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Wooster Science Cafe begins season with climate, mental health talk - Vimarsana News

Wooster Science Cafe begins season with climate, mental health talk

Wooster Science Café begins spring season with “The Science of Climate Change and its Impact on Mental Health."

"Parameter Identification for Memristive Chaotic System Using Modified " by Qi Xiong, Jun Shen et al. - Vimarsana News

"Parameter Identification for Memristive Chaotic System Using Modified " by Qi Xiong, Jun Shen et al.

A memristor is a non-linear element. The chaotic system constructed by it can improve its unpredictability and complexity. Parameter identification of a memristive chaotic system is the primary task to implement chaos control and synchronization. To identify the unknown parameters accurately and quickly, we introduce the Sine Pareto Sparrow Search Algorithm (SPSSA), a modified sparrow search algorithm (SSA). in this research. Firstly, we introduce the Pareto distribution to alter the scroungers’ location in the SSA. Secondly, we use a sine-cosine strategy to improve the producers’ position...

Source: uow.edu.au
Outlook on the Swarm Intelligence Global Market to 2028 - Use of Swarm Robotics in Warehouses Presents Opportunities - Vimarsana News

Outlook on the Swarm Intelligence Global Market to 2028 - Use of Swarm Robotics in Warehouses Presents Opportunities

/PRNewswire/ -- The "Global Swarm Intelligence Market (2022-2027) by Model, Capability, Applications, Geography, Competitive Analysis, and the Impact of...

Swarm Intelligence Market Size, Share, Growth [2022-2029] - Vimarsana News

Swarm Intelligence Market Size, Share, Growth [2022-2029]

Swarm Intelligence market report focuses on the Swarm Intelligence market size, segment size (mainly covering product type, application, and geography),...

"Evolutionary Machine Learning: A Survey" by Akbar Telikani, Amirhessam Tahmassebi et al. - Vimarsana News

"Evolutionary Machine Learning: A Survey" by Akbar Telikani, Amirhessam Tahmassebi et al.

Evolutionary Computation (EC) approaches are inspired by nature and solve optimization problems in a stochastic manner. They can offer a reliable and effective approach to address complex problems in real-world applications. EC algorithms have recently been used to improve the performance of Machine Learning (ML) models and the quality of their results. Evolutionary approaches can be used in all three parts of ML: preprocessing (e.g., feature selection and resampling), learning (e.g., parameter setting, membership functions, and neural network topology), and postprocessing (e.g., rule optimiza...

Source: uow.edu.au