Abstract
Due to the increase in criminality, surveillance of society is increasing all over the world. When it comes to urban management just is not right to talk about security aspect. Safety management systems used in the study, the city of surveillance technology and placement methods which are used in the field were investigated. MOBESE, carry out a combination of a lot of function such as transportation, health care, city architecture and emergency response units. These systems are proceeding in parallel with technological advances in the development of urban safety management systems to benefit works. However, planning, infrastructure, installation, management and adapting to changing conditions should be conducted in at the deep. MOBESE is costly, complex and difficult to keep up to date, because application areas of MOBESE are very large cities. In this study, the genetic algorithm solution to the problem of Ankara City in the settlement of the MOBESE and as a result sought out the settlement plan has been optimized. Genetic algorithms demonstrate successful results in classical solutions, time-consuming and difficult to solve problems of this type of hosting of many variables and different criteria. This problem has been resolved by the method used in the solution, and the application has been tested for functionality and reliability. Key words: City security management system, mobile electronic system ıntegration (MOBESE), genetic algorithms, optimization, surveillance.
Highlights
Following the emergence of modern state understanding, monitoring and surveillance activities of cities have been executed by governments and improvements have been supported
Output here represents the best result given by the candidate placement points
Output number will get higher as number of candidate application points in the city increase
Summary
Following the emergence of modern state understanding, monitoring and surveillance activities of cities have been executed by governments and improvements have been supported. In a chromosome formed to represent a possible placement point, genes are coded including following information. The main purpose in the study is determining possible placement points (chromosomes) in the city (population). For this reason, first population containing N chromosomes (20 in application) which will be the possible solution of placement problem is constructed according to the data in the Table 1. New population formed as a result of crossing is as follows From this mutation ratio ( Pm ) is determined as 0.05. To provide the genetic diversity in the newly formed population as a result of crossing, mutation is applied using a certain probability value. For each gene of each individual, 180 random numbers are generated (20(individual)* 9 (gene)=180) in the interval [0-1]. ( 0 ≤ ri ≤ 1, i [1,180])
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