Titlebook: Evolutionary Artificial Intelligence; Proceedings of ICEAI David Asirvatham,Francisco M. Gonzalez-Longatt,R. Conference proceedings 2024 T

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CRDP: Chronic Renal Disease Prediction and Evaluation with Reduced Prominent Features,reasons, but if certain symptoms are ignored and not treated on time, then it may lead to persistent malfunctioning leading to Chronic Renal Disease (CRD). This condition expedites kidney failure and, in turn, death if not attended appropriately. This work depicts the appropriate, relevant, and corr

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Comparative Examination of Credit Card Fraud Detection Using Machine Learning Algorithms,as a morally reprehensible criminal act. Both individuals and financial organizations experience significant financial losses annually, totaling billions of dollars. This research study intends to utilize machine learning approaches to detect the instances of fraudulent credit card transactions. The

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EEG Features Selection by Using Tasmanian Devil Optimization Algorithm for Stress Detection, on machine learning and deep learning have been presented in the past. However, the performance of the stress detection system is challenging due to inadequate training data, poor feature variability, poor feature selection, and the intricacy of the deep learning framework. This paper provides the

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https://doi.org/10.1007/978-3-531-91443-5 systems, necessitating the timely detection and remediation of security issues. This study addresses security challenges directly by employing an XGBoost model, tuned by a hybridized sine cosine (SCA) metaheuristics algorithm, to identify security vulnerabilities in applied IoT appliances in healthcare 4.0.

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https://doi.org/10.1007/978-1-349-12383-4 to capture long-term relationships in the text because of the dilated convolution design, which is critical for properly recognizing the fake news. The experimental findings show that the proposed strategy is capable of achieving a high degree of accuracy when instances of fake news are identified.

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Civic Market and Sortition Democracyon and prediction of CRD. The CRDP algorithm is implemented, and the results are predominantly used in logistic regression and K-nearest neighbor classification techniques to enhance and improve their prediction accuracy on CRD.

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