ABSTRACT
Natural disaster like floods almost happened in every year especially in our country. When it happened, the most important thing to do is rescue all the victim to the most safety places. To safe all of them in critical situation are not very easy. It will take more time because we should confronted with all the barriers during rescue process. So the problem that to be highlight here is we do not have a strategic place or central point for the flood victims which is divided by each area.Generic issue we heard during flood disaster is relief from rescue squad come very late to help the victims. Based on that problem, it is very important to make sure whether our rescue center are in the right and strategic position or not. To increase potential of rescue squad to do their relief mission in quickly. With the nearest and strategic rescue center, it also can give accelerates to the rescue squad to save flood victims. Smart Rescue Placement for the Floods Victim System is the best solution to solve that kind of this problem. K-means clustering is a method that had been chosen. This clustering is a part of the business intelligent method. What this system can do is it will automatically calculate using k-means algorithm and define centroids (the center of mass of a geometric object of uniform density) based on population of each demographic which is always hit by floods. Each demographic will be divide into some of partition, then for that each partition, user can get an output where is the strategic location to be a Smart Rescue Placement. The target user for this system is government, humanity agencies and rescue center developer.
INTRODUCTION
The system that want to develop are very useful to find the strategic place to get help at flooded area. That place are not far anymore. Through this system, user can plot their flooded area itself and the system will automatic generate using special technique or calculation to find strategic area to save themselves.This system are using best clustering algorithm to find the center of area. The algorithm is K-Means Clustering.
OBJECTIVES
These are the objectives that wish accomplish by the system :
To analyze the problem of transferring and helping the victims during flood
disaster. |
To design a system that can identify the strategic position of flooded area to place the rescue center.
|
To develop a system that is able to recommend users for most suitable place to make a rescue center.
|
ALGORITHM
K-Means Clustering
1. Clusters the data into k groups where k is predefined.
2. Select k points at random as cluster centers.
3. Assign objects to their closest cluster center according to the distance function.
4. Calculate the centroid or mean of all objects in each cluster.
5. Repeat steps 2, 3 and 4 until the same points are assigned to each cluster in consecutive rounds.
2. Select k points at random as cluster centers.
3. Assign objects to their closest cluster center according to the distance function.
4. Calculate the centroid or mean of all objects in each cluster.
5. Repeat steps 2, 3 and 4 until the same points are assigned to each cluster in consecutive rounds.
CONCLUSION
This system will support us during flood disaster for finding a safe place. In addition, the problems that occur during flood disaster can be reduced to become better. Finally, to enable users to carry out the process of finding most safety place.
MUHAMMAD HANNAN BIN MOHAMAD SHAH:: Bachelor in Computer Science
(Internet Computing) with Honours :: BTCL14037728 Email : [email protected] Contact number : +601119819747 |
HELP US IMPROVE