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- 저자 : Qianmu Li (검색결과 2 건)
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A Survey of Genetic Programming and Its Applications
( Milad Taleby Ahvanooey ),( Qianmu Li ),( Ming Wu ),( Shuo Wang ) 한국인터넷정보학회 2019 KSII Transactions on Internet and Information Syst Vol.13 No.4
Genetic Programming (GP) is an intelligence technique whereby computer programs are encoded as a set of genes which are evolved utilizing a Genetic Algorithm (GA). In other words, the GP employs novel optimization techniques to modify computer programs; imitating the way humans develop programs by progressively re-writing them for solving problems automatically. Trial programs are frequently altered in the search for obtaining superior solutions due to the base is GA. These are evolutionary search techniques inspired by biological evolution such as mutation, reproduction, natural selection, recombination, and survival of the fittest. The power of GAs is being represented by an advancing range of applications; vector processing, quantum computing, VLSI circuit layout, and so on. But one of the most significant uses of GAs is the automatic generation of programs. Technically, the GP solves problems automatically without having to tell the computer specifically how to process it. To meet this requirement, the GP utilizes GAs to a “population” of trial programs, traditionally encoded in memory as tree-structures. Trial programs are estimated using a “fitness function” and the suited solutions picked for re-evaluation and modification such that this sequence is replicated until a “correct” program is generated. GP has represented its power by modifying a simple program for categorizing news stories, executing optical character recognition, medical signal filters, and for target identification, etc. This paper reviews existing literature regarding the GPs and their applications in different scientific fields and aims to provide an easy understanding of various types of GPs for beginners.
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Column Generation Algorithm-Based DTN Routing Strategy in Complex Data Transmission Scenario
Qun Wang,Huanyan Qian,Chenchen Ni,Qianmu Li 보안공학연구지원센터 2015 International Journal of Future Generation Communi Vol.8 No.6
An ideal routing strategy shall be able to help the delay tolerant network (DTN) achieve an optimal transmission performance under the premise of lower energy consumption. However, due to the diverse of the application scenarios, it is hard to use one or more types of routing strategies as a universal optimum solution. There is a need to establish a routing strategy model of the corresponding DTN network for different application scenarios, analyze and evaluate the strategy model in combination of the knowledge of the operational research and statistics. For a complex data transmission DTN network scenario, with the introducing of a line programming method, the big-data and multi-node network transmission problem can be abstracted to a large-scale line programming problem. In this paper, the feasibility of solving the large-scale line programming problem by the column generation algorithm has been analyzed, and a column generation algorithm-based DTN routing strategy under the complex data transmission scenario has been designed. This routing strategy can realize the quantization of the routing strategy performance by the column generation algorithm. Also, by the simulation experiments, the performance of complex data transmission DTN routing strategy under different factors has been analyzed, and the performance of the column generation algorithm-based DTN routing strategy has been compared with the performance of the traditional jet waiting routing strategy
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