1.

Record Nr.

UNISA990001619800203316

Autore

GOLDSMITH, Oliver <1728-1744>

Titolo

She stoops to conquer / Oliver Goldsmith ; introduction and notes by Robert Herring

Pubbl/distr/stampa

London : MacMillan, 1958

Descrizione fisica

XXII, 112 p. ; 18 cm

Collocazione

VII.3.A. 731(II i A 161)

Lingua di pubblicazione

Inglese

Formato

Materiale a stampa

Livello bibliografico

Monografia

2.

Record Nr.

UNIORUON00027985

Autore

HAUSL, Maria

Titolo

Abischag und Batscheba : frauen am konigshof und die thronfolge Davids im zeugnis der texte 1 Kon 1 und 2 / Maria Hausl

Pubbl/distr/stampa

St. Ottilien, : EOS Verlag, 1993 ix, 345 p. ; 21 cm

ISBN

38-8096-541-2

Classificazione

SEB III

Soggetti

ANTICO TESTAMENTO - STUDI LINGUISTICI

Lingua di pubblicazione

Tedesco

Formato

Materiale a stampa

Livello bibliografico

Monografia



3.

Record Nr.

UNINA9910254258203321

Autore

Cuevas Erik

Titolo

Advances of Evolutionary Computation: Methods and Operators / / by Erik Cuevas, Margarita Arimatea Díaz Cortés, Diego Alberto Oliva Navarro

Pubbl/distr/stampa

Cham : , : Springer International Publishing : , : Imprint : Springer, , 2016

ISBN

3-319-28503-3

Edizione

[1st ed. 2016.]

Descrizione fisica

1 online resource (XIV, 202 p. 48 illus., 43 illus. in color.)

Collana

Studies in Computational Intelligence, , 1860-9503 ; ; 629

Disciplina

006.3823

Soggetti

Computational intelligence

Artificial intelligence

Computational Intelligence

Artificial Intelligence

Lingua di pubblicazione

Inglese

Formato

Materiale a stampa

Livello bibliografico

Monografia

Note generali

Bibliographic Level Mode of Issuance: Monograph

Nota di bibliografia

Includes bibliographical references.

Nota di contenuto

Introduction -- A Swarm Global Optimization Algorithm Inspired in the Behavior of the Social-spider.-A States of Matter Algorithm for Global Optimization -- An Algorithm for Global Optimization Inspired by Collective Animal Behavior -- A Bio-inspired Evolutionary Algorithm: Allostatic Optimization -- Optimization Based on the Behavior of Locust Swarms. .

Sommario/riassunto

The goal of this book is to present advances that discuss alternative Evolutionary Computation (EC) developments and non-conventional operators which have proved to be effective in the solution of several complex problems. The book has been structured so that each chapter can be read independently from the others. The book contains nine chapters with the following themes: 1) Introduction, 2) the Social Spider Optimization (SSO), 3) the States of Matter Search (SMS), 4) the collective animal behavior (CAB) algorithm, 5) the Allostatic Optimization (AO) method, 6) the Locust Search (LS) algorithm, 7) the Adaptive Population with Reduced Evaluations (APRE) method, 8) the multimodal CAB, 9) the constrained SSO method.