scispace - formally typeset
Search or ask a question
Topic

Soft computing

About: Soft computing is a research topic. Over the lifetime, 6710 publications have been published within this topic receiving 118508 citations.


Papers
More filters
Journal ArticleDOI
TL;DR: In this brief review, the recent progress in two niche applications are presented: neural network accelerators and numerical computing units, mainly focusing on the advances in hardware demonstrations.
Abstract: Memristors are now becoming a prominent candidate to serve as the building blocks of non-von Neumann in-memory computing architectures. By mapping analog numerical matrices into memristor crossbar arrays, efficient multiply accumulate operations can be performed in a massively parallel fashion using the physics mechanisms of Ohm’s law and Kirchhoff’s law. In this brief review, we present the recent progress in two niche applications: neural network accelerators and numerical computing units, mainly focusing on the advances in hardware demonstrations. The former one is regarded as soft computing since it can tolerant some degree of the device and array imperfections. The acceleration of multiple layer perceptrons, convolutional neural networks, generative adversarial networks, and long short-term memory neural networks are described. The latter one is hard computing because the solving of numerical problems requires high-precision devices. Several breakthroughs in memristive equation solvers with improved computation accuracies are highlighted. Besides, other nonvolatile devices with the capability of analog computing are also briefly introduced. Finally, we conclude the review with discussions on the challenges and opportunities for future research toward realizing memristive analog computing machines.

31 citations

Journal ArticleDOI
01 Jan 2013
TL;DR: It is shown that the collection of all fuzzy soft sets, equipped with this new order, forms a complete Heyting algebra, and the representation theorem of fuzzysoft sets with respect to the soft information order is obtained.
Abstract: In this paper, a new order relation on fuzzy soft sets, called soft information order, is introduced and its application to decision-making is investigated. It is shown that the collection of all fuzzy soft sets (over a given universe set), equipped with this new order, forms a complete Heyting algebra. The representation theorem of fuzzy soft sets with respect to the soft information order is also obtained. We initiate the concepts of soft set satisfaction problems and their solutions. An algorithm is presented to solve such decision-making problems.

31 citations

Journal ArticleDOI
TL;DR: Due to the large increase in computation power, new methods for modelling glass dissolution are becoming available and these methods, which can be viewed as complementary to traditional methods, are more empirically based and can be useful for modelling systems that are ill defined or not completely understood yet.

31 citations

BookDOI
01 Jan 2000
TL;DR: This work focuses on the application of Neural Networks in Reactor Diagnosis and Monotoring, and the design of Reactor Controller Design Using Genetic Algorithms with Simulated Annealing in Nuclear Power Plants.
Abstract: D. Ruan: Preface.- R. Hampel, W. Kastner, A. Fenske, B. Vandreier, S. Schefter: Analysis of Selected Structures for Model-Based Measuring Methods Using Fuzzy Logic.- B. Soo Moon: A Set of Fuzzy Systems to Automate the Manual Procedures for Reactor Power Level Changes.- M.S. Fodil, F. Guely, P. Siarry, J-L. Tyran: A Fuzzy Controller for the Real Time Supervision of Nuclear Power Reactors.- D. Ruan, X.Z. Li, G. Van den Eynde: Adaptive Fuzzy Control for a Simulation of Hydraulic Analogy of a Nuclear Reactor.- J.S. Benitez-Read, D. Velez-Diaz: Controlling Neutron Power of a TRIGA Mark III Research Nuclear Reactor with Fuzzy Adaptation of the Set of Output Membership Functions.- I. Petruzela: NPP Operator Support in Decision Making - Diagnostics of the Operation Failures Using Fuzzy Logic.- J.Y. Yang, K.J. Lee: Optimal Operation Planning of Radioactive Waste Processing System by Fuzzy Theory.- P. Kunsch, A. Fiordaliso, P. Fortemps: A Fuzzy Inference System for the Economic Calculus in Radioactive Waste Management.- M.G. Na: Neuro-Fuzzy Control Applications in Pressurized Water Reactors.- D. Roverso: Neural and Fuzzy Transient Classification Systems: General Techniques and Applications in Nuclear Power Plants.- R. Govil: Neural Networks in Signal Processing.- N.S. Garis, P. Linden: Application of Neural Networks in Reactor Diagnosis and Monotoring.- J.W. Hines, A.V. Gribok, I. Attieh, R.E. Uhrig: Regularization Methods for Inferential Sensing in Nuclear Power Plants.- C.M.N.A. Pereira, R. Schirru, A.S. Martinez: Genetic Algorithms Applied to Nuclear Reactor Design Optimization.- R. Schirru, C.M.N.A. Pereira, A.S. Martinez: Genetic Algorithms Applied to the Nuclear Power Plant Operation.- K. Erkan, E. Butun: Reactor Controller Design Using Genetic Algorithms with Simulated Annealing.- Y.-S. Hu, M. Modarres: Logic-Based Hierarchies for Modeling Behavior of Complex Dynamic Systems with Applications.- A. Zardecki: Continued Fractions in Time Series Forecasting.- A.G. Huizing , F.C.A. Groen: A Possibilistic Approach to Target Classification.- E. Nissan, A. Galperin, J. Zhao, B. Knight, A. Soper: From FUELCON to FUELGEN: Tools for Fuel Reload Pattern Design.- J. Reifman, T.Y.C. Wei: Diagnosis of Unanticipated Plant Component Faults in a Portable Expert System.

31 citations

Journal ArticleDOI
TL;DR: A sensor validation strategy based on soft computing techniques to isolate and classify some faults occurring in the measurement system of a Tokamak fusion plant is described, and a great improvement was achieved, in terms of both fault detection and classification capabilities, and the degree of automation achieved.
Abstract: A sensor validation strategy based on soft computing techniques to isolate and classify some faults occurring in the measurement system of a Tokamak fusion plant is described. Particular attention is focused on the system used to measure vertical stress in the mechanical structure of a Tokamak nuclear fusion plant during fusion experiments. The strategy adopted is based on a modular structure comprising two stages. The first stage consists of a neural network which acts as a symptom model able to estimate directly some suitable features of the expected sensor responses, thus allowing the most frequently occurring sensor faults to be isolated. The second stage consists of a fault classifier implemented via a fuzzy inference system, in order to exploit the knowledge of the experts. The proposed strategy was validated at the Joint European Torus (JET), on several experiments. A comparison was made with both traditional sensor monitoring techniques and validation performed manually by experts. A great improvement was achieved, in terms of both fault detection and classification capabilities, and the degree of automation achieved.

31 citations


Network Information
Related Topics (5)
Fuzzy logic
151.2K papers, 2.3M citations
90% related
Artificial neural network
207K papers, 4.5M citations
86% related
Optimization problem
96.4K papers, 2.1M citations
84% related
Feature extraction
111.8K papers, 2.1M citations
82% related
Cluster analysis
146.5K papers, 2.9M citations
81% related
Performance
Metrics
No. of papers in the topic in previous years
YearPapers
2023159
2022270
2021319
2020332
2019313
2018348