Memetic Algorithms (MAs) are computational intelligence structures combining multiple and various operators in order to address optimization problems. The combination and interaction amongst operator
This book describes models and algorithms for complex scheduling problems. It presents key algorithms in detail and includes examples. This second revised edition includes new material, in particular,
Memetic Algorithms (MAs) are computational intelligence structures combining multiple and various operators in order to address optimization problems.? The combination and interaction amongst operator
This book describes models and algorithms for complex scheduling problems. It presents key algorithms in detail and includes examples. This second revised edition includes new material, in particular,
Today most computer scientists believe that NP-hard problems cannot be solved by polynomial-time algorithms. From the polynomial-time perspective, all NP-complete problems are equivalent but their exp
Bioinformatics involves specialized application of computer technology to investigative and conceptual problems in biology and medicine; neuroinformatics (NI) is the practice of bioinformatics in the
Graph Theory, Combinatorics and Algorithms: Interdisciplinary Applications focuses on discrete mathematics and combinatorial algorithms interacting with real world problems in computer science, operat
The robust capability of Evolutionary Algorithms (EAs) to find solutions to difficult problems has permitted them to become the optimization and search techniques of choice for many practical static p
This book presents a thorough development of the modern theory of stochastic approximation or recursive stochastic algorithms for both constrained and unconstrained problems. This second edition is a
This well-written book contains the analytical tools, concepts, and viewpoints needed for modern applied mathematics. It treats various practical methods for solving problems such as differential equa
This book is aimed at undergraduate and graduate students in applied mathematics or computer science, as a tool for solving real-world design problems. The present work covers fundamentals in mul
This book offers a detailed overview of translational bioinformatics together with real-case applications. Translational bioinformatics integrates the areas of basic bioinformatics, clinical informati
This book presents the state of the art in reinforcement learning applied to robotics both in terms of novel algorithms and applications. It discusses recent approaches that allow robots to learn moto
This unique textbook/reference presents unified coverage of bioinformatics topics relating to both biological sequences and biological networks, providing an in-depth analysis of cutting-edge distribu
The book mainly introduces the bioinformatics resources and tools available for the study of allergenicity. Allergy symptoms affect more than 25% of the population in industrialized countries. Biotech
Evolutionary algorithms and metaheuristics play an increasing key role in the optimum design in many applied sciences and engineering fields. This book focus on civil and structural engineering and co
Machine Learning Projects for .NET Developers shows you how to build smarter .NET applications that learn from data, using simple algorithms and techniques that can be applied to a wide range of real-
This monograph addresses several critical problems to the operations of shipping lines and ports, and provides algorithms and mathematical models for use by shipping lines and port authorities for dec
“Bioinformatics of Human Proteomics” discusses the development of methods, techniques and applications in the field of protein bioinformatics, an important direction in bioinformatics. It collects con
A common approach to understanding the functional repertoire of a genome is through functional genomics. With systems biology burgeoning, bioinformatics has grown to a larger extent for plant genomes
This Brief covers broad areas of Applied Biology specifically into the domains of Biotechnology/Biomedicine and Forensic Science. Chapters included here would also explain the role of bioinformatics i
This book presents the state of the art in reinforcement learning applied to robotics both in terms of novel algorithms and applications. It discusses recent approaches that allow robots to learn moto
Bioinformatics brings computational methods to the analysis and processing of genomic data. Bioinformatics: Databases and Systems focuses on the issues of system building and data curation that domina
“Bioinformatics of Human Proteomics” discusses the development of methods, techniques and applications in the field of protein bioinformatics, an important direction in bioinformatics. It collects con
Stochastic Recursive Algorithms for Optimization presents algorithms for constrained and unconstrained optimization and for reinforcement learning. Efficient perturbation approaches form a thread unif
This book offers a basic introduction to genetic algorithms. It provides a detailed explanation of genetic algorithm concepts and examines numerous genetic algorithm optimization problems. In addition
Combining control theory and modeling, this textbook introduces and builds on methods for simulating and tackling concrete problems in a variety of applied sciences. Emphasizing "learning by doing," t
New perspective technologies of genetic search and evolution simulation represent the kernel of this book. The authors wanted to show how these technologies are used for practical problems solution. T
Nature-Inspired Algorithms?have been?gaining much popularity in recent years due to the fact that many real-world optimisation problems have become increasingly large, complex and dynamic. The size an
Practical Problems in VLSI Physical Design Automation contains problems and solutions related to various well-known algorithms used in VLSI physical design automation. Dr. Lim believes that the best w
What is this book good for? Imagine you are a computer scientist working in the bioinformatics area. P- bably you will be a member of a highly interdisciplinary team consisting of biologists, chemists
This book details approximate solutions to common fixed point problems and convex feasibility problems in the presence of perturbations. Convex feasibility problems search for a common point of a fini
This book combines a solid theoretical background in linear algebra with practical algorithms for numerical solution of linear algebra problems. Developed from a number of courses taught repeatedly by
This book provides a general theoretical background for constructing the recursive Bayesian estimation algorithms for mixture models. It collects the recursive algorithms for estimating dynamic mixtur
This book presents efficient metaheuristic algorithms for optimal design of structures. Many of these algorithms are developed by the author and his colleagues, consisting of Democratic Particle Swarm
This book covers aspects of human re-identification problems related to computer vision and machine learning. Working from a practical perspective, it introduces novel algorithms and designs for human
The goal in putting together this unique compilation was to present the current status of the solutions to some of the most essential open problems in pure and applied mathematics. Emphasis is also gi
Now in its third edition and supplemented with more online material, this book aims to make the "new" information-based (rather than gene-based) bioinformatics intelligible both to the "
This book introduces readers to classical population genetics and the ways in which it can be applied to practical problems, including testing for natural selection, genetic drift, genetic differentia
This book provides a basic introduction to reduced basis (RB) methods for problems involving the repeated solution of partial differential equations (PDEs) arising from engineering and applied science
