國立高雄大學圖資館 |

語系: 繁體中文

說明(常見問題)

圖資館首頁

登入

回首頁

切換: 標籤 | MARC模式 | ISBD

Combinatorial development of solid c...

Baerns, M. (1934-)

Combinatorial development of solid catalytic materialsdesign of high-throughput experiments, data analysis, data mining /

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Combinatorial development of solid catalytic materialsManfred Baerns, Martin Hole幯a.
其他題名:	design of high-throughput experiments, data analysis, data mining /
作者:	Baerns, M.
其他作者:	Hole幯a, Martin.
出版者:	London :Imperial College Press ;c2009.
面頁冊數:	xi, 178 p. :ill. (some col.)
標題:	CatalysisComputer simulation.
電子資源:	http://www.worldscientific.com/worldscibooks/10.1142/P620#t=toc
ISBN:	9781848163447 (electronic bk.)

Combinatorial development of solid catalytic materialsdesign of high-throughput experiments, data analysis, data mining /
Baerns, M.1934-

Combinatorial development of solid catalytic materialsdesign of high-throughput experiments, data analysis, data mining /[electronic resource] :Manfred Baerns, Martin Hole幯a. - London :Imperial College Press ;c2009. - xi, 178 p. :ill. (some col.) - Catalytic science series ;v. 7. - Catalytic science series ;v. 11..

Includes bibliographical references and index.

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.

Electronic reproduction.
Singapore :
World Scientific Publishing Co.,
2009.

System requirements: Adobe Acrobat Reader.

ISBN: 9781848163447 (electronic bk.)Subjects--Topical Terms:

469138
Catalysis
--Computer simulation.

LC Class. No.: QD505

Dewey Class. No.: 541.395

Combinatorial development of solid catalytic materialsdesign of high-throughput experiments, data analysis, data mining /
LDR:02382nmm a2200277 a 4500 001 345729
003 WSP
005 20100405110404.0
006 m d
007 cr cuu|||uu|||
008 121106s2009 enka sb 001 0 eng d
020 $a 9781848163447 (electronic bk.)
020 $z 1848163436
020 $z 9781848163430
035 $a 00000612
050 4 $a QD505
082 0 4 $a 541.395 $2 22
100 1 $a Baerns, M. $q (Manfred), $d 1934- $3 437100
245 1 0 $a Combinatorial development of solid catalytic materials $h [electronic resource] : $b design of high-throughput experiments, data analysis, data mining / $c Manfred Baerns, Martin Hole幯a.
260 $a London : $b Imperial College Press ; $a Singapore : $b Distributed by World Scientific Pub. Co., $c c2009.
300 $a xi, 178 p. : $b ill. (some col.)
490 1 $a Catalytic science series ; $v v. 7
504 $a Includes bibliographical references and index.
520 $a 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.
533 $a Electronic reproduction. $b Singapore : $c World Scientific Publishing Co., $d 2009. $n System requirements: Adobe Acrobat Reader. $n Mode of access: World Wide Web. $n Available to subscribing institutions.
650 0 $a Catalysis $x Computer simulation. $3 469138
650 0 $a Catalysis $x Mathematical models. $3 575823
700 1 $a Hole幯a, Martin. $3 575822
710 2 $a World Scientific (Firm) $3 575130
776 1 $z 1848163436
776 1 $z 9781848163430
830 0 $a Catalytic science series ; $v v. 11. $3 575176
856 4 0 $u http://www.worldscientific.com/worldscibooks/10.1142/P620#t=toc