﻿<?xml version="1.0" encoding="UTF-8"?>
<!DOCTYPE ArticleSet PUBLIC "-//NLM//DTD PubMed 2.0//EN" "http://www.ncbi.nlm.nih.gov:80/entrez/query/static/PubMed.dtd"[]>
<ArticleSet>
  <Article>
    <Journal>
      <PublisherName>Science and Education Publishing</PublisherName>
      <JournalTitle>American Journal of Industrial Engineering</JournalTitle>
      <Volume>2</Volume>
      <Issue>1</Issue>
      <PubDate PubStatus="epublish">
        <Year>2014</Year>
        <Month>02</Month>
        <Day>13</Day>
      </PubDate>
    </Journal>
    <ArticleTitle>The Use of Artificial Intelligence Methods of Technological Preparation of Engine-Building Production</ArticleTitle>
    <FirstPage>10</FirstPage>
    <LastPage>14</LastPage>
    <Language>EN</Language>
    <AuthorList>
      <Author>
        <FirstName>S.G.</FirstName>
        <LastName>Selivanov</LastName>
      </Author>
      <Author>
        <FirstName>S.N.</FirstName>
        <LastName>Poezjalova</LastName>
        <Affiliation>Department of Aviation Technological Systems, Ufa State Aviation Technical University, Ufa, Russia</Affiliation>
      </Author>
      <Author>
        <FirstName>O.A.</FirstName>
        <LastName>Gavrilova</LastName>
      </Author>
    </AuthorList>
    <ArticleIdList>
      <ArticleId IdType="pii">AJIE2014213</ArticleId>
      <ArticleId IdType="doi">10.12691/ajie-2-1-3</ArticleId>
    </ArticleIdList>
    <History>
      <PubDate PubStatus="received">
        <Year>2013</Year>
        <Month>12</Month>
        <Day>03</Day>
      </PubDate>
      <PubDate PubStatus="revised">
        <Year>2014</Year>
        <Month>01</Month>
        <Day>15</Day>
      </PubDate>
      <PubDate PubStatus="accepted">
        <Year>2014</Year>
        <Month>02</Month>
        <Day>13</Day>
      </PubDate>
    </History>
    <Abstract>The ways of application of artificial intelligence methods for optimization of design, perspective and directive technological processes of engine-building production in this publication are shown. The different choices of optimization of technological processes of engine-building production for providing the competitiveness of new products by means of the Elman and Jordan neural networks with elements of fuzzy logic and genetic algorithm are developed.</Abstract>
  </Article>
</ArticleSet>