Modeling

Cubre los aspectos más importantes acerca de las Bases de Datos. En la sección 3.3 los alumnos suelen encontrar los conceptos un poco ambiguos. Lo mismo sucede con al exposición de la notación del DER, donde a veces utiliza extensiones de la notación antes de presentarla. A pesar de todo puede decirse que, en general, es muy claro en su exposición y agradable su lectura.

Here's a self-contained introduction to connectionist modeling. Easy to read and straight-forward, this text provides software and excercises aimed at stepping a novice through the basics of connectionism. Designed to accompany Rethinking Innateness (1996), these examples provide a glimpse into the world of cognitive modeling. The examples can, at times, be frustrating and the text is in need of more debugging hints; yet, the simulations are rewarding and thought-provoking. While those already familiar with connectionism will find the excercises too basic, those curious about connectionism will find the book a great place to start and one that doesn't bog the reader down with technical jargon. It is accessible, enjoyable, and written by two key players in connectionism: Kim Plunkett and Jeff Elman. Well worth reading, but only if the reader is willing to work through the basic simulations and answer the excercises along the way.

Ik zou zo graag dit boek eens lezen en ik denk dat als ik het zou lezen ik het boek toch wel een volle 4 sterren zou geven. Indien jullie het boek ook niet gelezen hebben en het ook nog 4 sterren geven wil ik daar graag met jullie eens over praten. Voor interessantere praat wil ik jullie steeds doorverwijzen naar de site van het peulengaleis.

The problem with almost all data structures books is - when is someone going to write one which is the ultimate desk reference - nothing is left for the reader to derive. This book falls short also in that aspect. It covers all the necessary topics. Strong, but academic.

Many good books have recently been published on fuzzy rule-based systems for control, but few authors have dealt with open systems. The book by Bardossy and Duckstein, which does an excellent job of introducing fuzzy rule-based modeling of open systems, may stimulate more research in this area. Indeed, the realistic examples presented in the book are very convincing. More emphasis could however have been put on the complex processes of selecting input variables and defining fuzzy rules. The discussion, in the introduction, of the differences between fuzzy numbers and probability distributions is certainly too short to convince a statistician of the usefulness of fuzzy sets for uncertainty modeling. However, if the book does not contribute to this philosophical debate, it certainly does a good job of showing the practical value of fuzzy models for nonparametric modeling of open systems.

...well not really, but this book sparked the scientific interest in it. The concepts surrounding surface analysis date back to late 1970s and were championed by Dana Tomlin with his PhD dissertation in 1983, which was later published as this book. Here, Tomlin introduces map algebra operators based on how a computer algorithm obtains data values for processing raster surfaces. He identifies three fundamental classes: local, focal and zonal functions.
Tomlin is a must to any academic student of GIS, since much or nearly all work on raster GIS springs off from Tomlin's work. The illustrations clearly show that this is an old book, but the knowlegde still remains as brilliant today as it was then.
This is a book you want to own, simply because it is very sought after and constantly unavailable from your university library.

This book provides a collection of papers that were presented at a symposium of reservoir modeling in the 1990 at a meeting of the International Association of Sedimentologists. The papers discuss diverse aspects of geological reservoir modeling and methods for modeling reservoirs using information derived from analogous outcropping formations. Naturally, most of the papers are biased towards sedimentological aspects of reservoir modeling, although one paper considers that role of sealing

faults in compartmentalizing reservoirs. The scope of the papers is wide ranging: from the use of sedimentary dip profiles to orientate sand bodies, through process-based modeling of alluvial architecture to object-based computer modeling. The first paper in the volume is a review of the state-of-the-art in 3D geological reservoir modeling by the editors. This paper sets the context for the remainder of the papers in the volume and has an exhaustive bibliography. Aspects of marine and non-marine sequence stratigraphy are discussed by several papers. The principle contribution of the volume is to highlight the way in which quantified geological information is derived and applied to 3D computer modeling of subsurface reservoirs. The volume should be of interest to both academic geologists interested in 3D modeling and industry geoscientists interested in modeling hydrocarbon reservoirs. Whilst recent advances in geostatistical modeling have significantly the methodology of computer modeling beyond the approaches discussed, the fundamental principles and data sources remain unchanged. Consequently this book still provides a useful introduction to the subject and a valuable reference source.

The book emphasis is on different drug design techniques, specifically; The molecular modeling perspective in drug design, Molecular graphics and modeling, Molecular modeling of small molecules, Computer-assisted new lead design, Experimental techniques and data banks, Computer-assisted drug discovery, and Modeling drug-receptor interactions. The book covers in depth the docking of small molecules with protein receptors. Also the book surveys the molecular modeling packages currently used, their usage, strengths and weaknesses. The two main weaknesses of this book are (1) few illustrative figrues, (2) subjects overlapping (due to the fact that a group of authors contributed in writing this book). The book is really a guide book on molecular modeling and drug design as the title suggested.

This book gave you a lot of information (hints and tips). Although the book is very basic there is still a lot to learn, and most of the time simple solutions for big problems (in the eyes of the modeler).Those simple solutions are easy to follow, with great results. After some practical sessions you never forget what you learned.

An excellent book outlining hierarchical linear modeling. When used in conjuction with available software, it allows for self-teaching of the technique. The book is strictly for those with at least minimal multivariate training, and full understanding of OLS and ML methods.