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Introduction to Parallel Algorithms

is on the application of the PRAM (parallel random access machine) model of parallel computation, with all its variants, to algorithm analysis;

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Parallel Random Search Algorithm

Random search methods are implemented to solve the wide variety of the large-scale discrete optimization problems when the implementation;

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On the Influence of Non-Perfect Randomness on Probabilistic Algorithms

results are presented that describe implications of using non-perfect random numbers with probabilistic algorithms. In the first part several;

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MPPT for Photovoltaic Array under Partially Shaded Conditions

shaded conditions. Random Perturbation search method was one of the algorithms investigated. The method is based on perturbations of random but;

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Computing and Random Numbers

random numbers. It includes Implementation of Hardware-Accelerated Scalable Parallel Random Number Generators, True-Randomness and Pseudo;

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Cambridge International Series on Parallel Computation

for researchers. The first part is devoted to the Parallel Random Access Machine (P-RAM) model of parallel computation. The initial chapters;

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A Derivative-free Two Level Random Search Method for Unconstrained Optimization

presenting a two level derivative-free random search method for unconstrained optimization. It is assumed that the minimizing function is continuous;

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Optimization Models in Steganography Using Metaheuristics

and a Multi-Random Start Local Search optimization algorithm. One of the most important types of media used for steganography is the JPEG;

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Optimization Models in Steganography Using Metaheuristics

and a Multi-Random Start Local Search optimization algorithm. One of the most important types of media used for steganography is the JPEG;

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Robust and Constrained Optimization

various metaheuristic algorithms (including memetic, interval, and random search optimization methods) can be applied to solve different types;

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Parallel Algorithms

Focusing on algorithms for distributed-memory parallel architectures, Parallel Algorithms presents a rigorous yet accessible treatment;

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Parallel Algorithms

Focusing on algorithms for distributed-memory parallel architectures, Parallel Algorithms presents a rigorous yet accessible treatment;

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Image Reconstruction

Reconstruction 3.1 Fan-Beam Geometry and Point Spread Function 3.2 Parallel-Beam to Fan-Beam Algorithm Conversion 3.3 Short Scan 3.4 Mathematical;

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Evolutionary Multi-Criterion Optimization

techniques; hybrid approaches; stopping criteria; parallel EMO models; performance evaluation; test functions and benchmark problems; algorithm;

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Algorithms and Parallel Computing

There is a software gap between the hardware potential and the performance that can be attained using today's software parallel program;

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Travelling Salesman Problem(tsp)Optimization Through Genetic Algorithm

limited search space. Genetic Algorithm is also readily amenable to parallel implementation, which renders them usable in real-time. This book;

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Advances in Metaheuristic Algorithms for Optimal Design of Structures

problems. These consist of Partical Swarm Optimization, Big Band Big Crunch algorithm, Cuckoo Search Optimization, Imperialist Competitive;

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Advances in Metaheuristic Algorithms for Optimal Design of Structures

problems. These consist of Partical Swarm Optimization, Big Band Big Crunch algorithm, Cuckoo Search Optimization, Imperialist Competitive;

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Statistical Mechanics & Random Walks

algorithm for diffusion processes and application of random walks for the analysis of graphs, musical composition and language phylogeny.;

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Improved Scatter Search Algorithm for Predicting Protein Structures

In this book, I present an improved scatter search (SS) algorithm for predicting all-atoms protein structures using the CHARMM22 energy;

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Particle Swarm Optimisation: Classical and Quantum Perspectives

. The book presents the concepts of optimisation problems as well as random search methods for optimisation before discussing the principles;

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Particle Swarm Optimisation: Classical and Quantum Perspectives

book presents the concepts of optimisation problems as well as random search methods for optimisation before discussing the principles of the;

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DNA Algorithm for Integrated Process Planning and Scheduling Problem

) framework. Further, the inherently parallel search strategy and structured architecture used in DNA algorithm meets the implementation requirements;

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Introduction To Parallel Algorithms

Parallel algorithms Made Easy The complexity of today's applications coupled with the widespread use of parallel computing has made the;

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Graphical Models for Machine Learning and Digital Communication

learning, data compression, and channel coding. Using probabilistic structures such as Bayesian belief networks and Markov random fields, he;

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Parallel Programming

Parallel Programming talks about a type of computation parallel programming and the parallel algorithm designed by technique PCAM . It;

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Parallel Solution of Soil-Structure Interaction Problems

extensible parallel finite element analysis library was developed. Then this library was extended with algorithms that implement the parallel dynamic;

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