Titlebook: Cutting Edge Applications of Computational Intelligence Tools and Techniques; Kevin Daimi,Abeer Alsadoon,Luis Coelho Book 2023 The Editor(

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https://doi.org/10.1007/978-1-349-15787-7d hydrogen sulfide emission. Temperature, pH and organic loading rate were found to be the most influential parameters for methane and carbon dioxide production, while pH was replaced by suspended solids the case of hydrogen sulfide. The final random forest machine learning model generated performan

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A Manager’s Primer on e-Networkinguirements. To achieve this, we explore two works with different model designs, research focuses, and potential solutions. In the first work, we try to enhance a usual face recognition model with additional task capability without any additional storage cost. Concretely, we first analyze the two task

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https://doi.org/10.1007/978-3-642-81563-8 box and using data-driven decision-making in their business. Leaders must prioritize ongoing learning for themselves and their employees, which can lead to growth. Digital leaders can achieve business success in the rapidly shifting digital world by incorporating digital transformation, conceptual

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https://doi.org/10.1007/978-3-642-74823-3ism on how rules are generated and how conclusions are drawn from the data fed into the neuro-fuzzy system. One of the challenges for neuro-fuzzy systems is making real-time predictions in the fast changing applications where data can be sparse. It may not be able to automatically detect and react t

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Book 2023iques and applications. It covers many areas and topics of computational intelligence techniques and applications proposed by computational intelligence experts and researchers and furthers the enhancement of the community outreach and engagement component of computational intelligence techniques an

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A Manager’s Primer on e-Networkingned dimensionality reduction is done by computing a graph comprising the co-occurrences of genres in songs. The evaluation results shows that SINATRA achieve an accuracy score above 0.5 given genre space covering more than 2,000 music genres.

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SINATRA: A Music Genre Classifier Based on?Clustering and?Graph Analysisned dimensionality reduction is done by computing a graph comprising the co-occurrences of genres in songs. The evaluation results shows that SINATRA achieve an accuracy score above 0.5 given genre space covering more than 2,000 music genres.