Global Optimization Methods In Geophysical Inversion

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Author: Mrinal K. Sen
Publisher: Cambridge University Press
ISBN: 1139619519
Size: 25.47 MB
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Global Optimization Methods In Geophysical Inversion by Mrinal K. Sen


Original Title: Global Optimization Methods In Geophysical Inversion

Providing an up-to-date overview of the most popular global optimization methods used in interpreting geophysical observations, this new edition includes a detailed description of the theoretical development underlying each method and a thorough explanation of the design, implementation and limitations of algorithms. New and expanded chapters provide details of recently developed methods, such as the neighborhood algorithm, particle swarm optimization, hybrid Monte Carlo and multi-chain MCMC methods. Other chapters include new examples of applications, from uncertainty in climate modeling to whole earth studies. Several different examples of geophysical inversion, including joint inversion of disparate geophysical datasets, are provided to help readers design algorithms for their own applications. This is an authoritative and valuable text for researchers and graduate students in geophysics, inverse theory and exploration geoscience, and an important resource for professionals working in engineering and petroleum exploration.

Experimental Acoustic Inversion Methods For Exploration Of The Shallow Water Environment

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Author: Andrea Caiti
Publisher: Springer Science & Business Media
ISBN: 9401141126
Size: 75.18 MB
Format: PDF, ePub
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Experimental Acoustic Inversion Methods For Exploration Of The Shallow Water Environment by Andrea Caiti


Original Title: Experimental Acoustic Inversion Methods For Exploration Of The Shallow Water Environment

In recent years, research on acoustic remote sensing of the ocean has evolved considerably, especially in studying complex physical and biological processes in shallow water environments. To review the state of the art, an international workshop was held at Carvoeiro, Portugal, in March 1999, bringing together leading international researchers in the field. In contrast to much of the recent theoretical work, emphasis was placed on the experimental validation of the techniques. This volume, based on presentations at this workshop, summarizes a range of diverse and innovative applications. The invited contributions explore the use of acoustics to measure bottom properties and morphology, as well as to probe buried objects within the sediment. Within the water column, sound is applied to imaging of oceanographic features such as currents and tides or monitoring of marine life. Another key theme is the use of sound to solve geometric inverse problems for precise tracking of undersea vehicles. Audience: This volume should be useful both to the novice seeking an introduction to the field and to advanced researchers interested in the latest developments in acoustic sensing of the ocean environment. The workshop was sponsored by the Fundação para a Ciêcia e a Tecnologia (Portuguese Foundation for Science and Technology).

Swarm Intelligence Based Optimization

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Author: Patrick Siarry
Publisher: Springer
ISBN: 3319129708
Size: 44.39 MB
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Swarm Intelligence Based Optimization by Patrick Siarry


Original Title: Swarm Intelligence Based Optimization

This book constitutes the thoroughly refereed post-conference proceedings of the 1st International Conference on Swarm Intelligence Based Optimization, ICSIBO 2014, held in Mulhouse, France, in May 2014. The 20 full papers presented were carefully reviewed and selected from 48 submissions. Topics of interest presented and discussed in the conference focuses on the theoretical progress of swarm intelligence metaheuristics and their applications in areas such as: theoretical advances of swarm intelligence metaheuristics, combinatorial, discrete, binary, constrained, multi-objective, multi-modal, dynamic, noisy, and large-scale optimization, artificial immune systems, particle swarms, ant colony, bacterial foraging, artificial bees, fireflies algorithm, hybridization of algorithms, parallel/distributed computing, machine learning, data mining, data clustering, decision making and multi-agent systems based on swarm intelligence principles, adaptation and applications of swarm intelligence principles to real world problems in various domains.

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