Supreme Command: Soldiers, Statesmen, and Leadership in Wartime

Average customer rating:

War is too important to be left to the generals

Fully-vetted argument; could have been expanded

Senior Military Leaders Must Read This Book

Scattered and loses focus

Square peg into round hole (or, stop after the 4 bios)

Supreme Command: Soldiers, Statesmen, and Leadership in Wartime
Eliot A. Cohen
Manufacturer: Anchor
ProductGroup: Book
Binding: Paperback

General | Military | History | Subjects | Books
Military Science | History | Subjects | Books
Leadership | Politics | Nonfiction | Subjects | Books
History of Technology | Technology | Science | Subjects | Books
Similar Items:

Military Misfortunes: The Anatomy of Failure in War

The Soldier and the State: The Theory and Politics of Civil-Military Relations (Belknap Press)

Supplying War: Logistics from Wallenstein to Patton

Dereliction of Duty: Johnson, McNamara, the Joint Chiefs of Staff, and the Lies That Led to Vietnam

American Generalship: Character Is Everything: The Art of Command

ASIN: 1400034043
Release Date: 2003-09-09

Book Description

The orthodoxy regarding the relationship between politicians and military leaders in wartime democracies contends that politicians should declare a military operation's objectives and then step aside and leave the business of war to the military. In this timely and controversial examination of civilian-military relations in wartime democracies, Eliot A. Cohen chips away at this time-honored belief with case studies of statesmen who dared to prod, provoke, and even defy their military officers to great effect.

Using the leadership of Abraham Lincoln, Georges Clemenceau, Winston Churchill, and David Ben-Gurion to build his argument, Cohen offers compelling proof that, as Clemenceau put it, “War is too important to leave to the generals.” By examining the shared leadership traits of four politicians who triumphed in extraordinarily varied military campaigns, Cohen argues that active statesmen make the best wartime leaders, pushing their military subordinates to succeed where they might have failed if left to their own devices. Thought provoking and soundly argued, Cohen's Supreme Command is essential reading not only for military and political players but also for informed citizens and anyone interested in leadership.

Customer Reviews:

War is too important to be left to the generals.......2007-08-03

According to the appendix of the book, there is civilian control because military expertise may be isolated. There is a theory of objective control, but it doesn't suffice. The leadership of a Lincoln, a Ben-Gurion, a Churchill does not depend upon the separation of the military sphere from the civilian sphere. Tolstoy described strategic nihilism. Waging war is a different activity than the practice of other professions. An experience curve, routinization, is lacking. Calamities do not stem from incompetence, per se. Effective wartime leaders show ruthlessness, mastery of detail, interest in technology. The leaders cited in the book interfered with the military professionals. In Clauswitz's view there is no line dividing the civil and military areas of control. There are differences. In the military there are rules, in politics there are none.

Abraham Lincoln both found his generals, Grant and Sherman, and controlled them. Jefferson Davis had more military qualifications than Lincoln. Lincoln's war was driven by the rifle, the telegraph, and the railroad--new technology. Assaults on field fortifications proved ruinous. Lincoln's strategic plan had to be modified in practice.

Visits to the front betokened Clemenceau's wartime civilian leadership. In 1917 he was seventy-six. He served during the last year of the war and the negotiation of the peace. When Poincare called upon Clemenceau to guide France, it was experiencing a blood bath. In visiting the front, (Clemenceau had also done this as a senator), Clemenceau was practicing management by walking around. He acquired information and influenced events.

Winston Churchill had strength, humor, readiness to listen, (he thought outside of the box). His wartime leadership has been attacked by historians, but the writer of this book disagrees with such negative assessments. It has been charged that Chruchill had a deplorable strategic sense. The existence of a Churchill Society, evidence of popular acclaim, makes serious historians wince. Details provided by Lord Moran, Churchill's physician, have suggested impairments from drink and aging tending to hurt Churchill's reputation.

Notwithstanding what critics have said, Churchill had system and he was a glutton for work. Disciplined habits drove his career. He could see the relationship between the large and the small. He was unprepared to take military judgments on faith because he distrusted bureaucracies and remembered World War I. Churchill developed grand strategy, cultivating the Americans and the Russians in order to win the war. He excelled at holding together the alliance. He engaged in incessant close-questioning of his military staff. Churchill needed to goad his commanders into action. He mastered political rhetoric.

This book is a marvel of good arguments supported by telling details.
The theme is that greater exertion by civilian leadership ensures a better outcome in instances of last resort, i.e. nations finding it necessary to go to war.

Fully-vetted argument; could have been expanded.......2007-01-10

Eliot Cohen's work informs the current debate on the use of force to attain political objectives and the role of the statesman or politician compared to that of the soldier. His use of case studies is effective in proving his basic argument - that the normal theory of civil military relations is an inadequate explanation for success in war. But Cohen's poignant discussion does leave some questions unanswered on the military profession's place in a democracy:

- Understanding that Cohen's focus was on wartime leadership, the reader still could have gained benefit from a parallel discussion of the use of force in peacetime (e.g. U.N. Security Council Resolution enforcement, sanctions, show of force/posturing). In today's strategic environment, regional military personnel (combatant commanders) wield great power in peacetime foreign policy formulation. A treatment of the combatant commander's influence in foreign policy and the ethics of an unelected government official wielding such power would be valuable.

- Especially relevant today is a treatment of the retired military officer's place in a democracy: outspoken critic, advocate, or silent observer. Many, including Cohen apparently (see p. 171 comparing retired soldiers to "true civilians" in Israeli society), believe that for retirees to criticize a military strategy or the policy that guides the strategy degrades civil-military relations. I have the greatest contention with this thought. Military personnel, active duty or retired, have a stake in the outcome of the state's foreign policy machinations, and it is appropriate for them to state that opinion. As a former great citizen-soldier commented, "When we assumed the Soldier, we did not lay aside the Citizen."

The negative tone of this review should not detract from Cohen's excellent treatment of the subject. Supreme Command furthers the debate on civil-military relations and those in the defense establishment stand to gain from a careful study of this work, be they soldier or civilian.

Senior Military Leaders Must Read This Book.......2006-11-10

Senior Military Leaders Must Read This Book.
A must read for any military officer or civilian leader in the Department of Defense. Anyone interested in leadership will benefit from reading the lessons of leadership by great men during difficult times. 5 stars.

Scattered and loses focus.......2006-06-18

Eliot Cohen has an impressive background in policy work (OSD) and academia (Naval War College and Harvard). I had high hopes for this book because I thought his experience with the military combined with his academic work would produce a focused and well-grounded work. I was disappointed. I never really bought his argument that political leaders can lead war better than generals. He seemed to cherry pick leaders than fit his mold. I could not believe that someone who works so closely with the military would generalize military leadership in such a stereotypical way.

The article might have made a good article in a foreign affairs journal, but the author seemed to fill out the book with a lot of interesting but not really relevant historical stories and facts. The Lincoln chapter providing nothing that has not been stated numerous times in more detailed and focused work. The Churchill chapter was the best. Cohen obviously has extensively studied Churchill. His sections on how the historical view of Churchill have ebbed and flowed over the years was well done, thought not rally tied to the focus of the book. I learned the most from the Ben-Gurion, since I knew the least about him.

The book may be useful to an undergraduate class studying political leadership or foreign policy, but beyond that the book unfortunately offers little that is new or of great interest.

Square peg into round hole (or, stop after the 4 bios).......2006-02-26

This would have been 4 stars had I stopped after the individual chapters on Abraham Lincoln, Georges Clemenceau, Winston Churchill and David Ben Gurion. However, I unfortunately found out, in the subsequent chapter, that Cohen's REAL purpose was an end-around to attack American leadership during Vietnam (and, to a lesser extent, the Gulf War). For a book that focuses on leaders from England, France, and Israel, as well as the US, this struck me as a non-sequitor out of left field.

I do recommend purchasing this book. However, do NOT continue reading beyond the Ben Gurion chapter. You will become disappointed with your purchase.

Supreme Command: Soldiers, Statesmen, and Leadership in Wartime, Library Edition

Average customer rating:

Four examples of great leadership

Supreme Command: Soldiers, Statesmen, and Leadership in Wartime, Library Edition
Eliot A. Cohen
Manufacturer: Blackstone Audiobooks
ProductGroup: Book
Binding: Audio CD

General | Military | History | Subjects | Books

Leadership | Politics | Nonfiction | Subjects | Books

General | Books on CD | Audiobooks | Formats | Books

All Titles | Qualifying Textbooks - Fall 2007 | Stores | Books
ASIN: 0786192968

Customer Reviews:

Four examples of great leadership .......2004-11-01

Lincoln, Clemenceau, Churchill and Ben- Gurion's stories are told in this work, especially in regard to their relation to the military under their command. All four were strong leaders who focused in war on military victory but did not allow themselves to become subordinate to or enslaved by their military leaders. All four had the great ability to concentrate on the ultimate goal, and put all their force behind it to achieve it. They too showed an ability to listen to and learn from subordinates. And as leaders of their respective nations knew how to inspire others to follow them. Cohen's study is magnificently insightful, always interesting , filled with understanding of the complexities of democratic rule. It will be of great value and great pleasure especially to those who take interest in military and political affairs.

Book Description

Now available in paperback, a shocking examination of the politics of intellectual life during the Cold War. Now in paperback, Universities and Empire is a fascinating exploration of the seamier connections between academic research and official public policy during the most turbulent years of the Cold War. It explores the effects of the U.S. military, intelligence, and propaganda agencies on academic culture and intellectual life. Essays by leading academics examine the origins of new subjects of research such as Asian Studies and Development Studies; mine the secret history of Cold War initiatives such as Project Troy and Project Camelot; and discuss the legacy of corporate involvement in the university system.

Contributors include Bruce Cumings (University of Chicago), Irene L. Gendzier (Boston University), Allan A. Needell (Smithsonian Institution), Kevin Gaines (University of Texas, Austin), Slava Gerovitch (MIT), Ellen Herman (University of Oregon), Christopher Simpson (American University), and Lawrence Soley (Marquette University).

Book Description

Increasingly, neural networks are used and implemented in a wide range of fields and have become useful tools in probabilistic analysis and prediction theory. This bookâ€”unique in the literatureâ€”studies the application of neural networks to the analysis of time series of sea data, namely significant wave heights and sea levels. The particular problem examined as a starting point is the reconstruction of missing data, a general problem that appears in many cases of data analysis.

Specific topics covered include:

* Presentation of general information on the phenomenology of waves and tides, as well as related technical details of various measuring processes used in the study.

* Description of the model of wind waves (WAM) used to determine the spectral function of waves and predict the behavior of SWH (significant wave heights); a comparison is made of the reconstruction of SWH time series obtained by means of neural networks algorithms versus SWH computed by WAM.

* Principles of artificial neural networks, approximation theory, and extreme-value theory necessary to understand the main applications of the book.

* Application of artificial neural networks (ANN) to reconstruct SWH and sea levels (SL).

* Comparison of the ANN approach and the approximation operator approach, displaying the advantages of ANN.

* Examination of extreme-event analysis applied to the time series of sea data in specific locations.

* Generalizations of ANN to treat analogous problems for other types of phenomena and data.

This book, a careful blend of theory and applications, is an excellent introduction to the use of ANN, which may encourage readers to try analogous approaches in other important application areas. Researchers, practitioners, and advanced graduate students in neural networks, hydraulic and marine engineering, prediction theory, and data analysis will benefit from the results and novel ideas presented in this useful resource.

An Introduction to the Modeling of Neural Networks (Collection Alea-Saclay: Monographs and Texts in Statistical Physics)

Average customer rating:

An Introduction to the Modeling of Neural Networks (Collection Alea-Saclay: Monographs and Texts in Statistical Physics)
Pierre Peretto
Manufacturer: Cambridge University Press
ProductGroup: Book
Binding: Paperback

General | Certification Central | Computers & Internet | Subjects | Books

General | Science | Subjects | Books

General | Mathematics | Science | Subjects | Books

Mathematical Physics | Physics | Science | Subjects | Books

General | Medicine | Subjects | Books

All Titles | Qualifying Textbooks - Fall 2007 | Stores | Books
ASIN: 0521424879

Book Description

This text is a graduate-level introduction to neural networks, focusing on current theoretical models, examining what these models can reveal about how the brain functions, and discussing the ramifications for psychology, artificial intelligence, and the construction of a new generation of intelligent computers. The book is divided into four parts. The first part gives an account of the anatomy of the central nervous system, followed by a brief introduction to neurophysiology. The second part is devoted to the dynamics of neuronal states, and demonstrates how very simple models may stimulate associative memory. The third part of the book discusses models of learning, including detailed discussions on the limits of memory storage, methods of learning and their associated models, associativity, and error correction. The final section of the book reviews possible applications of neural networks in artificial intelligence, expert systems, optimization problems, and the construction of actual neuronal supercomputers, with the potential for one-hundred fold increase in speed over contemporary serial machines.

Modeling Brain Function: The World of Attractor Neural Networks

Average customer rating:

Of historical importance

Modeling Brain Function: The World of Attractor Neural Networks
Daniel J. Amit
Manufacturer: Cambridge University Press
ProductGroup: Book
Binding: Hardcover

General | Certification Central | Computers & Internet | Subjects | Books

Physiology | Basic Science | Medicine | Subjects | Books

General | Medicine | Subjects | Books

Networking | Computer Science & Information Systems | New & Used Textbooks | Stores | Books

Theoretical Neuroscience: Computational and Mathematical Modeling of Neural Systems

ASIN: 0521361001

Book Description

Exploring one of the most exciting and potentially rewarding areas of scientific research, the study of the principles and mechanisms underlying brain function, this book introduces and explains the techniques brought from physics to the study of neural networks and the insights they have stimulated. Substantial progress in understanding memory, the learning process, and self-organization by studying the properties of models of neural networks have resulted in discoveries of important parallels between the properties of statistical, nonlinear cooperative systems in physics and neural networks. The author presents a coherent and clear, nontechnical view of all the basic ideas and results. More technical aspects are restricted to special sections and appendices in each chapter.

Customer Reviews:

Of historical importance.......2005-10-04

The study of the physics of the brain from the standpoint of dynamical systems was very popular during the 1980's. The theory of chaotic dynamical systems, and the accompanying concepts of strange attractors, horseshoe maps, and fractal basins of attraction was the subject of intense research at that time. It was inevitable perhaps that these theories would be applied to the understanding of the brain, given the dynamical nature of the neuronal synapse. This book, published in 1989, gives a good overview of what was known at the time. It could be read by anyone with a background in dynamical systems and some elementary knowledge of brain biology. The mathematics is also straightforward in that the author does not bring in any of the heavy tools from differential topology or measure theory, which is normally done in discussions of dynamical systems.

There are some points made in the book that must be understood by the reader because the author feels that they are needed to build a successful model of the brain. For example, he discusses the notion of an `input system', which is a system that, for each input, produces and output with the same "status." Cognitive discrimination must be used at the input level, if one is to avoid the use of the `homunculus' (the little external observer), for distinguishing between "good" and "bad" outputs. The major task in the author's view is to produce "exceptional" input-output relations, i.e. relations that correspond to intuitions about cognitive processes. A successful brain model, i.e. one that is able to incorporate memory, should be able to distinguish between stimuli that are familiar from those that are to be submitted to the brain for processing or learning. Thus the model must avoid the use of what the author calls `spontaneous computations', which require an external observer (the homunculus again) to interpret the relation between the input and the output. The author gives an example of a system that performs only spontaneous computations early on in the book. Hence the author proposes the use of artificial neural networks (ANNs) to avoid the occurrence of spontaneous computations. An ANN organizes stimuli in association classes represented by an attractor, and all the stimuli in a particular class are associated with the attractor to which they flow. The author feels that ANNs are more adept at respecting the requirement that for mental computations, which are essentially operations on temporal sequences of data, some record of the initial input sequence must be carried along on a parallel channel, in order to provide the outcome with specific "meaning" and a correspondence to the assigned task.

These considerations on the dependence of the processing on the initial input motivate the author to discuss the role of ergodicity in the dynamics of the neural systems of the brain. As the author shows, any generic system subjected to noise will be ergodic, so that eventually the system will access each of its possible states in a manner that is completely independent of the initial state. The author points out two ways in which ergodicity can be avoided: one is to assume that the network is noiseless, and thus only certain moves are allowed from each vertex; the other is to assume that `cooperative phenomena' is present. Since the first possibility is rather exceptional, the author chooses the second, and gives detailed discussion on how cooperative behavior can arise in ANNs. One interesting, and ubiquitous example that he discusses for cooperativity as an emergent property is the Ising model. Mathematically, the breaking of ergodicity involves the taking of the thermodynamic limit, and a necessary condition for emergence is this context is the asymptotic degeneracy of the eigenvalues. To illustrate how this is done, the author uses the solution of a master equation that characterizes the probabilities of making transitions from one state to another in the system.

In order to build a credible model of the neuronal processes of the brain, the author is aware that such a model has to be able to deal with input in the form of temporal sequences, and not just single patterns. He devotes an entire chapter to this in the book, motivating his discussion with the notion of a `central pattern generator' (CPG). The simplicity of CPGs is a concern and the author is aware that such simplicity does not exist in models of cognitive processes. Nevertheless the modeling of CPGs using neural networks can add credence to the program to model general brain processes in terms of neural networks, complex as they can be.

One of course must be able to deal with both the storage and the retrieval of temporal sequences. After discussing some of the early research dealing with these needs, the author then reviews a strategy for dealing with temporal sequences that involves the notion of a `quasi-attractor', which is a network state that acts like an attractor for a short period of time. Quasi-attractors are used to delay the transfer of information out of the attractor. Thus the transitions are governed by synapses that have a time delay. The influence of a pre-synaptic neuron through these synapses will arrive later than the influence coming through a `stabilizing' synapse. The latter type of synapse arises because of the `stabilizing' term in the network model that ensures that if the network is in a state that is identical to a stored pattern then the network will remain there. The author shows how the network can use these delayed transitions to deal with temporal sequences in a manner that is acceptable, i.e. in a way that the `cognition time' is of the order of magnitude of the delay. The author discusses an example dealing with the counting of chimes, in order to give credence to his constructions. In this example it is seen that the network resides in each of the quasi-attractors for a long enough time so as to allow the output neurons to identify the cognitive event.

Neural Network Modeling: Statistical Mechanics and Cybernetic Perspectives

Average customer rating:

Neural Network Modeling: Statistical Mechanics and Cybernetic Perspectives
P. S. Neelakanta , and Dolores DeGroff
Manufacturer: CRC
ProductGroup: Book
Binding: Hardcover

Culture | Business & Culture | Computers & Internet | Subjects | Books

Systems Analysis & Design | Computer Science | Computers & Internet | Subjects | Books

General | Certification Central | Computers & Internet | Subjects | Books

General | Computers & Internet | Subjects | Books

General | Science | Subjects | Books
ASIN: 0849324882

Book Description

Neural Network Modeling offers a cohesive approach to the statistical mechanics and principles of cybernetics as a basis for neural network modeling. It brings together neurobiologists and the engineers who design intelligent automata to understand the physics of collective behavior pertinent to neural elements and the self-control aspects of neurocybernetics. The theoretical perspectives and explanatory projections portray the most current information in the field, some of which counters certain conventional concepts in the visualization of neuronal interactions.

Neural Networks for Statistical Modeling

Average customer rating:

Neural Networks for Statistical Modeling
Murray Smith
Manufacturer: Van Nostrand Reinhold
ProductGroup: Book
Binding: Paperback

General | Certification Central | Computers & Internet | Subjects | Books

General | Computers & Internet | Subjects | Books

General | Science | Subjects | Books

General | Mathematics | Science | Subjects | Books

Statistical Pattern Recognition (Hodder Arnold Publication)

Average customer rating:

The most comprehensive book about machine learning
Very Bad treatment of the subject
This book is good guidance.

Statistical Pattern Recognition (Hodder Arnold Publication)
Andrew Webb
Manufacturer: Arnold Publishing
ProductGroup: Book
Binding: Paperback

Modeling & Simulation | Computer Science | Computers & Internet | Subjects | Books

General | Computers & Internet | Subjects | Books

General | Science | Subjects | Books

All Titles | Qualifying Textbooks - Fall 2007 | Stores | Books

Computers & Internet | Qualifying Textbooks - Fall 2007 | Stores | Books

Professional | Qualifying Textbooks - Fall 2007 | Stores | Books

Science | Qualifying Textbooks - Fall 2007 | Stores | Books
Similar Items:

ASIN: 0340741643

Book Description

Statistical pattern recognition is currently a very active area of study and research. This text provides an introduction to statistical pattern theory and techniques, with material drawn from a wide range of fields, including the areas of engineering, statistics, computer science and the social sciences. It provides a valuable link between the application areas - such as database design, artificial neural networks, and decision support - and the more diverse theoretical topics available to the practitioner or researcher. It is very up-to-date and covers the latest state-of-the-art techniques.

Download Description

"Statistical pattern recognition is a very active area of study and research, which has seen many advances in recent years. New and emerging applications - such as data mining, web searching, multimedia data retrieval, face recognition, and cursive handwriting recognition - require robust and efficient pattern recognition techniques. Statistical decision making and estimation are regarded as fundamental to the study of pattern recognition. Statistical Pattern Recognition, Second Edition has been fully updated with new methods, applications and references. It provides a comprehensive introduction to this vibrant area - with material drawn from engineering, statistics, computer science and the social sciences - and covers many application areas, such as database design, artificial neural networks, and decision support systems. Provides a self-contained introduction to statistical pattern recognition. Each technique described is illustrated by real examples. Covers Bayesian methods, neural networks, support vector machines, and unsupervised classification. Each section concludes with a description of the applications that have been addressed and with further developments of the theory. Includes background material on dissimilarity, parameter estimation, data, linear algebra and probability. Features a variety of exercises, from 'open-book' questions to more lengthy projects. The book is aimed primarily at senior undergraduate and graduate students studying statistical pattern recognition, pattern processing, neural networks, and data mining, in both statistics and engineering departments. It is also an excellent source of reference for technical professionals working in advanced information development environments."

Customer Reviews:

The most comprehensive book about machine learning.......2007-02-28

The book written by Andrew Webb is certainly the most comprehensive book related to machine learning. I have not been able to find any machine learning topic which is not treated in this book.

According to me, this book is more for a scientific audience for the simplest reason that the presentation gives more importance to equations than to application examples. It does not explain how to program machine learning algorithm but rather which algorithms exist and what is their mathematical background. Every technique is presented first using text and only then mathematical development is shown. Therefore, it is convenient for people preferring textual description as well as the ones preferring equations.

The book is very well structured. Every chapter starts with a textual introduction on the related issue and then describes several techniques to solve it. At the end, specific application examples are given. A large part is then devoted to summary, discussion, recommendations (not always), notes and references, and finally exercises. Topics are covered in a non standard way for people used to data mining practical books. After an introduction, density estimation techniques are explained. Then linear and non-linear discriminant analyzes. It goes on with decision trees, performance and feature selection to finish with clustering and some other additional topics. Although this book is written in a statistical point of view, it is certainly one of the most comprehensive resource for machine learning and data mining.

Very Bad treatment of the subject.......2006-01-12

The author claims that this book is written for senior undergrads and gaduate students, on the contraray, of what he claimed, his treatment of the suject is very sketchy. He has written this book in a somewhat citational manner i.e not treating any details of the concerned topics whatsoever and only stating the facts directly like he is citing some kind of terminolgy and not intersted in giving the reader a thourough understanding of the subject.
He has given extensive references and urls and so this book is more like " I can't explain anything go search urself here".
I think its the most worst way anybody could adopt for writing a book. In my opinion the only purpose of this book was to have a publication on his credit.
I would strongly recommend any students to refrain from buying this one as it will not help you much in any way.
Or else if u realy like to use very expensive toilet paper then give this book a try.

This book is good guidance........2000-11-03

I recently started study about Pattern Recognition. This book is so well organized.

- Introduction to statistical pattern recognition

- Basic approaches to supervised classification via Bayes' rule and estimation of the class-conditional densities.

- Discriminant function approach to supervised classification.

- Techniques of exploratory data analysis.

- Additional topics on pattern recognition including performance assessment.

Especially, this book contains URL which concerned with topics. It is very useful!!

Average customer rating:
Neural network and regression spline value function approximations for [An article from: Computers and Operations Research]
C. Cervellera , A. Wen , and V.C.P. Chen
Manufacturer: Elsevier
ProductGroup: Book
Binding: Digital

Management | Management & Leadership | Business & Investing | Subjects | Books
Management | Business & Investing | Subjects | e-Docs | Formats | Books
ASIN: B000P6OFXC

Book Description

This digital document is a journal article from Computers and Operations Research, published by Elsevier in 2007. The article is delivered in HTML format and is available in your Amazon.com Media Library immediately after purchase. You can view it with any web browser.

Description:
Dynamic programming is a multi-stage optimization method that is applicable to many problems in engineering. A statistical perspective of value function approximation in high-dimensional, continuous-state stochastic dynamic programming (SDP) was first presented using orthogonal array (OA) experimental designs and multivariate adaptive regression splines (MARS). Given the popularity of artificial neural networks (ANNs) for high-dimensional modeling in engineering, this paper presents an implementation of ANNs as an alternative to MARS. Comparisons consider the differences in methodological objectives, computational complexity, model accuracy, and numerical SDP solutions. Two applications are presented: a nine-dimensional inventory forecasting problem and an eight-dimensional water reservoir problem. Both OAs and OA-based Latin hypercube experimental designs are explored, and OA space-filling quality is considered.

Approximating a function and its derivatives using MSE-optimal linear combinations of trained feedforward neural networks (Statistical analysis for stochastic ... with applications to manufacturing)

Average customer rating:

Approximating a function and its derivatives using MSE-optimal linear combinations of trained feedforward neural networks (Statistical analysis for stochastic ... with applications to manufacturing)
Sherif Hashem
Manufacturer: Pritsker & Associates
ProductGroup: Book
Binding: Unknown Binding

General | Certification Central | Computers & Internet | Subjects | Books
ASIN: B0006P79IU

Improving model accuracy using optimal linear combinations of trained neural networks (Statistical analysis for stochastic modeling and simulation with applications to manufacturing)

Average customer rating:

Improving model accuracy using optimal linear combinations of trained neural networks (Statistical analysis for stochastic modeling and simulation with applications to manufacturing)
Sherif Hashem
Manufacturer: Pritsker & Associates
ProductGroup: Book
Binding: Unknown Binding

General | Certification Central | Computers & Internet | Subjects | Books
ASIN: B0006P7A66

Optimal linear combinations of neural networks: An overview (Statistical analysis for stochastic modeling and simulation with applications to manufacturing)

Average customer rating:

Optimal linear combinations of neural networks: An overview (Statistical analysis for stochastic modeling and simulation with applications to manufacturing)
Sherif Hashem
Manufacturer: Pritsker & Associates
ProductGroup: Book
Binding: Unknown Binding

General | Certification Central | Computers & Internet | Subjects | Books
ASIN: B0006P7A4S

Product Description

Wildlife conservation through environmental means along with sustainable use is a relatively new practice in our country. Going back several thousand years we find conservation practices that are quite similar to today\'s in the Holy Bible.

Books:

Books Index

Books Home

Recommended Books