Telecommunication Fuzzy Rules for Multi Services Access Nodes Locations using Artificial Bee Colony
What is it about?
This paper presents the capabilities of the Artificial Bee Colony (ABC) to find the fuzzy classifications rules for the telecommunication MSANs locations based on a set of MSAN’s planning barriers.
Why is it important?
This paper presents the capabilities of the Artificial Bee Colony (ABC) to find the fuzzy classifications rules for the telecommunication MSANs locations based on a set of MSAN’s planning barriers. This system starts by preparing the training data set using the benefits of Geographic Information System (GIS) for generating digital maps. The system helps in analyzing spatial data of existing TAN and the barriers which affect planning TAN. Afterwards, the system fuzzifies the MSAN’s planning barriers using Particle Swarm Optimization and Total Entropy as fitness function (PSO-TE). Then, the ABC capabilities, correlation function and confidence rate as a fitness function and the mamdani inference system are utilized to find the appropriate telecommunication fuzzy rules with respect of training data. The system ends by evaluating the generated telecommunication fuzzy rules for MSAN locations via comparing the result of proposed model with a number of classification algorithms found in literature based on the test data set.