and technology. It contains all 83 papers of the 7th International Workshop on Cellular Neural Networks and their Applications. The workshop follows a biennial series of six workshops consecutively hosted in Budapest (1990), Munich, Rome, Seville, London and Catania (2000). Contents:On the Relationship Between CNNs and PDEs (M Gilli et al.)Moving Object Tracking on Panoramic Images (P Földesy et al.)Emergence of Global Patterns in Connected Neural Networks (T Shimizu)Configurable Multi-Layer CNN-UM Emulator on FPGA (Z Nagy & P Szolgay)A CNN Based System to Blind Sources Separation of MEG Signals (M Bucolo et al.)Time as Coding Space for Information Processing in the Cerebral Cortex (W Singer)Analyzing Multidimensional Neural Activity via CNN-UM (V Gál et al.)Visual Feedback by Using a CNN Chip Prototype System (P Arena et al.)Computational and Computer Complexity of Analogic Cellular Wave Computers (T Roska)Chaotic Phenomena in Quantum Cellular Neural Networks (L Fortuna & D Porto)Fingerprint Image Enhancement Using CNN Gabor-Type Filters (E Saatci & V Tavsanoglu)CNN Based Color Constancy Algorithm (L Török & Á Zarándy)Statistical Error Modeling of CNN-UM Architectures: The Grayscale Case (P Földesy)MEMS, Microsystems and Nanosystems (M E Zaghloul)Texture Segmentation by the 64x64 CNN Chip (T Szirányi)Teaching CNN and Learning by Using CNN (P Arena et al.)Novel Methods and Results in Training Universal Multi-Nested Neurons (R Dogaru et al.)Test-Bed Board for 16x64 Stereo Vision CNN Chip (M Salerno et al.)and other papers Readership: Graduate students, researchers, lecturers and industrialists. Keywords:

Complex Valued Neural Networks with Multi Valued Neurons

Complex Valued Neural Networks with Multi Valued Neurons
Author: Igor Aizenberg
Publsiher: Springer Science & Business Media
Total Pages: 273
Release: 2011-06-24
ISBN: 3642203523
Category: Computers
Language: EN, FR, DE, ES & NL

Complex Valued Neural Networks with Multi Valued Neurons Book Excerpt:

Complex-Valued Neural Networks have higher functionality, learn faster and generalize better than their real-valued counterparts. This book is devoted to the Multi-Valued Neuron (MVN) and MVN-based neural networks. It contains a comprehensive observation of MVN theory, its learning, and applications. MVN is a complex-valued neuron whose inputs and output are located on the unit circle. Its activation function is a function only of argument (phase) of the weighted sum. MVN derivative-free learning is based on the error-correction rule. A single MVN can learn those input/output mappings that are non-linearly separable in the real domain. Such classical non-linearly separable problems as XOR and Parity n are the simplest that can be learned by a single MVN. Another important advantage of MVN is a proper treatment of the phase information. These properties of MVN become even more remarkable when this neuron is used as a basic one in neural networks. The Multilayer Neural Network based on Multi-Valued Neurons (MLMVN) is an MVN-based feedforward neural network. Its backpropagation learning algorithm is derivative-free and based on the error-correction rule. It does not suffer from the local minima phenomenon. MLMVN outperforms many other machine learning techniques in terms of learning speed, network complexity and generalization capability when solving both benchmark and real-world classification and prediction problems. Another interesting application of MVN is its use as a basic neuron in multi-state associative memories. The book is addressed to those readers who develop theoretical fundamentals of neural networks and use neural networks for solving various real-world problems. It should also be very suitable for Ph.D. and graduate students pursuing their degrees in computational intelligence.

Encyclopedia of Computer Science and Technology

Encyclopedia of Computer Science and Technology
Author: Allen Kent,James G. Williams
Publsiher: CRC Press
Total Pages: 416
Release: 1996-07-26
ISBN: 9780824722883
Category: Computers
Language: EN, FR, DE, ES & NL

Encyclopedia of Computer Science and Technology Book Excerpt:

Acquiring Task-Based Knowledge and Specifications to Seek Time Evaluation

Artificial Neural Networks for Renewable Energy Systems and Real World Applications

Artificial Neural Networks for Renewable Energy Systems and Real World Applications
Author: Ammar Hamed Elsheikh,Mohamed Elasyed Abd Elaziz
Publsiher: Academic Press
Total Pages: 290
Release: 2022-09-08
ISBN: 0128231866
Category: Technology & Engineering
Language: EN, FR, DE, ES & NL

Artificial Neural Networks for Renewable Energy Systems and Real World Applications Book Excerpt:

Artificial Neural Networks for Renewable Energy Systems and Real-World Applications presents current trends for the solution of complex engineering problems in the application, modeling, analysis, and optimization of different energy systems and manufacturing processes. With growing research catering to the applications of neural networks in specific industrial applications, this reference provides a single resource catering to a broader perspective of ANN in renewable energy systems and manufacturing processes. ANN-based methods have attracted the attention of scientists and researchers in different engineering and industrial disciplines, making this book a useful reference for all researchers and engineers interested in artificial networks, renewable energy systems, and manufacturing process analysis. Includes illustrative examples on the design and development of ANNS for renewable and manufacturing applications Features computer-aided simulations presented as algorithms, pseudocodes and flowcharts Covers ANN theory for easy reference in subsequent technology specific sections

Current Perspectives and New Directions in Mechanics Modelling and Design of Structural Systems

Current Perspectives and New Directions in Mechanics  Modelling and Design of Structural Systems
Author: Alphose Zingoni
Publsiher: CRC Press
Total Pages: 4438
Release: 2022-09-02
ISBN: 1000824365
Category: Technology & Engineering
Language: EN, FR, DE, ES & NL

Current Perspectives and New Directions in Mechanics Modelling and Design of Structural Systems Book Excerpt:

Current Perspectives and New Directions in Mechanics, Modelling and Design of Structural Systems comprises 330 papers that were presented at the Eighth International Conference on Structural Engineering, Mechanics and Computation (SEMC 2022, Cape Town, South Africa, 5-7 September 2022). The topics featured may be clustered into six broad categories that span the themes of mechanics, modelling and engineering design: (i) mechanics of materials (elasticity, plasticity, porous media, fracture, fatigue, damage, delamination, viscosity, creep, shrinkage, etc); (ii) mechanics of structures (dynamics, vibration, seismic response, soil-structure interaction, fluid-structure interaction, response to blast and impact, response to fire, structural stability, buckling, collapse behaviour); (iii) numerical modelling and experimental testing (numerical methods, simulation techniques, multi-scale modelling, computational modelling, laboratory testing, field testing, experimental measurements); (iv) design in traditional engineering materials (steel, concrete, steel-concrete composite, aluminium, masonry, timber); (v) innovative concepts, sustainable engineering and special structures (nanostructures, adaptive structures, smart structures, composite structures, glass structures, bio-inspired structures, shells, membranes, space structures, lightweight structures, etc); (vi) the engineering process and life-cycle considerations (conceptualisation, planning, analysis, design, optimization, construction, assembly, manufacture, maintenance, monitoring, assessment, repair, strengthening, retrofitting, decommissioning). Two versions of the papers are available: full papers of length 6 pages are included in the e-book, while short papers of length 2 pages, intended to be concise but self-contained summaries of the full papers, are in the printed book. This work will be of interest to civil, structural, mechanical, marine and aerospace engineers, as well as planners and architects.

Power Converters and AC Electrical Drives with Linear Neural Networks

Power Converters and AC Electrical Drives with Linear Neural Networks
Author: Maurizio Cirrincione,Marcello Pucci,Gianpaolo Vitale
Publsiher: CRC Press
Total Pages: 649
Release: 2017-12-19
ISBN: 1351833944
Category: Technology & Engineering
Language: EN, FR, DE, ES & NL

Power Converters and AC Electrical Drives with Linear Neural Networks Book Excerpt:

The first book of its kind, Power Converters and AC Electrical Drives with Linear Neural Networks systematically explores the application of neural networks in the field of power electronics, with particular emphasis on the sensorless control of AC drives. It presents the classical theory based on space-vectors in identification, discusses control of electrical drives and power converters, and examines improvements that can be attained when using linear neural networks. The book integrates power electronics and electrical drives with artificial neural networks (ANN). Organized into four parts, it first deals with voltage source inverters and their control. It then covers AC electrical drive control, focusing on induction and permanent magnet synchronous motor drives. The third part examines theoretical aspects of linear neural networks, particularly the neural EXIN family. The fourth part highlights original applications in electrical drives and power quality, ranging from neural-based parameter estimation and sensorless control to distributed generation systems from renewable sources and active power filters. Simulation and experimental results are provided to validate the theories. Written by experts in the field, this state-of-the-art book requires basic knowledge of electrical machines and power electronics, as well as some familiarity with control systems, signal processing, linear algebra, and numerical analysis. Offering multiple paths through the material, the text is suitable for undergraduate and postgraduate students, theoreticians, practicing engineers, and researchers involved in applications of ANNs.

Meta Learning

Meta Learning
Author: Lan Zou
Publsiher: Elsevier
Total Pages: 404
Release: 2022-11-18
ISBN: 0323903703
Category: Computers
Language: EN, FR, DE, ES & NL

Meta Learning Book Excerpt:

Deep neural networks (DNNs) with their dense and complex algorithms provide real possibilities for Artificial General Intelligence (AGI). Meta-learning with DNNs brings AGI much closer: artificial agents solving intelligent tasks that human beings can achieve, even transcending what they can achieve. Meta-Learning: Theory, Algorithms and Applications shows how meta-learning in combination with DNNs advances towards AGI. The book explains the fundamentals of meta-learning by providing answers to these questions: What is meta-learning?; why do we need meta-learning?; how are self-improved meta-learning mechanisms heading for AGI ?; how can we use meta-learning in our approach to specific scenarios? The book presents the background of seven mainstream paradigms: meta-learning, few-shot learning, deep learning, transfer learning, machine learning, probabilistic modeling, and Bayesian inference. It then explains important state-of-the-art mechanisms and their variants for meta-learning, including memory-augmented neural networks, meta-networks, convolutional Siamese neural networks, matching networks, prototypical networks, relation networks, LSTM meta-learning, model-agnostic meta-learning, and the Reptile algorithm. The book takes a deep dive into nearly 200 state-of-the-art meta-learning algorithms from top tier conferences (e.g. NeurIPS, ICML, CVPR, ACL, ICLR, KDD). It systematically investigates 39 categories of tasks from 11 real-world application fields: Computer Vision, Natural Language Processing, Meta-Reinforcement Learning, Healthcare, Finance and Economy, Construction Materials, Graphic Neural Networks, Program Synthesis, Smart City, Recommended Systems, and Climate Science. Each application field concludes by looking at future trends or by giving a summary of available resources Meta-Learning: Theory, Algorithms and Applications is a great resource to understand the principles of meta-learning and to learn state-of-the-art meta-learning algorithms, giving the student, researcher and industry professional the ability to apply meta-learning for various novel applications. • A comprehensive overview of state-of-the-art meta-learning techniques and methods associated with deep neural networks together with a broad range of application areas • Coverage of nearly 200 state-of-the-art meta-learning algorithms, which are promoted by premier global AI conferences and journals, and 300 to 450 pieces of key research. • Systematic and detailed exploration of the most crucial state-of-the-art meta-learning algorithm mechanisms: model-based, metric-based, and optimization-based. • Provides solutions to the limitations of using deep learning and/or machine learning methods, particularly with small sample sizes and unlabeled data • Gives an understanding of how meta-learning acts as a stepping stone to Artificial General Intelligence in 39 categories of tasks from 11 real-world application fields.

Deep Learning for Natural Language Processing

Deep Learning for Natural Language Processing
Author: Karthiek Reddy Bokka,Shubhangi Hora,Tanuj Jain,Monicah Wambugu
Publsiher: Packt Publishing Ltd
Total Pages: 372
Release: 2019-06-11
ISBN: 1838553673
Category: Computers
Language: EN, FR, DE, ES & NL

Deep Learning for Natural Language Processing Book Excerpt:

Gain the knowledge of various deep neural network architectures and their application areas to conquer your NLP issues. Key FeaturesGain insights into the basic building blocks of natural language processingLearn how to select the best deep neural network to solve your NLP problemsExplore convolutional and recurrent neural networks and long short-term memory networksBook Description Applying deep learning approaches to various NLP tasks can take your computational algorithms to a completely new level in terms of speed and accuracy. Deep Learning for Natural Language Processing starts off by highlighting the basic building blocks of the natural language processing domain. The book goes on to introduce the problems that you can solve using state-of-the-art neural network models. After this, delving into the various neural network architectures and their specific areas of application will help you to understand how to select the best model to suit your needs. As you advance through this deep learning book, you’ll study convolutional, recurrent, and recursive neural networks, in addition to covering long short-term memory networks (LSTM). Understanding these networks will help you to implement their models using Keras. In the later chapters, you will be able to develop a trigger word detection application using NLP techniques such as attention model and beam search. By the end of this book, you will not only have sound knowledge of natural language processing but also be able to select the best text pre-processing and neural network models to solve a number of NLP issues. What you will learnUnderstand various pre-processing techniques for deep learning problemsBuild a vector representation of text using word2vec and GloVeCreate a named entity recognizer and parts-of-speech tagger with Apache OpenNLPBuild a machine translation model in KerasDevelop a text generation application using LSTMBuild a trigger word detection application using an attention modelWho this book is for If you’re an aspiring data scientist looking for an introduction to deep learning in the NLP domain, this is just the book for you. Strong working knowledge of Python, linear algebra, and machine learning is a must.

The Application of Neural Networks in the Earth System Sciences

The Application of Neural Networks in the Earth System Sciences
Author: Vladimir M. Krasnopolsky
Publsiher: Springer Science & Business Media
Total Pages: 189
Release: 2013-06-14
ISBN: 9400760736
Category: Science
Language: EN, FR, DE, ES & NL

The Application of Neural Networks in the Earth System Sciences Book Excerpt:

This book brings together a representative set of Earth System Science (ESS) applications of the neural network (NN) technique. It examines a progression of atmospheric and oceanic problems, which, from the mathematical point of view, can be formulated as complex, multidimensional, and nonlinear mappings. It is shown that these problems can be solved utilizing a particular type of NN – the multilayer perceptron (MLP). This type of NN applications covers the majority of NN applications developed in ESSs such as meteorology, oceanography, atmospheric and oceanic satellite remote sensing, numerical weather prediction, and climate studies. The major properties of the mappings and MLP NNs are formulated and discussed. Also, the book presents basic background for each introduced application and provides an extensive set of references. “This is an excellent book to learn how to apply artificial neural network methods to earth system sciences. The author, Dr. Vladimir Krasnopolsky, is a universally recognized master in this field. With his vast knowledge and experience, he carefully guides the reader through a broad variety of problems found in the earth system sciences where neural network methods can be applied fruitfully. (...) The broad range of topics covered in this book ensures that researchers/graduate students from many fields (...) will find it an invaluable guide to neural network methods.” (Prof. William W. Hsieh, University of British Columbia, Vancouver, Canada) “Vladimir Krasnopolsky has been the “founding father” of applying computation intelligence methods to environmental science; (...) Dr. Krasnopolsky has created a masterful exposition of a young, yet maturing field that promises to advance a deeper understanding of best modeling practices in environmental science.” (Dr. Sue Ellen Haupt, National Center for Atmospheric Research, Boulder, USA) “Vladimir Krasnopolsky has written an important and wonderful book on applications of neural networks to replace complex and expensive computational algorithms within Earth System Science models. He is uniquely qualified to write this book, since he has been a true pioneer with regard to many of these applications. (...) Many other examples of creative emulations will inspire not just readers interested in the Earth Sciences, but any other modeling practitioner (...) to address both theoretical and practical complex problems that may (or will!) arise in a complex system." ” (Prof. Eugenia Kalnay, University of Maryland, USA)

Business Applications of Neural Networks

Business Applications of Neural Networks
Author: Paulo J. G. Lisboa,Bill Edisbury,Alfredo Vellido
Publsiher: OECD Publishing
Total Pages: 228
Release: 2000
ISBN: 9789810240899
Category: Business & Economics
Language: EN, FR, DE, ES & NL

Business Applications of Neural Networks Book Excerpt:

Neural networks are increasingly being used in real-world business applications and, in some cases, such as fraud detection, they have already become the method of choice. Their use for risk assessment is also growing and they have been employed to visualise complex databases for marketing segmentation. This boom in applications covers a wide range of business interests -- from finance management, through forecasting, to production. The combination of statistical, neural and fuzzy methods now enables direct quantitative studies to be carried out without the need for rocket-science expertise. This book reviews the state-of-the-art in current applications of neural-network methods in three important areas of business analysis. It includes a tutorial chapter to introduce new users to the potential and pitfalls of this new technology.

The Handbook of Computational Linguistics and Natural Language Processing

The Handbook of Computational Linguistics and Natural Language Processing
Author: Alexander Clark,Chris Fox,Shalom Lappin
Publsiher: John Wiley & Sons
Total Pages: 802
Release: 2012-10-04
ISBN: 1118347188
Category: Language Arts & Disciplines
Language: EN, FR, DE, ES & NL

The Handbook of Computational Linguistics and Natural Language Processing Book Excerpt:

This comprehensive reference work provides an overview of the concepts, methodologies, and applications in computational linguistics and natural language processing (NLP). Features contributions by the top researchers in the field, reflecting the work that is driving the discipline forward Includes an introduction to the major theoretical issues in these fields, as well as the central engineering applications that the work has produced Presents the major developments in an accessible way, explaining the close connection between scientific understanding of the computational properties of natural language and the creation of effective language technologies Serves as an invaluable state-of-the-art reference source for computational linguists and software engineers developing NLP applications in industrial research and development labs of software companies

Emerging Computing Paradigms

Emerging Computing Paradigms
Author: Umang Singh,San Murugesan,Ashish Seth
Publsiher: John Wiley & Sons
Total Pages: 308
Release: 2022-07-25
ISBN: 1119813409
Category: Computers
Language: EN, FR, DE, ES & NL

Emerging Computing Paradigms Book Excerpt:

EMERGING COMPUTING PARADIGMS A holistic overview of major new computing paradigms of the 21st Century In Emerging Computing Paradigms: Principles, Advances and Applications, international scholars offer a compendium of essential knowledge on new promising computing paradigms. The book examines the characteristics and features of emerging computing technologies and provides insight into recent technological developments and their potential real-world applications that promise to shape the future. This book is a useful resource for all those who wish to quickly grasp new concepts of, and insights on, emerging computer paradigms and pursue further research or innovate new novel applications harnessing these concepts. Key Features Presents a comprehensive coverage of new technologies that have the potential to shape the future of our world—quantum computing, computational intelligence, advanced wireless networks and blockchain technology Revisits mainstream ideas now being widely adopted, such as cloud computing, the Internet of Things (IoT) and cybersecurity Offers recommendations and practical insights to assist the readers in the application of these technologies Aimed at IT professionals, educators, researchers, and students, Emerging Computing Paradigms: Principles, Advances and Applications is a comprehensive resource to get ahead of the curve in examining and exploiting emerging new concepts and technologies. Business executives will also find the book valuable and gain an advantage over competitors in harnessing the concepts examined therein.