Refine your search
Collections
Year
A B C D E F G H I J K L M N O P Q R S T U V W X Y Z All
Hisham Omar, Abdullah
- Improving Simplification Performance using FSA : Experimental Result
Abstract Views :170 |
PDF Views:0
Authors
Affiliations
1 Faculty of Computing, Universiti Teknologi Malaysia, Skudai 81310, Johor, MY
2 Faculty of Geoinformation and Real Estate, Universiti Teknologi Malaysia, Skudai 81310 Johor, MY
1 Faculty of Computing, Universiti Teknologi Malaysia, Skudai 81310, Johor, MY
2 Faculty of Geoinformation and Real Estate, Universiti Teknologi Malaysia, Skudai 81310 Johor, MY
Source
Indian Journal of Science and Technology, Vol 9, No 47 (2016), Pagination:Abstract
Simplification is generally eliminating unnecessary characteristics of the object without distortion the original shape of the object. Tolerance value is an important parameter needs to be considered produce a good result of simplification process. The current model of simplification has difficulty to execute simplification process in a short time and unable to determine the best tolerance value for simplification process. Fish Swarm Algorithm (FSA) one of the swarm intelligent algorithms with capability of estimating optimum solution shortly was executed in standard simplification design namely FSASimplification. Besides to improve performance of standard simplification, FSA-Simplification is proposed to determine the most optimum and best quality of tolerance value for simplification process. Therefore, this paper carries out the experimental for both simplification models. The roads in Miri, Sarawak with scale ratio 1:1000 is used for simplification process and be displayed in polyline data type. The result shows FSA-simplification has reduced the computing time by 9% till 12% that leads to a better simplification result compared to standard simplification. This performance indicates FSA-Simplification has given a better quality of simplification result. Besides that, 10 and 20 are the optimum value and best choice of tolerance value for simplification process. This performance indicates FSA-Simplification has given a better quality of simplification result.Keywords
Cartography Generalization, Fish Swarm Algorithm, Map Object, Simplification Process, Tolerance Value.Full Text
- Polygon Simplification Improved with Flower Pollination Algorithm (FPA)
Abstract Views :139 |
PDF Views:0
Authors
Affiliations
1 Department of Computing, Universiti Teknologi Malaysia, Skudai – 81310, Johor, MY
2 Department of Geoinformation and Real Estate, Universiti Teknologi Malaysia, Skudai – 81310, Johor, MY
3 Department of Geoinformation and Real Estate, UniversitiTeknologi Malaysia, Skudai – 81310, Johor, MY
1 Department of Computing, Universiti Teknologi Malaysia, Skudai – 81310, Johor, MY
2 Department of Geoinformation and Real Estate, Universiti Teknologi Malaysia, Skudai – 81310, Johor, MY
3 Department of Geoinformation and Real Estate, UniversitiTeknologi Malaysia, Skudai – 81310, Johor, MY
Source
Indian Journal of Science and Technology, Vol 9, No 48 (2016), Pagination:Abstract
This paper proposed new algorithm, FPA-simplification in order to improve computing time of simplification process. With the attempt to solve this problem, standard simplification algorithm is improved using Flower Pollination Algorithm (FPA). Results from the experiment shows FPA-simplification indeed improve the performance of simplification process in term of computing time from 61% to 75%.Keywords
Cartographic Generalization, Flower Pollination Algorithm, Standard Simplification, Simplification.Full Text