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<article  article-type="research-article"        dtd-version="1.4">
            <front>

                <journal-meta>
                                                                <journal-id>yyu jinas</journal-id>
            <journal-title-group>
                                                                                    <journal-title>Yüzüncü Yıl Üniversitesi Fen Bilimleri Enstitüsü Dergisi</journal-title>
            </journal-title-group>
                            <issn pub-type="ppub">1300-5413</issn>
                                        <issn pub-type="epub">2667-467X</issn>
                                                                                            <publisher>
                    <publisher-name>Van Yüzüncü Yıl Üniversitesi</publisher-name>
                </publisher>
                    </journal-meta>
                <article-meta>
                                        <article-id/>
                                                                                                                                                                                            <title-group>
                                                                                                                        <trans-title-group xml:lang="en">
                                    <trans-title>Using Genetic Algorithm Approach for Select Suıtable Model in Mültiple Linear Regression</trans-title>
                                </trans-title-group>
                                                                                                                                                                                                <article-title>Çoklu Doğrusal Regresyonda Uygun Model Seçiminde Genetik Algoritma Yaklaşımının Kullanılması</article-title>
                                                                                                    </title-group>
            
                                                    <contrib-group content-type="authors">
                                                                        <contrib contrib-type="author">
                                                                <name>
                                    <surname>Kaya</surname>
                                    <given-names>Yılmaz</given-names>
                                </name>
                                                                    <aff>VAN YÜZÜNCÜ YIL ÜNİVERSİTESİ</aff>
                                                            </contrib>
                                                    <contrib contrib-type="author">
                                                                <name>
                                    <surname>Yeşilova</surname>
                                    <given-names>Abdullah</given-names>
                                </name>
                                                                    <aff>VAN YÜZÜNCÜ YIL ÜNİVERSİTESİ</aff>
                                                            </contrib>
                                                    <contrib contrib-type="author">
                                                                <name>
                                    <surname>Almalı</surname>
                                    <given-names>M. Nuri</given-names>
                                </name>
                                                                    <aff>VAN YÜZÜNCÜ YIL ÜNİVERSİTESİ</aff>
                                                            </contrib>
                                                                                </contrib-group>
                        
                                        <pub-date pub-type="pub" iso-8601-date="20090801">
                    <day>08</day>
                    <month>01</month>
                    <year>2009</year>
                </pub-date>
                                        <volume>14</volume>
                                        <issue>1</issue>
                                        <fpage>33</fpage>
                                        <lpage>37</lpage>
                        
                        <history>
                                    <date date-type="received" iso-8601-date="20090801">
                        <day>08</day>
                        <month>01</month>
                        <year>2009</year>
                    </date>
                                            </history>
                                        <permissions>
                    <copyright-statement>Copyright © 1995, Yuzuncu Yil University Journal of the Institute of Natural and Applied Sciences</copyright-statement>
                    <copyright-year>1995</copyright-year>
                    <copyright-holder>Yuzuncu Yil University Journal of the Institute of Natural and Applied Sciences</copyright-holder>
                </permissions>
            
                                                                                                <trans-abstract xml:lang="en">
                            <p>The selection of independent variables is an important stage fort he best expression of dependent variable in case of more independent variable in multiple linear regression. A lot of methods have been used for the formation of suitable models. The conventional methods have been insufficient in case of much more variables. The suitable model selection can be made using genetic algorithm instead of conventiona[ methods. In the present stüdy, the best model selection was made using genetic algorithm approach in real data cluster provided fram physical education and sport area. The best independent variables expressing the number of shuttle are determined to be the preexam shuttle number and the period of the preparation for exam.</p></trans-abstract>
                                                                                                                                    <abstract><p>Çoklu doğrusal regresyon modelinde bağımsız değişken sayısının fazla olması durumunda, bağımlı değişkeni en iyi açıklayan bağımsız değişkenlerin seçilmesi oldukça önemli bir aşamadır. Uygun modelin oluşturulmasında birçok yöntem kullanılmaktadır. Değişken sayısının çok fazla olması durumunda klasik yöntemler yetersiz kalabilmektedir. Klasik yöntemler yerine genetik algoritma yöntemi kullanılarak uygun model seçimi yapılabilir. Bu çalışmada, beden eğitim ve spor alanında elde edilen gerçek bir veri kümesinde, genetik algoritma yaklaşımı kullanılarak en iyi model seçimi yapılmıştır. Sınav mekik sayısını en iyi açıklayan bağımsız değişkenlerin sınav öncesi mekik sayısı ile sınava hazırlanma süresinin olduğu saptanmıştır.</p></abstract>
                                                            
            
                                                                                        <kwd-group>
                                                    <kwd>Optimizasyon</kwd>
                                                    <kwd>  Genetik Algoritma</kwd>
                                            </kwd-group>
                            
                                                <kwd-group xml:lang="en">
                                                    <kwd>Optimization</kwd>
                                                    <kwd>  Genetic Algorithm</kwd>
                                            </kwd-group>
                                                                                                                                        </article-meta>
    </front>
    <back>
                            <ref-list>
                                    <ref id="ref1">
                        <label>1</label>
                        <mixed-citation publication-type="journal">Andrew 8., Dan K., 2002. Genetic Algorithm search
for large logistic regression models with
significant variables. 22. int. Conf. information
Technology Interfaces, June 13-16, 2000.
Pula. Croatia</mixed-citation>
                    </ref>
                                    <ref id="ref2">
                        <label>2</label>
                        <mixed-citation publication-type="journal">Cowgill. M.. 1999. A Genetic Algorithm Approch to
Cluster Analysis. An international computer
and mathematics with application. 37: 99-108.
Draper. N. R.. Smith,H., 1989. Applied regression
analysis. John Wiley &amp; Sons, New York.</mixed-citation>
                    </ref>
                                    <ref id="ref3">
                        <label>3</label>
                        <mixed-citation publication-type="journal">Franti. P.. and at all, 1997. Genetic Algorithms for large
scale clustering problems. The Computer
Journal. 40:547-554. .</mixed-citation>
                    </ref>
                                    <ref id="ref4">
                        <label>4</label>
                        <mixed-citation publication-type="journal">Goldberg. D., 1989. Genetic Algorithms in Search,
Optimization and Machine Learning, Addison-
Wesley. Reading MA</mixed-citation>
                    </ref>
                                    <ref id="ref5">
                        <label>5</label>
                        <mixed-citation publication-type="journal">Hsiang H.L.. Chorng-S.O.. 2008. Variable selection in
clustering for marketing segmentation using
genetic algorithms. Expert Systems with
Applications 34: 502—510</mixed-citation>
                    </ref>
                            </ref-list>
                    </back>
    </article>
