Up

A Novel Approach In Software Cost Estimation Combining Swarm Optimization And Clustering Technique


Notice: Undefined variable: link_article in /home/ijtc/public_html/plugins/content/bt_socialshare/bt_socialshare.php on line 818

Notice: Undefined property: stdClass::$image in /home/ijtc/public_html/plugins/content/bt_socialshare/bt_socialshare.php on line 818

Notice: Undefined variable: title in /home/ijtc/public_html/plugins/content/bt_socialshare/bt_socialshare.php on line 818

Notice: Undefined offset: 1 in /home/ijtc/public_html/plugins/content/bt_socialshare/bt_socialshare.php on line 820
 Hot
File Size:
974.20 kB
Volume:
Volume 2, Issue 1 (January, 2016)
Publication No:
IJTC201601001
Author:
Swati Sharma, Rupinder Kaur

Notice: Undefined variable: pdFileDate in /home/ijtc/public_html/components/com_phocadownload/views/file/tmpl/default.php on line 277
Downloads:
42 x

Abstract

Arranging is the most key a portion of task management. It describes the resources that we have to finish the task effectively. Programming cost estimation is a part of arranging. It describes the evaluated cost and time required to finish the project. The input in softeware cost estimation is the extent of the code and cost drivers. The yield is the Effort in wording individual every month. Our proposed model is for tuning parameters of COCOMO model programming cost estimation utilizing Multi Objective (MO) Particle Swarm Optimization (PSO). We will be utilizing grouping techniques to isolate the information things into number of bunches and PSO be utilized then for parameter tuning of every group. The groups and the tuned parameters will be prepared on Neural Network by back proliferation calculation. The results will be analyzed for the change of the previous work.

Keywords

Multiobjective (MO) Particle Swarm Optimization (PSO), integrated development environment (IDE), Constructive cost model (COCOMO), SWARM intelligence.

Tags Associated: