COMBINATORIAL DEVELOPMENT OF SOLID..(V7)

Design Of High-throughput Experiments, Data Analysis, Data Mining

By: Manfred Baerns, Martin Holeňa

Write A Review

Hardcover | 1 December 2009

At a Glance

Hardcover
192 Pages

Dimensions(cm)
22.86 x 15.24 x 1.27

Hardcover

RRP $180.99

$126.75

30%OFF

or 4 interest-free payments of $31.69 with

or

Ships in 15 to 25 business days

The book provides a comprehensive treatment of combinatorial development of heterogeneous catalysts. In particular, two computer-aided approaches that have played a key role in combinatorial catalysis and high-throughput experimentation during the last decade - evolutionary optimization and artificial neural networks - are described. The book is unique in that it describes evolutionary optimization in a broader context of methods of searching for optimal catalytic materials, including statistical design of experiments, as well as presents neural networks in a broader context of data analysis. It is the first book that demystifies the attractiveness of artificial neural networks, explaining its rational fundamental - their universal approximation capability. At the same time, it shows the limitations of that capability and describes two methods for how it can be improved. The book is also the first that presents two other important topics pertaining to evolutionary optimization and artificial neural networks: automatic generating of problem-tailored genetic algorithms, and tuning evolutionary algorithms with neural networks. Both are not only theoretically explained, but also well illustrated through detailed case studies.

Shipping

	Standard Shipping	Express Shipping
Metro postcodes:	$9.99	$14.95
Regional postcodes:	$9.99	$14.95
Rural postcodes:	$9.99	$14.95

Orders over $0.00 qualify for free shipping.

How to return your order

At Booktopia, we offer hassle-free returns in accordance with our returns policy. If you wish to return an item, please get in touch with Booktopia Customer Care.

Additional postage charges may be applicable.

Defective items

If there is a problem with any of the items received for your order then the Booktopia Customer Care team is ready to assist you.

For more info please visit our Help Centre.

More in Neural Networks & Fuzzy Systems

Hands-On Machine Learning with Scikit-Learn and PyTorch

Concepts, Tools, and Techniques to Build Intelligent Systems

Paperback

RRP $82.99

$66.39

20%
OFF

Fuzzy Logic in Computational Intelligence : Applications and Case Studies - Rahul Kar

$64.75

51%
OFF

Effective Machine Learning Teams

Best Practices for ML Practitioners

Paperback

RRP $152.00

$121.60

20%
OFF

Practical Machine Learning for Computer Vision

End-to-End Machine Learning for Images

Paperback

RRP $171.00

$136.80

20%
OFF

Quantum Machine Learning : Theory, Algorithms, and Practical Implementation - Hamid D. Ismail

$148.75

Computational Approaches to Emotion in Artificial Psychology - Alessandro Grecucci

$361.75

Preface	p. vii
Background of Combinatorial Catalyst Development	p. 1
Bibliography	p. 4
Approaches in the Development of Heterogeneous Catalysts	p. 7
Fundamental Aspects	p. 7
High-throughput Technologies for Preparation and Testing in Combinatorial Development of Catalytic Materials	p. 9
Selection of Potential Elements for Defining the Multi-parameter Compositional Space of Catalytic Materials	p. 10
Experimental Tools for Preparing and Testing Large Numbers of Catalytic-material Specimens	p. 13
Preparation of catalytic materials	p. 14
Testing and screening of catalytic materials	p. 16
Bibliography	p. 19
Mathematical Methods of Searching for Optimal Catalytic Materials	p. 21
Introduction	p. 21
Statistical Design of Experiments	p. 22
Optimisation Methods for Empirical Objective Functions	p. 24
Evolutionary Optimisation: The Main Approach to Seek Optimal Catalysts	p. 26
Dealing with Constraints in Genetic Optimisation	p. 31
Other Stochastic Optimisation Methods	p. 33
Deterministic Optimisation	p. 34
Utilizability of Methods with Derivatives in Catalysis	p. 36
Bibliography	p. 37
Generating Problem-Tailored Genetic Algorithms for Catalyst Search	p. 43
Using a Program Generator - Why and How	p. 43
Description Language for Optimisation Tasks in Catalysis	p. 47
Tackling Constrained Mixed Optimisation	p. 53
A Prototype Implementation	p. 57
Bibliography	p. 59
Analysis and Mining of Data Collected in Catalytic Experiments	p. 61
Similarity and Difference Between Data Analysis and Mining	p. 61
Survey of Existing Methods	p. 62
Statistical Methods	p. 63
Extraction of Logical Rules from Data	p. 67
Case Study with the Synthesis of HCN	p. 70
Bibliography	p. 75
Artificial Neural Networks in the Development of Catalytic Materials	p. 79
What are Artificial Neural Networks?	p. 79
Network Architecture	p. 80
Important Kinds of Neural Networks	p. 83
Activity of Neurons	p. 87
What do Neural Networks Compute?	p. 88
Approximation Capability of Neural Networks	p. 90
Training Neural Networks	p. 95
Knowledge Obtainable from a Trained Network	p. 103
Bibliography	p. 110
Tuning Evolutionary Algorithms with Artificial Neural Networks	p. 115
Heuristic Parameters of Genetic Algorithms	p. 115
Parameter Tuning Based on Virtual Experiments	p. 116
Case Study with the Oxidative Dehydrogenation of Propane	p. 119
Bibliography	p. 133
Improving Neural Network Approximations	p. 135
Importance of Choosing the Right Network Architecture	p. 135
Influence of the Distribution of Training Data	p. 136
Boosting Neural Networks	p. 138
Case Study with HCN Synthesis Continued	p. 141
Bibliography	p. 152
Applications of Combinatorial Catalyst Development and An Outlook on Future Work	p. 155
Introduction	p. 155
Experimental Applications of Combinatorial Catalyst Development	p. 155
Methodology	p. 163
Conclusions and Outlook	p. 169
Applications of Combinatorial Methodologies in Practice	p. 169
Computer-aided Methods for the Optimisation of Catalyst Composition and Data Mining	p. 171
Bibliography	p. 172
Index	p. 175
Table of Contents provided by Ingram. All Rights Reserved.

COMBINATORIAL DEVELOPMENT OF SOLID..(V7)

Design Of High-throughput Experiments, Data Analysis, Data Mining

At a Glance

Hardcover

Shipping

How to return your order

Defective items

You Can Find This Book In

More in Neural Networks & Fuzzy Systems

Hands-On Machine Learning with Scikit-Learn and PyTorch

Concepts, Tools, and Techniques to Build Intelligent Systems

Fuzzy Logic in Computational Intelligence

Applications and Case Studies

Mathematics of Uncertainty Applied to Global Issues

Sustainability, Mistreatment of Women, Nuclear Power, Smart Cities, Digitalization

Vector Databases

A Practical Introduction

Effective Machine Learning Teams

Best Practices for ML Practitioners

Practical Machine Learning for Computer Vision

End-to-End Machine Learning for Images

Quantum Machine Learning

Theory, Algorithms, and Practical Implementation

Data and Model-Centric Artificial Intelligence for Industry 5.0

Brain-Inspired AI for Sustainable Development

Knowledge-based Engineering for Innovation

Large Language Models and Prompt Engineering

A Comprehensive Guide with Practical Applications

Practical Applications of Artificial Intelligence in Education

For Early Childhood Education, Primary, Secondary, Baccalaureate and Vocational Training

Computational Approaches to Emotion in Artificial Psychology

Computational Approaches to Emotion in Artificial Psychology

AI for Human-Computer Interaction

AI for Everything

AI for Human-Computer Interaction

AI for Everything

An Introduction to Large Language Models

An Introduction to Large Language Models

Machine Translation

Best Practices using Deep Learning and Generative AI

Neuroscience and the Dream of Digital Immortality

The Upload Illusion

Neuroscience and the Dream of Digital Immortality

The Upload Illusion

Reinforcement Learning in Action

From Foundations to Frontier AI

Reinforcement Learning in Action

From Foundations to Frontier AI

Superhuman

Beyond the Limits of Our Intelligence

Modern Computing

Principles and Paradigms

This product is categorised by