Titlebook: Artificial Intelligence Methods in Intelligent Algorithms; Proceedings of 8th C Radek Silhavy Conference proceedings 2019 Springer Nature S

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Emergent Imputative Symbols: In One Word). Experiments were designed to demonstrate the importance of the percentile concept in the binarization process. Subsequently, the efficiency of the algorithm is verified through reference instances. The results indicate that the binary Ant Lion Algorithm (BALO) obtains adequate results when evaluated with a combinatorial problem such as the SCP.

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Do Currency Boards Have a Future?,ases, were critically reviewed. The review revealed that VSSLMS is better than LMS in reducing the motion artifact in slow motion and high-speed motion. For future work, the VSSLMS results will be formulated with regression machine learning.

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An Ontology-Based Approach to the Workload Distribution Problem Solving in Fog-Computing Environmenties. So there is a problem to get solutions of an acceptable quality under the restricted time conditions..In this paper an approach based on the optimization problem search space reduction is proposed. An ontological approach is used for this purpose. It allows to reduce the optimization problem search space and the problem solving time thereby.

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Principal Component Analysis and ReliefF Cascaded with Decision Tree for Credit Scoring,r side, using the same combination of feature selection (PCA and ReliefF) but cascaded with SVM classifier, one has obtained an accuracy of only 85.15%. The experimental results confirm the accuracy of the proposed model, and at the same time they show the importance of feature selection and its optimization for credit scoring decision systems.

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Variable Step Size Least Mean Square Optimization for Motion Artifact Reduction: A Review,ases, were critically reviewed. The review revealed that VSSLMS is better than LMS in reducing the motion artifact in slow motion and high-speed motion. For future work, the VSSLMS results will be formulated with regression machine learning.

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