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<!DOCTYPE ArticleSet PUBLIC "-//NLM//DTD PubMed 2.7//EN" "https://dtd.nlm.nih.gov/ncbi/pubmed/in/PubMed.dtd">
<ArticleSet>
<Article>
<Journal>
<PublisherName>OICC Press</PublisherName>
<JournalTitle>International Journal of Mathematical Modelling &amp; Computations</JournalTitle>
<Issn>2228-6233</Issn>
<Volume>4</Volume>
<Issue>3</Issue>
<PubDate PubStatus="epublish">
<Year>2014</Year>
<Month>03</Month>
<Day>21</Day>
</PubDate>
</Journal>
<ArticleTitle>A NEW TWO STEP CLASS OF METHODS WITH MEMORY FOR SOLVING NONLINEAR EQUATIONS WITH HIGH EFFICIENCY INDEX</ArticleTitle>
<VernacularTitle></VernacularTitle>
<FirstPage>277</FirstPage>
<LastPage>288</LastPage>
<ELocationID EIdType="doi"></ELocationID>
<Language>EN</Language>
<AuthorList>
<Author>
<FirstName>Taher</FirstName>
<LastName>Lotfi</LastName>
<Affiliation>Isalmic Azad University- Hamedan Branch

Nonlinear Systems of EquationsInterval Analysis Absolute Value EquationsGeneralized inversesMoore_penrose InversesReproducing kernel methods</Affiliation>
<Identifier Source="ORCID"></Identifier>
</Author>
<Author>
<FirstName>Paria</FirstName>
<LastName>Assari</LastName>
<Affiliation>Isalmic Azad University- Hamedan Branch</Affiliation>
<Identifier Source="ORCID"></Identifier>
</Author>
</AuthorList>
<PublicationType>Journal Article</PublicationType>
<History>
<PubDate PubStatus="received">
<Year>2014</Year>
<Month>03</Month>
<Day>21</Day>
</PubDate>
</History>
<Abstract>It is attempted to extend a two-step without memory method to it's with memory. Then, a new two-step derivative free class of without memory methods, requiring three function evaluations per step, is suggested by using a convenient weight function for solving nonlinear equations. Eventually, we obtain a new class of methods by employing a self-accelerating parameter calculated in each iterative step applying only information from the current and the previous iteration, defining a with memory class.
Although these improvements are achieved without any additional function evaluations, the $ R $-order of convergence are boosted from 4 to 5.24 and 6, respectively, and it is demonstrated that the proposed with memory classes provide a very high computational efficiency.
Numerical examples are put forward and the performances are compared with the basic two-step without memory methods.</Abstract>
</Article>
</ArticleSet>