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Evolutionary design of neural networks

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Evolutionary design of neural networks

Evolutionary Design of Neural NetworksMarko A. GronroosMaster of Science ThesisComputer ScienceDepartment of Mathematical SciencesUniversity of Turku.

Evolutionary design of neural networks . 1998TƯRƯN YI.10PIST0Mateinaatisten tieteiden laitosGRỠNROOS, MARKO: Evolutionary design of neural networks(Hennoverkkojen rakenleen evolutiivinen op

timointi)Pro gradu -tutkielnia, 66 s.» 8 liites.TietojenkasittelyoppiKesakuu 1998Tama tutkielma kasitteiee nienetelniia sopivien hennoverkkorakenteide Evolutionary design of neural networks

n loytiirniseksi eri oppimisongelrnille. Hermoverkot ovat laskennallinen menetelmă, jossa yksinkertaiset, toisiinsa kytket.yt laskentaeleinentit voiva

Evolutionary design of neural networks

t yhdessă H1U0-dostaa inonimutkaisia funktioita. Elementtien ja kytkentojen parametrien maarittamiseen on oleinassa useita opetusmeneteliniă, mutt a n

Evolutionary Design of Neural NetworksMarko A. GronroosMaster of Science ThesisComputer ScienceDepartment of Mathematical SciencesUniversity of Turku.

Evolutionary design of neural networks nuoverkkojen rakenteen geneettisen koodausnienetehnan kanssa. Menetelinat ovat Miller. Toddja Hedgen suora koodaus, Kitanon graafingenerointikielioppi

. Nolfi ja Parish) sohiavaruuteen perustuva nienetelina, sekii Cangelosi, Parisi ja Nolfin generatiivinen soluava-ruuteen perustuva menetelma. Koodaus Evolutionary design of neural networks

nienetelniat niaarittavat vain verkon rakenteen; painojen opetus tapahtuu kăyttăen RProp-opetusinenetehnaa. Evolu-tiivisen algoritmin tarvitsema kelpo

Evolutionary design of neural networks

isuusarvo maaritellaan opetetun hermoverkon laskentavirheena erillisen arviointiaineiston suhteen.Tutkielman alkuosassa kaydăăn lăpi hennoverkkojen, e

Evolutionary Design of Neural NetworksMarko A. GronroosMaster of Science ThesisComputer ScienceDepartment of Mathematical SciencesUniversity of Turku.

Evolutionary design of neural networks tâ kokeista. Koodausmenetelmien suorituskykya hyvãn verkkorakenteen lõytâmìsessã tarkastellaan kahdcksan eri oppiinisongelman suhteen. Ongelmista nelj

ii on keinotekoisia (XOR, koodaus ja kaksi funktion approksimoinnin ongelinaa), kolnie on todellisia hahmontun-nistusongelnna PROBENl-ongelmajoukosta Evolutionary design of neural networks

(syoviin. lasityyppien ja sydănsairau-den tunnistus) ja yksi on konkurssien ennustusongelnia yritysten tilinpaatostie-tojen perusteella. Koodausinenet

Evolutionary design of neural networks

elmien suorituskykya mitataan luokitustarkkuu-della hahrnontunnistusongelinissa. sekii kyvyllă lọytăă oleelli.set niuuttujavalinnat keinotekoisissa on

Evolutionary Design of Neural NetworksMarko A. GronroosMaster of Science ThesisComputer ScienceDepartment of Mathematical SciencesUniversity of Turku.

Evolutionary design of neural networks oleellisesti huonoinpi. Muuttujien valinnassa parliaiiiimaksi osoittautui suora koodaus. vaikkakin Xolfi ja Parisin koodausmenetelmă pãăsi melko lahel

le sen tulosta.AbstractThis thesis deals with methods for finding neural network architectures suitable for learning particular problems. We use an ev Evolutionary design of neural networks

olutionary algorithm with four different genetic encoding methods to search for the suitable architectures. We train the neural network weights with a

Evolutionary design of neural networks

separate neural learning algorithm. We use eight different learning problems for benchmarking the encoding methods. Four of the problems are artifici

Evolutionary Design of Neural NetworksMarko A. GronroosMaster of Science ThesisComputer ScienceDepartment of Mathematical SciencesUniversity of Turku.

Evolutionary design of neural networks one is a bankruptcy classification problem studied earlier in one of our projects. Our evaluation criteria are classification accuracy and efficiency

for using only the relevant variables. The classification results are compared also to those for network architectures found by a systematic search.K Evolutionary design of neural networks

eywords: neural networks, evolutionary algorithms, encoding methodsVI

Evolutionary Design of Neural NetworksMarko A. GronroosMaster of Science ThesisComputer ScienceDepartment of Mathematical SciencesUniversity of Turku.

Evolutionary Design of Neural NetworksMarko A. GronroosMaster of Science ThesisComputer ScienceDepartment of Mathematical SciencesUniversity of Turku.

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