Application Of Improved Artificial Fish Swarm Algorithm In Planning Of Binzhou Wireless Network

The Artificial Fish Swarm Algorithm is a new stochastic optimization algorithm based on group intelligent,essentially is a complex intelligent system.It has a stronger robustness,the fin distributed computing machine-made,easy to union with other methods,and so on.At present to this algorithm research,the application already seeped to many applications domain,and developed from the solution in unidimensional static state optimization questions to the solution in multi-dimensional dynamic combination optimization questions.The artificial Fish Swarm Algorithm has already become in the interdisciplinary studies as an extremely active front research question.Parameters of base station including position,height,transmitting power,number of carrier,dominant frequency,antenna azimuth,type of antenna,antenna downtilt and co-locaiton etc.need to decide in wireless network planning in order to achieve the maximum transmission speed and get a tradeoff between transmission speed and construction cost.This is a typical multi-dimensional combination optimization question.Therefore application of AFSA to wireless network planning can save a lot of labor cost and improve the effect of planning.First,in this paper,the basic idea of AFSA,characteristics and present research situation is discussed briefly,the significance of improve research on AFSA is elaborated.Then several kinds of method to make the improvement to the algorithm are discussed.Next,the principle and flow of TD-SCDMA wireless network planning is discussed and the planning objective of wireless network in Binzhouispresented.Aiming at planning problem,two improvements are made in this paper.One is improvement to initialization of AF,in which co-location is taken into consideration;another is introducing the adaptive search strategy which improve the convergence of AFSA.AF and food concentration function are designed,the framework of AFSA for base station location planning problem is given,and simulation experiments is done to validate the proposed algorithm.Experimental result shows that the proposed solution can obtain higher network coverage rate with lower cost of network construction relatively,and has the advantage of good application value.Finallythe Artificial Fish Swarm Algorithm Provement effect and the next research direction is simplysununarized.Thortough research and attempt to AFSA improvement method has been conducted in present paper,after the improvement,AFSA has a higher search efficiency and the gain optimal solution ability.The research results in this paper have the important reference significance regarding the application of AFSA to solution actual optimazation problem.Further the thorough research also has higher reference value to the next research on AFSA.