Titlebook: Computational Sciences and Sustainable Technologies; First International Sagaya Aurelia,Chandra J.,Vijaya Padmanabha Conference proceeding

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The Nordic Perspective on Integrating ESG, Support Vector Machine, Decision Tree, Random Forest, Gradient Boost, AdaBoost and Multi Layered Perceptron using Artificial Neural Network on reduced PIMA Indian Diabetes dataset and provided a detailed performance comparison of the algorithms. From this article readers are expected to gain a det

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Methods of Sustainable Investinge proposed Recommendation system using the Health Aware- Krill Herd Optimization (Recsys-HA-KHO). The Resys utilize HA-KHO to provide an efficient recommendation to consume nutritious food based on their Physical Activity (PA). The results obtained from the proposed HA-KHO is compared with other opt

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,Performance Evaluation of?Metaheuristics-Tuned Deep Neural Networks for?HealthCare 4.0,ecting optimal values is the use of metaheuristic algorithms. This work proposes a novel metaheuristic based on the sine cosine algorithm, that builds on the excellent performance of the original. The introduced approach is then tasked with tuning hyperparameter values of a DNN handling medical diag

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Early Prediction of At-Risk Students in Higher Education Institutions Using Adaptive Dwarf Mongoosetinent features collected utilizing the created ADMOA algorithm. Additionally, the effectiveness of the proposed ADMOA_DNFN is examined in light of a number of characteristics, including Root MSE (RMSE), Mean Square Error (MSE), Mean Absolute Error (MAE) and Mean Absoulte Percentage Error (MAPE), it

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,Decomposition Aided Bidirectional Long-Short-Term Memory Optimized by?Hybrid Metaheuristic Applied to the many complexities affecting wind power production data, a signal decomposition technique, variational mode decomposition?(VMD), is applied to help BiLSTM networks accommodate data. Furthermore, to optimize the performance of the network an improved version of the reptile search algorithm, wh

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Interpretable Drug Resistance Prediction for Patients on Anti-Retroviral Therapies (ART),ting them on the previous 70%. Our findings were remarkable: the Decision Tree algorithm outperformed four other comparative algorithms with an f1 scoring mean of 0.9949, greatly improving our ability to identify drug resistance in HIV patients. Our research highlights the potential of combining dat

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