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The algorithm development based on the immune search for solving unclear problems to detect the optical flow with minimal cost

Оlga Purchina, Аnna Poluyan, Dmitry Fugarov

2021E3S Web of Conferences15 citationsDOIOpen Access PDF

Abstract

The main aim of the research is the development of effective methods and algorithms based on the hybrid principles functioning of the immune system and evolutionary search to determine a global optimal solution to optimisation problems. Artificial immune algorithms are characterised as diverse ones, extremely reliable and implicitly parallel. The integration of modified evolutionary algorithms and immune algorithms is proposed to be used for the solution of above problem. There is no exact method for the efficient solving unclear optimisation problems within the polynomial time. However, by determining close to optimal solutions within the reasonable time, the hybrid immune algorithm (HIA) is capable to offer multiple solutions, which provide compromise between several goals. Quite few researches have been focused on the optimisation of more than one goal and even fewer used to have distinctly considered diversity of solutions that plays fundamental role in good performance of any evolutionary calculation method.

Topics & Concepts

Evolutionary algorithmArtificial immune systemComputer scienceDevelopment (topology)AlgorithmMathematical optimizationMathematicsArtificial intelligenceMathematical analysisAquatic and Environmental StudiesAtmospheric and Environmental Gas DynamicsOil Spill Detection and Mitigation
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