首页|Researchers at China University of Petroleum (East China) Report New Data on Int elligent Systems (A Hybrid Algorithm Based On State-adaptive Slime Mold Model an d Fractional-order Ant System for the Travelling Salesman Problem)
Researchers at China University of Petroleum (East China) Report New Data on Int elligent Systems (A Hybrid Algorithm Based On State-adaptive Slime Mold Model an d Fractional-order Ant System for the Travelling Salesman Problem)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews – Current study results on Machine Learning - Intel ligent Systems have been published. Accordingto news reporting out of Qingdao, People’s Republic of China, by NewsRx editors, research stated, “Theant colony optimization (ACO) is one efficient approach for solving the travelling salesman problem (TSP).Here, we propose a hybrid algorithm based on state-adaptive slim e mold model and fractional-order antsystem (SSMFAS) to address the TSP.”
QingdaoPeople’s Republic of ChinaAsiaIntelligent SystemsMachine LearningAlgorithmsChina University of Petrol eum (East China)
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