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Author : Hoffmann, Frank,Hüllermeier, E.
Publisher : KIT Scientific Publishing
Page : 328 pages
File Size : 54,7 Mb
Release : 2015-11-16
Category : Electronic
ISBN : 9783731504320
Author : Hoffmann, Frank,Huellermeier, E.,Mikut, Ralf
Publisher : KIT Scientific Publishing
Page : 294 pages
File Size : 44,5 Mb
Release : 2016-11-14
Category : Electronic
ISBN : 9783731505884
Author : Schulte, Horst,Hoffmann, Frank,Mikut, Ralf
Publisher : KIT Scientific Publishing
Page : 318 pages
File Size : 47,6 Mb
Release : 2021-11-15
Category : Computers
ISBN : 9783731511311
Dieser Tagungsband enthält die Beiträge des 31. Workshop Computational Intelligence. Die Schwerpunkte sind Methoden, Anwendungen und Tools für Fuzzy-Systeme, Künstliche Neuronale Netze, Evolutionäre Algorithmen und Data-Mining-Verfahren sowie der Methodenvergleich anhand von industriellen und Benchmark-Problemen. - The proceedings of the 31st Workshop on Computational Intelligence focus on methods, applications, and tools for fuzzy systems, artificial neural networks, deep learning, system identification, and data mining techniques.
Author : Hoffmann, Frank,Huellermeier, E.,Mikut, Ralf
Publisher : KIT Scientific Publishing
Page : 310 pages
File Size : 45,6 Mb
Release : 2017-11-09
Category : Electronic
ISBN : 9783731507260
Author : Schulte, Horst ,Hoffmann, Frank,Mikut, Ralf
Publisher : KIT Scientific Publishing
Page : 288 pages
File Size : 52,7 Mb
Release : 2020-11-20
Category : Computers
ISBN : 9783731510512
Dieser Tagungsband enthält die Beiträge des 30. Workshops Computational Intelligence. Die Schwerpunkte sind Methoden, Anwendungen und Tools für Fuzzy-Systeme, Künstliche Neuronale Netze, Evolutionäre Algorithmen und Data-Mining-Verfahren sowie der Methodenvergleich anhand von industriellen und Benchmark-Problemen. - The proceedings of the 30th workshop on computational intelligence focus on methods, applications, and tools for fuzzy systems, artificial neural networks, deep learning, system identification, and data mining techniques.
Author : Hoffmann, Frank,Huellermeier, E.
Publisher : KIT Scientific Publishing
Page : 380 pages
File Size : 43,6 Mb
Release : 2014-11-20
Category : Electronic
ISBN : 9783731502753
Author : Hoffmann, Frank,Hüllermeier, Eyke,Mikut, Ralf
Publisher : KIT Scientific Publishing
Page : 322 pages
File Size : 53,9 Mb
Release : 2019-11-21
Category : Computers
ISBN : 9783731509790
Author : Gabriele Kern-Isberner,Johannes Fürnkranz,Matthias Thimm
Publisher : Springer
Page : 396 pages
File Size : 52,6 Mb
Release : 2017-09-18
Category : Computers
ISBN : 9783319671901
This book constitutes the refereed proceedings of the 40th Annual German Conference on Artificial Intelligence, KI 2017 held in Dortmund, Germany in September 2017. The 20 revised full technical papers presented together with 16 short technical communications were carefully reviewed and selected from 73 submissions. The conference cover a range of topics from, e. g., agents, robotics, cognitive sciences, machine learning, planning, knowledge representation, reasoning, and ontologies, with numerous applications in areas like social media, psychology, transportation systems and reflecting the richness and diversity of their field.
Author : Frederik Rehbach
Publisher : Springer Nature
Page : 123 pages
File Size : 40,8 Mb
Release : 2023-05-29
Category : Technology & Engineering
ISBN : 9783031306099
This book presents a solution to the challenging issue of optimizing expensive-to-evaluate industrial problems such as the hyperparameter tuning of machine learning models. The approach combines two well-established concepts, Surrogate-Based Optimization (SBO) and parallelization, to efficiently search for optimal parameter setups with as few function evaluations as possible. Through in-depth analysis, the need for parallel SBO solvers is emphasized, and it is demonstrated that they outperform model-free algorithms in scenarios with a low evaluation budget. The SBO approach helps practitioners save significant amounts of time and resources in hyperparameter tuning as well as other optimization projects. As a highlight, a novel framework for objectively comparing the efficiency of parallel SBO algorithms is introduced, enabling practitioners to evaluate and select the most effective approach for their specific use case. Based on practical examples, decision support is delivered, detailing which parts of industrial optimization projects can be parallelized and how to prioritize which parts to parallelize first. By following the framework, practitioners can make informed decisions about how to allocate resources and optimize their models efficiently.
Author : Thomas Bäck,Mike Preuss,André Deutz,Hao Wang,Carola Doerr,Michael Emmerich,Heike Trautmann
Publisher : Springer Nature
Page : 753 pages
File Size : 54,5 Mb
Release : 2020-09-02
Category : Computers
ISBN : 9783030581121
This two-volume set LNCS 12269 and LNCS 12270 constitutes the refereed proceedings of the 16th International Conference on Parallel Problem Solving from Nature, PPSN 2020, held in Leiden, The Netherlands, in September 2020. The 99 revised full papers were carefully reviewed and selected from 268 submissions. The topics cover classical subjects such as automated algorithm selection and configuration; Bayesian- and surrogate-assisted optimization; benchmarking and performance measures; combinatorial optimization; connection between nature-inspired optimization and artificial intelligence; genetic and evolutionary algorithms; genetic programming; landscape analysis; multiobjective optimization; real-world applications; reinforcement learning; and theoretical aspects of nature-inspired optimization.
Author : Mong-Fong Horng,Hsu-Yang Kung,Chi-Hua Chen,Feng-Jang Hwang
Publisher : MDPI
Page : 272 pages
File Size : 51,9 Mb
Release : 2020-05-22
Category : Technology & Engineering
ISBN : 9783039288632
This book collects 14 articles from the Special Issue entitled “Deep Learning Applications with Practical Measured Results in Electronics Industries” of Electronics. Topics covered in this Issue include four main parts: (1) environmental information analyses and predictions, (2) unmanned aerial vehicle (UAV) and object tracking applications, (3) measurement and denoising techniques, and (4) recommendation systems and education systems. These authors used and improved deep learning techniques (e.g., ResNet (deep residual network), Faster-RCNN (faster regions with convolutional neural network), LSTM (long short term memory), ConvLSTM (convolutional LSTM), GAN (generative adversarial network), etc.) to analyze and denoise measured data in a variety of applications and services (e.g., wind speed prediction, air quality prediction, underground mine applications, neural audio caption, etc.). Several practical experiments were conducted, and the results indicate that the performance of the presented deep learning methods is improved compared with the performance of conventional machine learning methods.
Author : Michael E. Auer,Danilo G. Zutin
Publisher : Springer
Page : 1062 pages
File Size : 47,7 Mb
Release : 2017-09-14
Category : Technology & Engineering
ISBN : 9783319643526
This book discusses online engineering and virtual instrumentation, typical working areas for today’s engineers and inseparably connected with areas such as Internet of Things, cyber-physical systems, collaborative networks and grids, cyber cloud technologies, and service architectures, to name just a few. It presents the outcomes of the 14th International Conference on Remote Engineering and Virtual Instrumentation (REV2017), held at Columbia University in New York from 15 to 17 March 2017. The conference addressed fundamentals, applications and experiences in the field of online engineering and virtual instrumentation in the light of growing interest in and need for teleworking, remote services and collaborative working environments as a result of the globalization of education. The book also discusses guidelines for education in university-level courses for these topics.
Author : Frank Hutter,Lars Kotthoff,Joaquin Vanschoren
Publisher : Springer
Page : 223 pages
File Size : 42,7 Mb
Release : 2019-05-17
Category : Computers
ISBN : 9783030053185
This open access book presents the first comprehensive overview of general methods in Automated Machine Learning (AutoML), collects descriptions of existing systems based on these methods, and discusses the first series of international challenges of AutoML systems. The recent success of commercial ML applications and the rapid growth of the field has created a high demand for off-the-shelf ML methods that can be used easily and without expert knowledge. However, many of the recent machine learning successes crucially rely on human experts, who manually select appropriate ML architectures (deep learning architectures or more traditional ML workflows) and their hyperparameters. To overcome this problem, the field of AutoML targets a progressive automation of machine learning, based on principles from optimization and machine learning itself. This book serves as a point of entry into this quickly-developing field for researchers and advanced students alike, as well as providing a reference for practitioners aiming to use AutoML in their work.
Author : Agoston E. Eiben,J.E. Smith
Publisher : Springer Science & Business Media
Page : 307 pages
File Size : 55,9 Mb
Release : 2013-03-14
Category : Computers
ISBN : 9783662050941
The first complete overview of evolutionary computing, the collective name for a range of problem-solving techniques based on principles of biological evolution, such as natural selection and genetic inheritance. The text is aimed directly at lecturers and graduate and undergraduate students. It is also meant for those who wish to apply evolutionary computing to a particular problem or within a given application area. The book contains quick-reference information on the current state-of-the-art in a wide range of related topics, so it is of interest not just to evolutionary computing specialists but to researchers working in other fields.
Author : Christian Moewes,Andreas Nürnberger
Publisher : Springer
Page : 306 pages
File Size : 43,9 Mb
Release : 2012-08-23
Category : Technology & Engineering
ISBN : 9783642323782
Complex systems and their phenomena are ubiquitous as they can be found in biology, finance, the humanities, management sciences, medicine, physics and similar fields. For many problems in these fields, there are no conventional ways to mathematically or analytically solve them completely at low cost. On the other hand, nature already solved many optimization problems efficiently. Computational intelligence attempts to mimic nature-inspired problem-solving strategies and methods. These strategies can be used to study, model and analyze complex systems such that it becomes feasible to handle them. Key areas of computational intelligence are artificial neural networks, evolutionary computation and fuzzy systems. As only a few researchers in that field, Rudolf Kruse has contributed in many important ways to the understanding, modeling and application of computational intelligence methods. On occasion of his 60th birthday, a collection of original papers of leading researchers in the field of computational intelligence has been collected in this volume.