Computational Intelligence in Inflation Forecasting

Open Software Challenge Nepal 2009 was announced somewhere during early 2009. And somehow, computer-half of the CSIDC team (me-Prajwol and Dipesh) decided to participate in it.

Screen blurred, grayscale stars – To talk about CSIDC, it was CSIDC 2006, organized by the IEEE under the theme of “Preserving, Protecting and Enhancing the Environment”. Saurav Ratna Tuladhar and Nilesh Shakya (electronics), and Dipesh Karki and Prajwol Kumar Nakarmi –me (computer) were selected from Pulchowk Campus to participate in it. We had presented our project “iForest – A Monitoring and Management System for Sustainable Forestry”. The certificate of participation of this competition has definitely increased the weight of our CVs – Screen normal, colorscale resumes. he he

Dipesh and I talked in phone, texted in MSN, brainstormed in Eiden Garden and came out with what we christened “Computational Intelligence in Inflation Forecasting” (CIIF). Of course Carlsberg was there to accompany us whenever possible. LOL

Now on August, we both are proud to say that we made to the prestigious TOP 10 among some 80+ projects. My heartfelt congratulations to the guys who made it to the TOP 3 (Y).

Many were expecting our project to do better before the result announcement, and of course, we were hopeful too.  But probably, the fact that our development platform was .NET pulled our legs and we didn’t make till the TOP 3 mark. We had some people asking “how can your software be open when I have to pay for it” LOL LOL a big disgrace to such a question. We tried to explain – they seemed to agree – it was apparent that they didn’t understand :’(. May the true meaning of Openness of the Software come to light to all of us, AMEN.

Let me, now, say some about CIIF. As we know, Inflation is a persistent and significant increase in general price level and it is calculated by averaging the percentage growth rate of the prices of selected sample of commodities. It is one of the most essential macroeconomic indicator as many other economic variables like wage rate, salaries , gross domestic product, interest rate are either directly or indirectly related to change in price. However the inflation can be calculated only in hindsight by comparing present commodity price with the past. As this isn’t much help while formulating the future pricing policy, a forecasting mechanism must be introduced to estimate the future expectation of the inflation rate.

In this light, the software, that attempts to forecast one of the key macroeconomic indicator- ‘Inflation’ using both Neural Network and Genetic Algorithm, was developed. Ladies and Gentlemen, we give to you CIIF . The system consists of two main engines, viz. Artificial Neural Network and Genetic Algorithm. Two flavors of the later are available as Encoding and No Encoding. Statistics are present to measure the fitness of the predicted data. For easy visualization of the output, Graph component is also available.

The input data consisted of inflation rates of USA for last 1143 months, dating back to January of 1914 to March of 2009.  Before beginning the training, the data set is divided into the training set and the validation (Prediction set). First 1043 months data are kept in training set while last 100 are kept in validation set. The application is supple in sense that by simply changing the parameter in the input file the size of validation set as well as training set can be changed. The value of R2 >= 0.5 is acceptable for our system, which implies that at least 50pc of total variation in the data should be explained by the system. Our tests show that the results are over par.

You can follow CIIF under http://collaborate.d2labs.org/projects/ciif/

Cheese and Cheers

Prajwol

Solving the encoding problem while writing to Response

Technology: C# ASP.NET

Level: Expert

Depth: Medium

I, once, had to present a save-as dialogue that would export the content of a GridView into csv and the database would contain Japanese texts. Export was all fine and the file was read fine from Visual Studio itself. However, when the csv was opened from Excel, the Japanese texts came all garbage.

This could have been for my PC doesn’t have Japanese locales and fonts. But the PC with such features also read it same. Here I present a way that solved this problem.

protected void ImageButton_CSV_Click(object sender, ImageClickEventArgs e)

{

…

MyDataSet.MyDataTable exportTable = …

HttpContext context = HttpContext.Current;

context.Response.Clear();

context.Response.ContentEncoding = Encoding.GetEncoding(“shift_JIS”);

for (int i = 1; i < exportTable.Columns.Count; i++)

{

context.Response.Write(exportTable.Columns[i].ColumnName + “,”);

}

context.Response.Write(Environment.NewLine);

string orig_string = “”;

byte[] unicodeBytes = null;

byte[] codBytes = null;

char[] codChars = null;

string codString = “”;

Encoding cod = Encoding.GetEncoding(“shift_JIS”);

Encoding unicode = Encoding.UTF8;

for (int i = 1; i < exportTable.Rows.Count; i++)

{

for (int j = 0; j < exportTable.Columns.Count; j++)

{

orig_string = exportTable[i][j].ToString().Replace(“,”, string.Empty).Replace(“&nbsp;”, string.Empty) + “,”;

unicodeBytes = unicode.GetBytes(orig_string);

codBytes = Encoding.Convert(unicode, cod, unicodeBytes);

codChars = new char[cod.GetCharCount(codBytes, 0, codBytes.Length)];

cod.GetChars(codBytes, 0, codBytes.Length, codChars, 0);

codString = new string(codChars);

context.Response.Write(codString);

}

context.Response.Write(Environment.NewLine);

}

context.Response.ContentType = “text/csv”;

context.Response.AppendHeader(“Content-Disposition”, “attachment; filename=my_file.csv”);

context.Response.End();

}

The codes in the bold do the actual trick. The content encoding and writing to the response in the correct manner is all that needs to be done.

This, however, is not limited to csv exports. You can try with other file formats too.

Cheers and Cheese (Y)