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Numerical Methods Using Java : For Data Science, Analysis, and Engineering
Covers a wide range of topics, including chapters on linear algebra, root finding, curve fitting, differentiation and integration, solving differential equations, random numbers and simulation, a whole suite of unconstrained and constrained optimization algorithms, statistics, regression and time series analysis. The mathematical concepts behind the algorithms are clearly explained, with plenty of code examples and illustrations to help even beginners get started. You will: Program in Java using a high-performance numerical library / Learn the mathematics for a wide range of numerical computing algorithms / Convert ideas and equations into code / Put together algorithms/ and classes to build your own engineering solution / Build solvers for industrial optimization problems / Do data analysis using basic and advanced statistics
Innovations in Machine Learning : Theory and Applications
Machine learning is currently one of the most rapidly growing areas of research in computer science. In compiling this volume we have brought together contributions from some of the most prestigious researchers in this field. This book covers the three main learning systems; symbolic learning, neural networks and genetic algorithms as well as providing a tutorial on learning casual influences. Each of the nine chapters is self-contained. Both theoreticians and application scientists/engineers in the broad area of artificial intelligence will find this volume valuable. It also provides a useful sourcebook for Postgraduate since it shows the direction of current research.
Human Ear Recognition by Computer
Human Ear Recognition by Computer is the first book on the automatic recognition of human ears. It presents an entire range of computational algorithms for recognition of humans by their ears. These algorithms have been tested and validated on the largest databases that are available today,This state-of-the-art research reference explores all aspects of 3D ear recognition, including representation, detection, recognition, indexing and performance prediction. It has been written for a professional audience of both researchers and practitioners within industry, and is also ideal as an informative text for graduate students in computer science and engineering.
High performance computing for drug discovery and biomedicine
Explores the application of high-performance computing (HPC) technologies to computational drug discovery (CDD) and biomedicine. Collects CDD approaches that, together with HPC, can revolutionize and automate drug discovery process, such as knowledge graphs, natural language processing (NLP), Bayesian optimization, automated virtual screening platforms, alchemical free energy workflows, fragment-molecular orbitals (FMO), HPC-adapted molecular dynamic simulation (MD-HPC), and the potential of cloud computing for drug discovery. And delves into computational algorithms and workflows for biomedicine, featuring an HPC framework to assess drug-induced arrhythmic risk, digital patient applications relevant to the clinic, virtual human simulations, cellular and whole-body blood flow modeling for stroke treatments, prediction of the femoral bone strength from CT data, and many more subjects.
Fuzzy systems and knowledge discovery ; Vol. 3614 ; 2nd International Conference, FSKD 2005, Changsha, China, August 27-29, 2005, Proceedings, Part II
This book and its sister volume, LNAI 3613 and 3614, constitute the proce- ings of the Second International Conference on Fuzzy Systems and Knowledge Discovery (FSKD 2005), jointly held with the First International Conference on Natural Computation (ICNC 2005, LNCS 3610, 3611, and 3612) from - gust 27–29, 2005 in Changsha, Hunan, China. FSKD 2005 successfully attracted 1249 submissions from 32 countries/regions (the joint ICNC-FSKD 2005 received 3136 submissions). After rigorous reviews, 333 high-quality papers, i. e. , 206 long papers and 127 short papers, were included in the FSKD 2005 proceedings, r- resenting an acceptance rate of 26. 7%. The ICNC-FSKD 2005 conference featured the most up-to-date research - sults in computational algorithms inspired from nature, including biological, e- logical, and physical systems. It is an exciting and emerging interdisciplinary area in which a wide range of techniques and methods are being studied for dealing with large, complex, and dynamic problems. The joint conferences also promoted cross-fertilization over these exciting and yet closely-related areas, which had a signi?cant impact on the advancement of these important technologies. Speci?c areas included computation with words, fuzzy computation, granular com- tation, neural computation, quantum computation, evolutionary computation, DNA computation, chemical computation, information processing in cells and tissues, molecular computation, arti?cial life, swarm intelligence, ants colony, arti?cial immune systems, etc. , with innovative applications to knowledge d- covery, ?nance, operations research, and more.
Fuzzy systems and knowledge discovery ; Vol. 3613 ; 2nd International Conference, FSKD 2005, Changsha, China, August 27-29, 2005, Proceedings, Part I
This book and its sister volume, LNAI 3613 and 3614, constitute the proce- ings of the Second International Conference on Fuzzy Systems and Knowledge Discovery (FSKD 2005), jointly held with the First International Conference on Natural Computation (ICNC 2005, LNCS 3610, 3611, and 3612) from - gust 27–29, 2005 in Changsha, Hunan, China. FSKD 2005 successfully attracted 1249 submissions from 32 countries/regions (the joint ICNC-FSKD 2005 received 3136 submissions). After rigorous reviews, 333 high-quality papers, i. e. , 206 long papers and 127 short papers, were included in the FSKD 2005 proceedings, r- resenting an acceptance rate of 26. 7%. The ICNC-FSKD 2005 conference featured the most up-to-date research - sults in computational algorithms inspired from nature, including biological, e- logical, and physical systems. It is an exciting and emerging interdisciplinary area in which a wide range of techniques and methods are being studied for dealing with large, complex, and dynamic problems. The joint conferences also promoted cross-fertilization over these exciting and yet closely-related areas, which had a signi?cant impact on the advancement of these important technologies. Speci?c areas included computation with words, fuzzy computation, granular com- tation, neural computation, quantum computation, evolutionary computation, DNA computation, chemical computation, information processing in cells and tissues, molecular computation, arti?cial life, swarm intelligence, ants colony, arti?cial immune systems, etc. , with innovative applications to knowledge d- covery, ?nance, operations research, and more.
Discrete-Time Markov Chains : Two-Time-Scale Methods and Applications
The motivation stems from existing and emerging applications in optimization and control of complex hybrid Markovian systems in manufacturing, wireless communication, and financial engineering. Much effort in this book is devoted to designing system models arising from these applications, analyzing them via analytic and probabilistic techniques, and developing feasible computational algorithms so as to reduce the inherent complexity. This book presents results including asymptotic expansions of probability vectors, structural properties of occupation measures, exponential bounds, aggregation and decomposition and associated limit processes, and interface of discrete-time and continuous-time systems. One of the salient features is that it contains a diverse range of applications on filtering, estimation, control, optimization, and Markov decision processes, and financial engineering.
Control Systems Theory and Applications for Linear Repetitive Processes
After motivating examples, this monograph gives substantial new results on the analysis and control of linear repetitive processes. These include further applications of the abstract model based stability theory which, in particular, shows the critical importance to the dynamics developed of the structure of the initial conditions at the start of each new pass, the development of stability tests and performance bounds in terms of so-called 1D and 2D Lyapunov equations. It presents the development of a major bank of results on the structure and design of control laws, including the case when there is uncertainty in the process model description, together with numerically reliable computational algorithms. Finally, the application of some of these results in the area of iterative learning control is treated --- including experimental results from a chain conveyor system and a gantry robot system.
Computational earthquake physics ; Part II
Exciting developments in earthquake science have benefited from new observations, improved computational technologies, and improved modeling capabilities. Designing realistic supercomputer simulation models for the complete earthquake generation process is a grand scientific challenge due to the complexity of phenomena and range of scales involved from microscopic to global. The present volume - Part II - incorporates computational environment and algorithms, data assimilation and understanding, model applications and iSERVO. Topics covered range from iSERVO and QuakeSim: implementing the international solid earth research virtual observatory by integrating computational grid and geographical information web services; LURR (Load-Unload Response Ratio) described in six papers involving this promising earthquake forecasting model; pattern informatics and phase dynamics and their applications, which was also a highlight in the Workshop; computational algorithms, including continuum damage models and visualization and analysis of geophysical datasets; evolution of mantle material; the state vector approach; and assimilation of data such as geodetic data, GPS data, and seismicity and laboratory experimental data.
Advances in natural computation ; Vol. 3610 ; 1st International conference, ICNC 2005, Changsha, China, August 27-29, 2005, Proceedings, Part I
Featured the most up-to-date research results in computational algorithms inspired from nature, including biological, ecological, andphysical systems. It is an exciting and emerging interdisciplinary area in which a wide range of techniques and methods are being studied for dealing with large, complex, and dynamic problems. The joint conferences also promoted cross-fertilization over these exciting and yet closely-related areas, which had a sig-nificant impact on the advancement of these important technologies. Specificareas included neural computation, quantum computation, evolutionary com-putation, DNA computation, chemical computation, information processing incells and tissues, molecular computation, computation with words, fuzzy com-putation, granular computation, artificial life, swarm intelligence, ants colonies
