Cargando…

Sustainable development of multi-media communication path of broadcasting and hosting with a dynamic environment

To enrich people’s lifestyles at home, the research on the transmission path of new media broadcasting and hosting programs has become a hot topic. The traditional statistical regression model has low prediction accuracy and weak generalization ability on such issues. Therefore, we propose an improv...

Descripción completa

Detalles Bibliográficos
Autor principal: Hu, Qiong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: PeerJ Inc. 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10280439/
https://www.ncbi.nlm.nih.gov/pubmed/37346664
http://dx.doi.org/10.7717/peerj-cs.1397
Descripción
Sumario:To enrich people’s lifestyles at home, the research on the transmission path of new media broadcasting and hosting programs has become a hot topic. The traditional statistical regression model has low prediction accuracy and weak generalization ability on such issues. Therefore, we propose an improved comprehensive path planning algorithm based on an ant colony algorithm to search for the optimal path of the multi-media transmission for broadcasting and hosting programs in a dynamic environment. Firstly, we improve the bidirectional search strategy, optimize the probability transition and extend the early search scope. Then, we utilize the allocation strategy of the wolf to change the updating rules of the pheromone. Finally, we take the shortest process time for listeners to obtain the broadcast program as the optimization goal and construct a comprehensive evaluation model. We also solve the optimal parameters to improve the overall performance of our method for finding out the excellent path of multi-media transmission in a dynamic environment. Experiment results show that our method can achieve the optimal route plans and we can demonstrate that the path planned by the improved ant colony algorithm is more reasonable, which can effectively avoid the optimum local problem and shorten the solution.