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Microcosm algorithm hardware platform realizing method based on FPGA

A technology of world and algorithm, applied in the field of hardware platform implementation of small world optimization algorithm, can solve the problems of complex design of hardware optimization platform and demanding function properties, and achieve the effect of overcoming the problem of deception, low development cost and stable structure

Inactive Publication Date: 2008-05-21
XI AN JIAOTONG UNIV
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AI Technical Summary

Problems solved by technology

[0005] In order to overcome the strict requirements on the function properties of classical optimization methods and the complex and difficult-to-solve local extremum problems existing in other hardware optimization platforms based on ASICs, the purpose of the present invention is to provide a new method based on large-scale Realization method of optimized platform for programming logic devices

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  • Microcosm algorithm hardware platform realizing method based on FPGA
  • Microcosm algorithm hardware platform realizing method based on FPGA
  • Microcosm algorithm hardware platform realizing method based on FPGA

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Embodiment Construction

[0026] The present invention adopts the principle of small-world algorithm to realize optimized operation on the hardware platform constructed by FPGA (Field Programmable Gate Array). The specific scheme is as follows.

[0027] Because the small-world algorithm needs two steps of "individual optimization" and "global optimization", the individual optimization process is completed by three steps of "neighborhood search", "fitness calculation" and "optimum selection", and the global optimization process is completed again Globally select the best for each individual and perform overall scheduling. Therefore, as shown in Figure 1, the small-world algorithm implemented in FPGA needs to build the following two-level structure:

[0028] 1. The first layer completes the individual optimization process, which consists of a random number generator module, a position reorganization module, a fitness calculation module and a comparison module. The random number generator generates a ra...

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Abstract

The invention discloses a field programmable gate array-based small-world algorithm hardware system. Based on the principle of the small-world algorithm, it consists of two levels of individual optimization and global optimization, and is connected by individual information modules in the middle. The individual optimization part is composed of a random number generator, a position reorganization module, a fitness calculation module and a comparison module connected in sequence. Complete the individual neighborhood search, fitness calculation and selection process. The global optimization part is composed of individual fitness comparison module and system scheduling module connected sequentially. The individual fitness comparison module selects the best individual among all individuals, and supplies the system scheduling module to judge whether the termination condition is met, and whether to initiate the next generation search, etc. This method has simple hardware implementation, high parallelism, can effectively overcome the local extremum problem, retain the diversity of the solution space, and overcome the deception problem more effectively to a certain extent, and has faster convergence speed and stability.

Description

technical field [0001] The invention belongs to the application field of artificial intelligence optimization algorithms, and in particular relates to a hardware platform implementation method of small-world optimization algorithms on FPGA. Background technique [0002] In scientific research and engineering practice, it is often necessary to solve various optimization problems, which requires the use of various optimization methods. At present, optimization methods mainly include classical optimization methods and heuristic optimization algorithms. Classical optimization methods mainly include linear programming, gradient method, Newton method, interior point method, etc. Heuristic algorithm is another important branch, including genetic algorithm, artificial neural network algorithm, ant colony algorithm, particle swarm algorithm and simulated annealing algorithm. Because the classical optimization algorithm has more requirements on the nature of the function, it often n...

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Application Information

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IPC IPC(8): G06F17/50G06F17/30G06F7/544
Inventor 杜海峰张进华庄健杨斌陈永森
Owner XI AN JIAOTONG UNIV
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