<?xml version="1.0" encoding="UTF-8"?><!DOCTYPE article  PUBLIC "-//NLM//DTD Journal Publishing DTD v3.0 20080202//EN" "http://dtd.nlm.nih.gov/publishing/3.0/journalpublishing3.dtd"><article xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" dtd-version="3.0" xml:lang="en" article-type="research article"><front><journal-meta><journal-id journal-id-type="publisher-id">AM</journal-id><journal-title-group><journal-title>Applied Mathematics</journal-title></journal-title-group><issn pub-type="epub">2152-7385</issn><publisher><publisher-name>Scientific Research Publishing</publisher-name></publisher></journal-meta><article-meta><article-id pub-id-type="doi">10.4236/am.2013.44082</article-id><article-id pub-id-type="publisher-id">AM-29818</article-id><article-categories><subj-group subj-group-type="heading"><subject>Articles</subject></subj-group><subj-group subj-group-type="Discipline-v2"><subject>Physics&amp;Mathematics</subject></subj-group></article-categories><title-group><article-title>
 
 
  A Conventional Approach for the Solution of the Fifth Order Boundary Value Problems Using Sixth Degree Spline Functions
 
</article-title></title-group><contrib-group><contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>archa</surname><given-names>Kalyani</given-names></name><xref ref-type="aff" rid="aff1"><sup>1</sup></xref><xref ref-type="corresp" rid="cor1"><sup>*</sup></xref></contrib><contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Patibanda</surname><given-names>S. Rama Chandra Rao</given-names></name><xref ref-type="aff" rid="aff1"><sup>1</sup></xref></contrib><contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Ammiraju</surname><given-names>Sowbhagya Madhusudhan Rao</given-names></name><xref ref-type="aff" rid="aff2"><sup>2</sup></xref></contrib></contrib-group><aff id="aff2"><addr-line>Varadha Reddy College of Engineering, Warangal, India</addr-line></aff><aff id="aff1"><addr-line>Kakatiya Institute of Technology and Sciences, Warangal, India</addr-line></aff><author-notes><corresp id="cor1">* E-mail:<email>kk.parcha@yahoo.com(AK)</email>;</corresp></author-notes><pub-date pub-type="epub"><day>16</day><month>04</month><year>2013</year></pub-date><volume>04</volume><issue>04</issue><fpage>583</fpage><lpage>588</lpage><history><date date-type="received"><day>December</day>	<month>23,</month>	<year>2012</year></date><date date-type="rev-recd"><day>February</day>	<month>25,</month>	<year>2013</year>	</date><date date-type="accepted"><day>March</day>	<month>2,</month>	<year>2013</year></date></history><permissions><copyright-statement>&#169; Copyright  2014 by authors and Scientific Research Publishing Inc. </copyright-statement><copyright-year>2014</copyright-year><license><license-p>This work is licensed under the Creative Commons Attribution International License (CC BY). http://creativecommons.org/licenses/by/4.0/</license-p></license></permissions><abstract><p>
 
 
     
   In this communication we have used Bickley’s method for the construction of a sixth order spline function and apply it to solve the linear fifth order differential equations of the form y<sup>x</sup>(x)+g (x)y(x)= r(x) where g(x) and r(x) are given functions with the two different problems of different boundary conditions. The method is illustrated by applying it to solve some problems to demonstrate the application of the methods discussed.
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</p></abstract><kwd-group><kwd>Cubic Spline; Tridiagonal; Conventional Approach</kwd></kwd-group></article-meta></front><body><sec id="s1"><title>1. Introduction</title><p>In the recent past, several authors have considered the application of cubic spline functions for the solution of two point boundary value problems. Bickley [<xref ref-type="bibr" rid="scirp.29818-ref1">1</xref>] has considered the use of cubic spline for solving second order two point boundary value problems. The essential feature of his analysis is that it leads to the solution of a set of linear equations whose matrix coefficients are of upper Heisenberg form. Bickley uses a special notation other than the conventional one for the representation of the cubic spline, for a detailed discussion one may refer to E. A. Boquez and J. D. A. Walker [<xref ref-type="bibr" rid="scirp.29818-ref2">2</xref>], M. M. Chawla [<xref ref-type="bibr" rid="scirp.29818-ref3">3</xref>], and P. S. Ramachandra Rao [4-7]. We used Bickley’s method for the construction of a sixth degree spline and apply it to the linear fifth order differential equation with two different problems with different boundary conditions. The work has been illustrated through examples with h = 0.5 and h = 0.25.</p></sec><sec id="s2"><title>2. Cubic Spline-Bickley’s Method</title><p>Suppose the interval <img src="1-7401323\8e3598de-77ac-4a9e-ae64-ea811cf9c10b.jpg" /> is divided in to n subintervals with knots <img src="1-7401323\ae933364-07a3-4d9c-8cdf-b862e2f8a8f1.jpg" /> starting at<img src="1-7401323\4b8eb507-218e-4e27-b3be-990a120b28ba.jpg" />, the function <img src="1-7401323\f3aace8b-8fc7-4c7d-8268-aa6dc0ce8e02.jpg" /> in the interval<img src="1-7401323\b971702a-b414-45cb-a2af-cf33c26371b4.jpg" /> is represented by a cubic spline in the form</p><p>Proceeding in to the next interval<img src="1-7401323\dcb040fd-f6f2-4334-a80a-af94d200ebc0.jpg" />, we add a term<img src="1-7401323\3818104b-e9de-4d87-be7c-87d256dcfc9d.jpg" />; proceeding in to the next interval<img src="1-7401323\6eba02e0-02ab-4c61-af49-e538245730f3.jpg" />, we add another term <img src="1-7401323\c77275f2-61ee-40c5-8496-3a9996fabd62.jpg" /> and so until we reach<img src="1-7401323\812551b6-7143-4b72-b97a-260e8476488d.jpg" />. Thus the function <img src="1-7401323\a45906ba-3e63-420d-8fdf-81497cff9d2e.jpg" /> &#160;is represented in the form for <img src="1-7401323\5d759a08-58c1-4bec-9028-9fdf9191e2c3.jpg" /></p><sec id="s2_1"><title>2.1. The Two-Point Second Order Boundary Value Problem</title><p>First, we consider the linear differential equation</p><p>With the boundary conditions</p><p>The number of coefficients in (1.1) is (n + 3). The satisfaction of the differential equation by the spline function at the (n + 1) nodes gives (n + 1) equations in the &#160;(n + 3) unknowns. Also the end conditions (1.5) give us two more equations in the unknowns. Thus we get (n + 3) equations in (n + 3) unknowns<img src="1-7401323\51aa54f5-a5ed-42cd-9ce4-912689697e45.jpg" />. after determining these unknowns we substitute them in (1.1) and thus we get the cubic spline approximation of<img src="1-7401323\a559c6a3-d0ba-4b15-960d-96e9d7472cac.jpg" />. Putting <img src="1-7401323\06742a5c-6145-4a7d-81f3-4319cab09ff3.jpg" /> in the spline function thus determined, we get the solution at the nodes. The system of equations to be satisfied by the coefficients <img src="1-7401323\efdf8707-afaa-4237-a8a1-f8148d0fbeff.jpg" /> are derived below.</p><p>Substituting (1.1), (1.2), (1.3) in (1.4), at <img src="1-7401323\e0e80b8c-0e10-4d40-90ca-ef4e86ed995a.jpg" /> we get</p><p>where <img src="1-7401323\23bf294b-312f-457c-8818-c313380332f5.jpg" /> and so on. Applying boundary conditions in (1.5), we get</p><disp-formula id="scirp.29818-formula10231"><label>(1.7)</label><graphic position="anchor" xlink:href="1-7401323\e6402995-226e-4d15-beaa-e931d10c10c0.jpg"  xlink:type="simple"/></disp-formula><p>If these equations are taken in the order (1.7), (1.6) with<img src="1-7401323\f2b3e5a7-3975-42a7-bb4d-9049ff8eee78.jpg" />, the matrix of the coefficients of the unknowns <img src="1-7401323\2ae8b0c1-60ca-4964-8747-de0448fc0ff2.jpg" /> is of the Heisenberg form, namely an upper triangle with a single lower sub-diagonal. The forward elimination is then simple, with only one multiplier at each step and the back substitution is correspondingly easy.</p></sec><sec id="s2_2"><title>2.2. Construction of the Sixth Degree Spline</title><p>Suppose the interval <img src="1-7401323\35cf587e-8ce2-414b-8f0a-685c64cad1cd.jpg" /> is divided in to “n” subintervals with knots<img src="1-7401323\27a3235b-108d-4c51-ab87-ff5cf9e0294c.jpg" />. Starting at x<sub>0</sub>, the function <img src="1-7401323\5bb61a57-0083-43d2-8662-4260f30a2338.jpg" /> in the interval <img src="1-7401323\01a3efbf-426c-436b-a8ad-9aa015ac8e57.jpg" /> is represented by a sixth degree spline</p><p><img src="1-7401323\cd8ad787-c584-4225-9dd9-71b518f650f1.jpg" /></p><p>Proceeding in to the next interval<img src="1-7401323\3b0bee6f-3064-411c-a0d5-9f187c6dc54d.jpg" />, we add a term<img src="1-7401323\4f4723a7-ad11-4bea-bcf4-f81775fd0c3b.jpg" />, Proceeding in to the next interval <img src="1-7401323\f1fc10ad-9686-4799-91dc-bb72a2c1ba49.jpg" /> we add another term <img src="1-7401323\f6e7e538-cd78-458c-9415-10a29aa7076a.jpg" /> and so until we reach<img src="1-7401323\354b7fb9-da9c-483a-9a1c-e9b352fea646.jpg" />. Thus the function <img src="1-7401323\cd03211e-26a5-4256-8546-7e4ec080aef8.jpg" /> is represented in the form</p><p>It can be seen that <img src="1-7401323\f9299aba-714e-4308-a082-69576b71c348.jpg" /> and its first five derivatives are continuous across nodes.</p></sec></sec><sec id="s3"><title>3. Fifth Order Boundary Value Problem</title><p>We consider the linear fifth order differential equation</p><p>With the boundary conditions</p><p>We get (n + 6) equations in (n + 6) unknowns<img src="1-7401323\e87f2175-f689-4a9d-aafb-8e23109742a4.jpg" />,<img src="1-7401323\c1f14f1d-50fb-4095-9096-7f6ce5510242.jpg" />. After determining these unknowns we substitute them in (1.8) and thus we get the sixth degree spline approximation of<img src="1-7401323\113b8d60-28dc-422a-9ee0-2b4c8ea91550.jpg" />. Putting <img src="1-7401323\e5c5f23b-e586-44ed-addd-d731956915ea.jpg" /> in the spline function thus determined, we get the solution at the nodes. The system of equations to be satisfied by the coefficients <img src="1-7401323\83ca2e72-20c6-4dc3-8106-ed4b435b9694.jpg" /> <img src="1-7401323\93966c61-f973-49d4-a775-843b00a717a1.jpg" /> are derived below. From (1.8) we get</p><p>using (1.8) &amp; (1.11) in the differential Equation (1.9) at the nodes <img src="1-7401323\85a4105c-2e2c-4933-86c7-ca61666342c0.jpg" /> takes of the form</p><p>To these equations we add those obtained from the boundary conditions (1.10), we get</p><p>If these equations are taken in the order (1.14), (1.16), (1.12) with<img src="1-7401323\65552417-f12e-41ca-8e2b-65ecb73cf0e8.jpg" />, (1.17), (1.15) &amp; (1.13) the matrix of the coefficients of the unknowns, <img src="1-7401323\7d70fcf3-7864-45ad-be3e-1a3a9d04cc88.jpg" />, <img src="1-7401323\b4e3b06c-726f-4e7d-97f2-be2322f7b393.jpg" />is an upper triangular matrix with two lower sub diagonals. The forward elimination is then simple with only two multipliers at each step, and the back substitution is correspondingly easy.</p><sec id="s3_1"><title>3.1. Example 1</title><p>Consider the following fifth order linear boundary value problem</p><p>With the boundary conditions</p><p>by taking equal subintervals with h = 0.5 and h = 0.25 1) Solution with h = 0.5 The sixth order spline <img src="1-7401323\3acafc1d-d664-45ff-9b3c-569fedb97494.jpg" /> which approximates <img src="1-7401323\f1103c81-110f-4559-9a28-ec990a4aa5c0.jpg" /> is given by</p><p>where<img src="1-7401323\4d031278-2621-4d42-8e50-b749d31ac1bb.jpg" />. We have eight unknowns <img src="1-7401323\3e0138b5-44f7-491c-a565-6c8d7555bd89.jpg" /> and eight conditions to be satisfied by these unknowns are<img src="1-7401323\e0a34873-f3b5-4c0c-9d62-a928ff2084dd.jpg" />,</p><p>Since <img src="1-7401323\30e8b1cb-b0dc-4eaa-a148-11c0a129ff20.jpg" /> it follows that <img src="1-7401323\e8657727-d911-44cf-9533-09ac6347e1ad.jpg" /> Equation (3) reduces to the form</p><p>also since <img src="1-7401323\1239c6c4-d5a5-4bb9-82ec-4baf76528fa4.jpg" /> and equations of (5) for i = 0 &amp; 2 reduces to</p><p><img src="1-7401323\13dbea65-da5d-4a7a-8b05-e6742bb2c50d.jpg" />and <img src="1-7401323\4b513649-4c99-497a-acc3-87b03aaf1528.jpg" /></p><p>It follows that we have to determine the five unknowns <img src="1-7401323\ea0442a8-263d-4a2e-a16c-68a43972e025.jpg" /> in Equation (6), subject to the five conditions</p><p>from (6)</p><p>and</p><p>Substituting (6), (8), (9) in (7) we get the system of equations</p><p>Solving these we get</p><p><img src="1-7401323\8737d95e-91bd-4faa-8aaf-4fb0156489b6.jpg" /></p><p>Substituting these values in (6) we get</p><p><img src="1-7401323\55dcd68a-d0c4-424c-8bdc-e60b26d88922.jpg" /></p><p>where h = 0.5 Therefore <img src="1-7401323\1b607fd7-c468-46c6-897f-c439a6aedb80.jpg" /></p><p>The analytical solution of the differential equation (1.18) subject to the conditions is given by</p><p>The exact value of <img src="1-7401323\16868554-f70d-440e-9203-085f05cf1fdc.jpg" /></p><p>It follows that the Absolute error of the numerical value of<img src="1-7401323\148c68d3-f951-46e0-9b92-551c2411893d.jpg" />, computed from the spline approximation is 0.00083433 which is very small.</p><p>The interval [0,1] is divided in to 4 equal subintervals we denote the knots by <img src="1-7401323\89ea9723-2aff-41e4-844b-ccd2a2a51a21.jpg" /> where<img src="1-7401323\89a80339-439c-49b5-a6f9-91240f9f4246.jpg" />,<img src="1-7401323\e4308b88-33a1-47ab-8e2e-e63800d8d7d8.jpg" />.</p><p>The sixth order spline <img src="1-7401323\ec320bdc-0730-48b2-9772-fdf50a3e4d04.jpg" /> which approximate <img src="1-7401323\3ce8f7eb-45b8-4daa-a471-939d96737ca7.jpg" /> is given by</p><p>There are 10 unknowns in <img src="1-7401323\1f987535-6237-4b57-9c2b-5ff254337d88.jpg" /> which are to be determined from 10 conditions</p><p>In view of the conditions <img src="1-7401323\20466e4d-f645-4028-bda6-0fbf0815c975.jpg" />and <img src="1-7401323\8db0c2c7-a2a0-47dc-ad52-262baf55dade.jpg" /> it follows that <img src="1-7401323\0dc259ca-3458-4b56-8373-71689ef22fbc.jpg" /> hence The spline <img src="1-7401323\d1b8c137-4ad4-4add-bb47-19c08898bf11.jpg" /> reduces to the form</p><p>From (14)&#160;</p><p>Substituting (14), (15), (16) in (13) taken in the order,</p><p><img src="1-7401323\1fe1e5ce-b51b-4d5b-969a-439989776b7b.jpg" /></p><p>we get the following system of equations</p><p>From the above system of equations, we notice that the coefficient matrix is an upper triangular matrix with two lower sub diagonals. solving the above equations we get</p><p>However it may be noticed that from the Equation (17) <img src="1-7401323\3e0b2f77-1537-4fce-bca2-f65bc2555718.jpg" />which when substituted in the remaining equations will give us a 6 &#215; 6 system of equations which may be solved. Substituting (18) in (14) we get the spline Approximation <img src="1-7401323\02aca64a-19fc-4844-ad70-eaa0fda27050.jpg" /> of<img src="1-7401323\49edd014-5c1f-45c3-b107-75663f6527b4.jpg" />. The values of<img src="1-7401323\3c0c00bc-3e47-44ea-b413-e745a676cf6b.jpg" />, and The corresponding absolute errors at <img src="1-7401323\27f5061f-4446-4289-9b09-b3e2061e6760.jpg" /> tabulated in <xref ref-type="table" rid="table1">Table 1</xref>.</p><p>The analytical solution of the differential equation (1.18) with the conditions is given by (11.1) is symmetric about the central value. The same aspect is also satisfied by the numerical approximations as is evident from the above table. We found that the approximate values are remarkably accurate.</p></sec><sec id="s3_2"><title>3.2. Example 2</title><p>Consider the following fifth order linear boundary value problem</p><p>Subject to</p><p>1) Solution with <img src="1-7401323\9dde3b64-7021-42cd-a6cd-7a9aad3a0158.jpg" /></p><p>The sixth order spline <img src="1-7401323\5c6c4406-c87c-4fe2-8089-716637f348ca.jpg" /> which approximates <img src="1-7401323\f0cfb6bf-e4f7-4e8e-8e64-a0090a62b189.jpg" /> is given by (3). The equations to be satisfied by the coefficients of the spline function are</p><p>We observe that</p><p><img src="1-7401323\2285377e-e83e-4f86-9a37-86bce128abdc.jpg" /></p><p><xref ref-type="table" rid="table1">Table 1</xref>. Approximate solutions and absolute errors for Example 1 with h = 0.25.</p><p><img src="1-7401323\de9e4a71-d43c-42d1-a279-c81b8a781279.jpg" /></p><p>also since</p><p><img src="1-7401323\25fa764a-60be-480b-937b-6bb12313fddf.jpg" /></p><p>and <img src="1-7401323\c2ab8f2c-0f3f-4586-98ef-6b933cf3141c.jpg" /> the equations of (21) for <img src="1-7401323\d0576a79-6841-4d8e-978c-5fa3c86de0b4.jpg" /> reduces to</p><p><img src="1-7401323\a6ccbb6f-7286-451c-8c0c-07cbace72f74.jpg" /></p><p>It follows that we have to determine the 5 unknowns <img src="1-7401323\e228f5d3-f065-4f10-8eb8-2793d13046ff.jpg" /> <img src="1-7401323\2c07a295-3768-4565-aee3-0b094b95d5bc.jpg" /> in Equation (3), subject to the five conditions</p><p>From (3)</p><disp-formula id="scirp.29818-formula10232"><label>(24)</label><graphic position="anchor" xlink:href="1-7401323\88d06dd6-6255-47d0-b246-195d5f85913b.jpg"  xlink:type="simple"/></disp-formula><p>Substituting (3), (23), (24) in (22)</p><p>We get the system of equations</p><p>Solving these we get</p><p><img src="1-7401323\5c765de4-b9bd-46e6-bd30-a88e4bc81a66.jpg" /></p><p>also we have</p><p><img src="1-7401323\605d8edb-1bad-4719-b2d6-538e5d2a1856.jpg" /></p><p>Substituting all these values in Equation (3) we get the spline approximation for <img src="1-7401323\59eb93b8-d299-4bb9-8a8a-6500e9d56fd3.jpg" /> which is given by</p><p>where <img src="1-7401323\78304571-6b1e-4b8f-9b59-8ea752af0326.jpg" /></p><p>The analytical solution of (19) with the conditions (20) is given by</p><p>The exact value of <img src="1-7401323\f102d7ee-66b3-4f12-b1b0-478dc4b58210.jpg" /> it follows that the absolute error in the numerical approximation <img src="1-7401323\403c3930-3ae6-4992-82e0-786c543bec65.jpg" /> is found to be <img src="1-7401323\21bc65ac-8308-453f-b8a3-77fdba45f7f9.jpg" /> which is very small.</p><p>2) Solution with <img src="1-7401323\0601e87e-bd91-49ec-a4ce-49eeaff0aeb2.jpg" /></p><p>The interval <img src="1-7401323\9ef4a000-77c6-41b7-b710-3c70ebd8bc3b.jpg" /> is divided in to 4 equal subintervals we denote the knots by <img src="1-7401323\3f205f3e-e109-4b12-bce5-449841da50db.jpg" /> where <img src="1-7401323\6bcfbee1-d19d-431c-bc97-8f499f461342.jpg" /></p><p>We assume the spline function <img src="1-7401323\74e4132b-b7aa-4e62-b900-aaae5f19557a.jpg" /> which approximates <img src="1-7401323\950b194c-ae8c-46c9-9b56-cad49a3c2304.jpg" /> in the form is given by (12)</p><p>From (12) we have</p><p>The conditions to be satisfied by <img src="1-7401323\52f017fe-f56a-4b93-a73d-88912d4a5515.jpg" /> are</p><p>for <img src="1-7401323\273c6d93-9cf9-4f3a-83c9-a9be8eda21e1.jpg" /> from (29) we find that</p><p><xref ref-type="table" rid="table2">Table 2</xref>. Approximate solutions and absolute errors for Example 2 with h = 0.5.</p><p><img src="1-7401323\822a6fff-5e93-4506-b356-f560be37642b.jpg" /></p><p><img src="1-7401323\55fb2369-a9f2-4680-b7d9-bff4490af834.jpg" /></p><p>using the remaining conditions of (29) in the order,</p><p><img src="1-7401323\527d6465-1c6b-48cb-aa77-48e8c3db059a.jpg" /></p><p>that is taking the Equations (12), (16), (28) in (29) &amp; by substituting the values of <img src="1-7401323\45cf9b5f-2e66-47ab-9cc9-d4736c738ba6.jpg" /></p><p>We get the following system of equations</p><p>Solving (29) we get</p><p>Also we have</p><p><img src="1-7401323\a737b621-3ca2-4360-a65b-fcfccfecf3c0.jpg" /></p><p>Substituting these values in (12) we get the approximation<img src="1-7401323\dac188d1-e075-4949-8006-b99dcb117d36.jpg" />.</p><p>The values of <img src="1-7401323\d07dfe98-60c7-4f47-aa6d-65407e4a0a6b.jpg" /> and the corresponding absolute errors at <img src="1-7401323\ed774a43-2214-4a1f-9e84-b886895ea797.jpg" /> are mentioned in <xref ref-type="table" rid="table2">Table 2</xref>.</p></sec></sec><sec id="s4"><title>4. Conclusion</title><p>Numerical values obtained by the spline approximation have high accuracy. It has been noticed that the numerical solutions obtained are remarkably accurate and have negligible percentage errors even for values of h as large as 0.5, 1.0.</p></sec><sec id="s5"><title>REFERENCES</title></sec><sec id="s6"><title>NOTES</title></sec></body><back><ref-list><title>References</title><ref id="scirp.29818-ref1"><label>1</label><mixed-citation publication-type="other" xlink:type="simple">W. G. Bickley, “Piecewise Cubic Interpolation and Two Point Boundary Value Problems,” Computer Journal, Vol. 11, No. 2, 1968, pp. 206-208.  
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