This book provides a unified framework that describes how genetic learning can be used to design pattern recognition and learning systems. It examines how a search technique, the genetic algorithm, can be used for pattern classification mainly through approximating decision boundaries. Coverage also demonstrates the effectiveness of the genetic classifiers vis-a-vis several widely used classifiers, including neural networks.
This book provides a unified framework that describes how genetic learning can be used to design pattern recognition and learning systems. It exami...
DNA computation has emerged in the last ten years as an exciting new - search ?eld at the intersection (and, some would say, frontiers) of computer science, biology, engineering, andmathematics.AlthoughanticipatedbyFe- man as long ago as the 1950s 59], the notion of performing computations at a molecular level was only realized in 1994, with Adleman's seminal work 3] on computing with DNA. Since then the ?eld has blossomed rapidly, with signi?cant theoretical and experimental results being reported regularly. Several books 120, 39] have described various aspects of DNA compu- tion, but...
DNA computation has emerged in the last ten years as an exciting new - search ?eld at the intersection (and, some would say, frontiers) of computer sc...
This book introduces some key problems in bioinformatics, discusses the models used to formally describe these problems, and analyzes the algorithmic approaches used to solve them. After introducing the basics of molecular biology and algorithmics, Part I explains string algorithms and alignments; Part II details the field of physical mapping and DNA sequencing; and Part III examines the application of algorithmics to the analysis of biological data. Exciting application examples include predicting the spatial structure of proteins, and computing haplotypes from genotype data. Figures,...
This book introduces some key problems in bioinformatics, discusses the models used to formally describe these problems, and analyzes the algorithm...
Many advances have recently been made in metaheuristic methods, from theory to applications. The editors, both leading experts in this field, have assembled a team of researchers to contribute 21 chapters organized into parts on simulated annealing, tabu search, ant colony algorithms, general purpose studies of evolutionary algorithms, applications of evolutionary algorithms, and metaheuristics.
Many advances have recently been made in metaheuristic methods, from theory to applications. The editors, both leading experts in this field, have ...
Swarm intelligence is a modern arti?cial intelligence discipline that is c- cerned with the design of multiagent systems with applications, e.g., in - timization and in robotics. The design paradigm for these systems is fun- mentally di?erent from more traditional approaches. Instead of a sophisticated controller that governs the global behavior of the system, the swarm intelligence principle is based on many unsophisticated entities that cooperate in order to exhibit a desired behavior. Inspiration for the design of these systems is taken from the collective behavior of social insects such...
Swarm intelligence is a modern arti?cial intelligence discipline that is c- cerned with the design of multiagent systems with applications, e.g., in -...
This text examines how multiobjective evolutionary algorithms and related techniques can be used to solve problems, particularly in the disciplines of science and engineering. Contributions by leading researchers show how the concept of multiobjective optimization can be used to reformulate and resolve problems in areas such as constrained optimization, co-evolution, classification, inverse modeling, and design.
This text examines how multiobjective evolutionary algorithms and related techniques can be used to solve problems, particularly in the disciplines...
Honey bee colonies demonstrate robust adaptive efficient agent-based communications and task allocations without centralized controls - desirable features in network design. This book introduces a multipath routing algorithm for packet-switched telecommunication networks based on techniques observed in bee colonies. The algorithm, BeeHive, is dynamic, simple, efficient, robust and flexible, and it represents an important step towards intelligent networks that optimally manage resources.
The author guides the reader in a survey of nature-inspired routing protocols and communication...
Honey bee colonies demonstrate robust adaptive efficient agent-based communications and task allocations without centralized controls - desirable f...
A fundamental understanding of algorithmic bioprocesses is key to learning how information processing occurs in nature at the cell level. The field is concerned with the interactions between computer science on the one hand and biology, chemistry, and DNA-oriented nanoscience on the other. In particular, this book offers a comprehensive overview of research into algorithmic self-assembly, RNA folding, the algorithmic foundations for biochemical reactions, and the algorithmic nature of developmental processes.
The editors of the book invited 36 chapters, written by the...
A fundamental understanding of algorithmic bioprocesses is key to learning how information processing occurs in nature at the cell level. The field...
Artificial neural networks are used to model systems that receive inputs and produce outputs. The relationships between the inputs and outputs and the representation parameters are critical issues in the design of related engineering systems, and sensitivity analysis concerns methods for analyzing these relationships. Perturbations of neural networks are caused by machine imprecision, and they can be simulated by embedding disturbances in the original inputs or connection weights, allowing us to study the characteristics of a function under small perturbations of its parameters.
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Artificial neural networks are used to model systems that receive inputs and produce outputs. The relationships between the inputs and outputs and ...
Theoretical tools and insights from discrete mathematics, theoretical computer science, and topology now play essential roles in our understanding of vital biomolecular processes. The related methods are now employed in various fields of mathematical biology as instruments to "zoom in" on processes at a molecular level. This book contains expository chapters on how contemporary models from discrete mathematics - in domains such as algebra, combinatorics, and graph and knot theories - can provide perspective on biomolecular problems ranging from data analysis, molecular and gene arrangements...
Theoretical tools and insights from discrete mathematics, theoretical computer science, and topology now play essential roles in our understanding of ...
