Author: K. Malanowski
Publisher: Springer
ISBN: 9780387349220
Category: Computers
Page: 387
View: 891
Infinite Dimensional Optimization and Control Theory
J.-P. Raymond [ 1996 ] Optimal control problems for semilinear parabolic equations with pointwise state constraints , Modelling and Optimization of Distributed Parameter Systems : Applications to Engineering , Chapman & Hall ( 1996 ) ...
Author: Hector O. Fattorini
Publisher: Cambridge University Press
ISBN: 0521451256
Category: Mathematics
Page: 798
View: 193
Treats optimal problems for systems described by ODEs and PDEs, using an approach that unifies finite and infinite dimensional nonlinear programming.Smart Structures
Requirements and Potential Applications in Mechanical and Civil Engineering Jan Holnicki-Szulc, José Rodellar ... in : Modelling and Optimization of Distributed Parameter Systems : Applications to Engineering , ed . by K. Malanowski ...
Author: Jan Holnicki-Szulc
Publisher: Springer Science & Business Media
ISBN: 0792356136
Category: Science
Page: 391
View: 160
Smart (intelligent) structures have been the focus of a great deal of recent research interest. In this book, leading researchers report the state of the art and discuss new ideas, results and trends in 43 contributions, covering fundamental research issues, the role of intelligent monitoring in structural identification and damage assessment, the potential of automatic control systems in achieving a desired structural behaviour, and a number of practical issues in the analysis and design of smart structures in mechanical and civil engineering applications. Audience: A multidisciplinary reference for materials scientists and engineers in such areas as mechanical, civil, aeronautical, electrical, control, and computer engineering.Hyperbolic Problems
[ 3 ] S. Kosiński , Evolution law for shock strength in simple elastic structures , in : K. Malanowski , M. Peszyńska , and Z. Nahorski , Eds . , Modelling and Optimization of Distributed Parameter Systems , Application to Engineering ...
Author: Michael Fey
Publisher: Springer Science & Business Media
ISBN: 3764360801
Category: Mathematics
Page: 1011
View: 816
Discretization Methods and Iterative Solvers Based on Domain Decomposition
Additive Schwarz methods for elliptic mortar finite element problems. In K. Malanowski, Z. Nahorski, and M. Peszynska, editors, Modelling and optimization of distributed parameter systems. Applications to engineering, pages 31–50.
Author: Barbara I. Wohlmuth
Publisher: Springer Science & Business Media
ISBN: 9783642567674
Category: Mathematics
Page: 199
View: 381
Domain decomposition methods provide powerful and flexible tools for the numerical approximation of partial differential equations arising in the modeling of many interesting applications in science and engineering. This book deals with discretization techniques on non-matching triangulations and iterative solvers with particular emphasis on mortar finite elements, Schwarz methods and multigrid techniques. New results on non-standard situations as mortar methods based on dual basis functions and vector field discretizations are analyzed and illustrated by numerical results. The role of trace theorems, harmonic extensions, dual norms and weak interface conditions is emphasized. Although the original idea was used successfully more than a hundred years ago, these methods are relatively new for the numerical approximation. The possibilites of high performance computations and the interest in large- scale problems have led to an increased research activity.Artificial Intelligence Methodology Systems and Applications
Pietil, S., Koivo, H.N.: Centralized and Decentralized Neural Network Models for Distributed Parameter Systems. In: Proc. of the Symposium ... IMACS Multi-conference on Computational Engineering in Systems Applications, pp. 1043–1048.
Author: Daniel Dochev
Publisher: Springer Science & Business Media
ISBN: 9783540857754
Category: Computers
Page: 416
View: 800
The 13th Conference on Arti?cial Intelligence: Methodology, Systems, App- cations (AIMSA 2008) was held in Varna, Bulgaria, on September 4–6, 2008. The AIMSA conference series has provideda biennial forum for the presentation of arti?cial intelligence research and development since 1984. The conference covered the full range of topics in arti?cial intelligence and related disciplines and provided an ideal forum for international scienti?c exchange between C- tral/Eastern Europe and the rest of the world. For AIMSA 2008,wedecided to placespecial emphasisonthe worksonth- ries, experimentations, applications, and case studies that demonstrate in pr- tice the added value and the impact ofAI science,methodologiesand techniques for the market,society,and culture. We believe that this vision of “[email protected]” truly re?ects the original intention of AIMSA, a conference dedicated to ar- ?cial intelligence in its entirety but with a special emphasis on “methodology, systems, and applications”, as explicitly stated in its name. According to this vision, we have also paid special attention to works that “cross the boundaries of AI”, i. e. , works that demonstrate the in?uence of AI on di?erent ?elds of research and di?erent scienti?c communities, such as software engineering, data bases, distributed systems, information systems, information retrieval, etc. Both of these aspects were covered by the papers that were submitted and by those that were accepted for publication. A total of 109 papers were submitted to the conference, and the program committee accepted 30 full papers and 10 posters.Kokuritsu Kokkai Toshokan shoz kagaku gijutsu kankei bun kaigiroku mokuroku
Systems Modelling and Optimization Proceedings of the 18th IFIP TC7 Conference
The papers offered in this volume were selected from among the 250 plenary, invited, and contributed works presented at the conference.
Author: Michael P. Polis
Publisher: CRC Press
ISBN: 0849306078
Category: Mathematics
Page: 528
View: 596
Top researchers in optimization and control from around the world gathered in Detroit for the 18th annual IFIP TC7 Conference on Systems Modelling and Optimization held in July 1997. The papers offered in this volume were selected from among the 250 plenary, invited, and contributed works presented at the conference. The editors chose these papers to represent the myriad and diverse range of topics within the field -in theory and applications-and to disseminate important new results. The editors have organized the book into seven sections: Distributed Parameter Systems Modelling Optimal Control and Nonsmoooth Analysis Automotive Optimization and Operations Research Applications · Reliability Each section contains important advances in theoretical development of optimization and control, new results, and discussions of applications. Treatment of numerous and wide- ranging applications-from turbulent flows, European option pricing, and storage location, to wear processes, passive fire protection, and robotics-make this resource important for academic and industrial researchers working in a variety of areas in systems engineering and applied mathematics.Applied Mechanics Reviews
Applications to practical engineering planning are promising but seem to be still in the preparation phase . ... A. P. , and Chaudhuri , S.P. , Gradient and quasilinearization computational techniques for distributed parameter systems ...
Author:
Publisher:
ISBN: UCAL:C2682430
Category: Mechanics, Applied
Page:
View: 673
DNA Computing Based Genetic Algorithm
Applications in Industrial Process Modeling and Control Jili Tao, Ridong Zhang, Yong Zhu ... Decoupled ARX and RBF neural network modeling using PCA and GA optimization for nonlinear distributed parameter systems.
Author: Jili Tao
Publisher: Springer Nature
ISBN: 9789811554032
Category: Computers
Page: 274
View: 848
This book focuses on the implementation, evaluation and application of DNA/RNA-based genetic algorithms in connection with neural network modeling, fuzzy control, the Q-learning algorithm and CNN deep learning classifier. It presents several DNA/RNA-based genetic algorithms and their modifications, which are tested using benchmarks, as well as detailed information on the implementation steps and program code. In addition to single-objective optimization, here genetic algorithms are also used to solve multi-objective optimization for neural network modeling, fuzzy control, model predictive control and PID control. In closing, new topics such as Q-learning and CNN are introduced. The book offers a valuable reference guide for researchers and designers in system modeling and control, and for senior undergraduate and graduate students at colleges and universities.