Swarming Behaviors of Chicken for Predicting Posts on Facebook Branding Pages

Citation:
Ahmed, K., A. E. Hassanien, E. Ezzat, and Siddhartha Bhattacharyya, "Swarming Behaviors of Chicken for Predicting Posts on Facebook Branding Pages", AMLTA 2018: The International Conference on Advanced Machine Learning Technologies and Applications (AMLTA2018), Cairo, 23 fEB , 2018.

Date Presented:

23 fEB

Abstract:

The rapid increase in social networks data and users present an urgent need for predicting the performance of posted data over these networks. It helps in many industrial aspects such as election, public opinion detection and advertising or branding over social networks. This paper presents a new posts’ prediction system for Facebook’s branding pages concerning the user’s attention and interaction. CSO is utilized to optimize the ANFIS parameters for accurate prediction. CSO-ANFIS is compared with several methods including ANFIS, particle swarm optimization, genetic algorithm and krill herd optimization.

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