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AITSO: a tool for spatial optimization based on artificial immune systems.

Zhao X, Liu Y, Liu D, Ma X - Comput Intell Neurosci (2015)

Bottom Line: However, user-friendly professional software is still unavailable, which is a great impediment to the popularity of artificial immune systems.As an integrated, flexible, and convenient tool, AITSO contributes to knowledge sharing and practical problem solving.It is therefore believed that it will advance the development and popularity of spatial optimization in geocomputation and spatial analysis.

View Article: PubMed Central - PubMed

Affiliation: School of Resource and Environmental Science, Wuhan University, Wuhan 430079, China.

ABSTRACT
A great challenge facing geocomputation and spatial analysis is spatial optimization, given that it involves various high-dimensional, nonlinear, and complicated relationships. Many efforts have been made with regard to this specific issue, and the strong ability of artificial immune system algorithms has been proven in previous studies. However, user-friendly professional software is still unavailable, which is a great impediment to the popularity of artificial immune systems. This paper describes a free, universal tool, named AITSO, which is capable of solving various optimization problems. It provides a series of standard application programming interfaces (APIs) which can (1) assist researchers in the development of their own problem-specific application plugins to solve practical problems and (2) allow the implementation of some advanced immune operators into the platform to improve the performance of an algorithm. As an integrated, flexible, and convenient tool, AITSO contributes to knowledge sharing and practical problem solving. It is therefore believed that it will advance the development and popularity of spatial optimization in geocomputation and spatial analysis.

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The schema diagram of the primary classes used for developing application plugins.
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fig6: The schema diagram of the primary classes used for developing application plugins.

Mentions: As stated in Section 3.1, developers usually have to redesign the encoding strategy, objective function, constraints, inputs, outputs, and the data structure of genes for each spatial optimization problem. On the other hand, it is advantageous that all the immune operators can be reused, and the development of applications is simple enough. Therefore, two interface/abstract classes were designed to encapsulate all these particular requirements. The architecture of a typical application class and its relationship with the other components in AITSO are illustrated in Figure 5, and the schema diagram of the primary classes is shown in Figure 6.


AITSO: a tool for spatial optimization based on artificial immune systems.

Zhao X, Liu Y, Liu D, Ma X - Comput Intell Neurosci (2015)

The schema diagram of the primary classes used for developing application plugins.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4307625&req=5

fig6: The schema diagram of the primary classes used for developing application plugins.
Mentions: As stated in Section 3.1, developers usually have to redesign the encoding strategy, objective function, constraints, inputs, outputs, and the data structure of genes for each spatial optimization problem. On the other hand, it is advantageous that all the immune operators can be reused, and the development of applications is simple enough. Therefore, two interface/abstract classes were designed to encapsulate all these particular requirements. The architecture of a typical application class and its relationship with the other components in AITSO are illustrated in Figure 5, and the schema diagram of the primary classes is shown in Figure 6.

Bottom Line: However, user-friendly professional software is still unavailable, which is a great impediment to the popularity of artificial immune systems.As an integrated, flexible, and convenient tool, AITSO contributes to knowledge sharing and practical problem solving.It is therefore believed that it will advance the development and popularity of spatial optimization in geocomputation and spatial analysis.

View Article: PubMed Central - PubMed

Affiliation: School of Resource and Environmental Science, Wuhan University, Wuhan 430079, China.

ABSTRACT
A great challenge facing geocomputation and spatial analysis is spatial optimization, given that it involves various high-dimensional, nonlinear, and complicated relationships. Many efforts have been made with regard to this specific issue, and the strong ability of artificial immune system algorithms has been proven in previous studies. However, user-friendly professional software is still unavailable, which is a great impediment to the popularity of artificial immune systems. This paper describes a free, universal tool, named AITSO, which is capable of solving various optimization problems. It provides a series of standard application programming interfaces (APIs) which can (1) assist researchers in the development of their own problem-specific application plugins to solve practical problems and (2) allow the implementation of some advanced immune operators into the platform to improve the performance of an algorithm. As an integrated, flexible, and convenient tool, AITSO contributes to knowledge sharing and practical problem solving. It is therefore believed that it will advance the development and popularity of spatial optimization in geocomputation and spatial analysis.

Show MeSH