Development of a Predictive Model for N-Dealkylation of Amine Contaminants Based on Machine Learning Methods by Shiyang Cheng, Qihang Zhang, Hao Min, Wenhui Jiang, Jueting Liu, Chunsheng Liu, Zehua Wang

“…The SlogP_VSA2 descriptor is the primary factor influencing predictions of N-dealkylation metabolism. Then an ensemble model was generated that uses a consensus strategy to integrate three different algorithms, whose performance is generally better than any single algorithm, with an accuracy rate of 86.2%. …”
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Predictive model using systemic inflammation markers to assess neoadjuvant chemotherapy efficacy in breast cancer by Yulu Sun, Yinan Guan, Hao Yu, Yin Zhang, Jinqiu Tao, Weijie Zhang, Yongzhong Yao

“…Machine learning algorithm analysis identified the random forest (RF) model as the optimal predictive model for pCR.ConclusionThis study demonstrated that lymph node status, NLR, and LMR had significant value in predicting pCR and prognosis in breast cancer patients. …”
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Predicting Forest Evapotranspiration using Remote Sensing and Machine Learning by B. Yadav, L. K. Sharma, B. Bijarniya

“…ML methods, with their ability to handle complex and non-linear relationships to make accurate predictions, can be used to predict ET. In this study, ML algorithms—Random Forest Regression, Support Vector Regressor, Artificial Neural Network, and an ensemble model—are developed to predict forest evapotranspiration. …”
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Prediction of Anemia from Multi-Data Attribute Co-Existence by Talal Qadah, Asmaa Munshi

“…Therefore, this study has reevaluated the claims within the domain of detecting and predicting anemia with the best machine learning algorithm. …”
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Model Predictive Control-Based Energy Management System for Cooperative Optimization of Grid-Connected Microgrids by Sungmin Lim, Jaekyu Lee, Sangyub Lee

“…Second, its robustness against prediction errors was tested by comparing scenarios with and without disturbance prediction. …”
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A two-stage approach to enhancing biofuel supply chains through predictive and optimization analytics by Mehdi Soltani Tehrani, Siamak Noori, Ehsan Dehghani

“…For large-scale scenarios, the study leverages the non-dominated sorting genetic algorithm and multi-objective simulated annealing to generate near-optimal solutions. …”
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Machine learning driven diabetes care using predictive-prescriptive analytics for personalized medication prescription by Manaf Zargoush, Somayeh Ghazalbash, Mahsa Madani Hosseini, Farrokh Alemi, Dan Perri

“…The BN’s unique dual capability serves both predictive and prescriptive functions. Several BN learning algorithms are applied to map the relationships among patient features and decision variables for predicting the outcome. …”
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Explainable Predictive Model for Suicidal Ideation During COVID-19: Social Media Discourse Study by Salah Bouktif, Akib Mohi Ud Din Khanday, Ali Ouni

“…According to Local Interpretable Model-Agnostic Explanations (LIME) and Shapley Additive Explanations (SHAP) XAI algorithms, there was a drift in the features during and before COVID-19. …”
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AN INTELLIGENT POSTOPERATIVE CHRONIC PAIN PREDICTION SYSTEM (I-POCPP) by Elif Kartal, Fatma Önay Koçoğlu, Zeki Özen, İlkim Ecem Emre, Gürcan Güngör, Pervin Sutaş Bozkurt

“…The aim of this study is to predict the POCP status of patients based on perioperative data by developing an “Intelligent POCP Prediction System (I-POCPP)” using the best performing machine learning algorithm. …”
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An improved performance model for artificial intelligence-based diabetes prediction by Ugwu Hillary Okwudili, Oparaku Ogbonna Ukachukwu, V. C. Chijindu, Michael Okechukwu Ezea, Buhari Ishaq

“…By integrating these algorithms into an ensemble framework, this study effectively mitigated their individual limitations, leading to a more accurate and improved reliable prediction model. …”
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Testing the effectiveness of an algorithm for suppressing self-excited vibrations during intensive braking of a vehicle by A. V. Klimov

“…The study of the efficiency and effectiveness of the algorithm was based on field experiments.Results. Based on field experiment method, the efficiency and effectiveness of the algorithm for suppressing self-excited vibrations during deceleration has been determined, which allows for six-fold reduction in maximum amplitudes and 3-3,5-fold reduction in averaged amplitudes, while excluding changes in the moment sign during vehicle intense deceleration.Conclusion. …”
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A New Hybrid Model for Underwater Acoustic Signal Prediction by Guohui Li, Wanni Chang, Hong Yang

“…The prediction of underwater acoustic signal is the basis of underwater acoustic signal processing, which can be applied to underwater target signal noise reduction, detection, and feature extraction. …”
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Text classification using SVD, BERT, and GRU optimized by improved Seagull optimization (ISO) algorithm by Yuanyuan Chen, Nan Sun, Yuanbang Li, Rong Peng, Abbas Habibi

“…This integration of preprocessing, feature extraction, and dimensionality reduction was highly efficacious in overcoming the challenges of text classification. …”
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A fuzzy-predictive current control with real-time hardware for PEM fuel cell systems by Badreddine Kanouni, Abd Essalam Badoud, Saad Mekhilef, Ahmed Elsanabary, Mohit Bajaj, Ievgen Zaitsev

“…Abstract This research study presents the application of the FC-PCC (Fuzzy Logic Predictive Current Control) algorithm in the context of maximum power point tracking (MPPT) for a proton exchange membrane fuel cell system employing a three-level boost converter (TLBC). …”
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Machine learning-based prediction of FeNi nanoparticle magnetization by Federico Williamson, Nadhir Naciff, Carlos Catania, Gonzalo dos Santos, Nicolás Amigo, Eduardo M. Bringa

“…Several machine-learning algorithms, including Random Forest (RF), Elastic Net, Support Vector Regression (SVR), and Gradient Boosting Regression (CatBoost), were applied to predict the average magnetic moment per atom of these NPs. …”
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New insights into biomarkers and risk stratification to predict hepatocellular cancer by Katrina Li, Brandon Mathew, Ethan Saldanha, Puja Ghosh, Adrian R. Krainer, Srinivasan Dasarathy, Hai Huang, Xiyan Xiang, Lopa Mishra

“…Therefore, there is an urgent need for novel biomarkers that can stratify risk and predict early diagnosis of HCC, which is curable. …”
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Design of an evolutionary model for international trade settlement based on genetic algorithm and fuzzy neural network. by Jiaqing Huang, Yang Liu, Miaomiao Tu, Osama Sohaib

“…The objective is to improve the classification of bank-related risks by integrating the adaptability of fuzzy logic with the global optimization capability of genetic algorithms. The GA is used to fine-tune the structure, membership functions, and parameters of the FNN to improve predictive performance. …”
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Enhanced path planning algorithm via hybrid WOA-PSO for differential wheeled mobile robots by Huda Talib Najm, Nur Syazreen Ahmad, Ahmed Sabah Al-Araji

“…This study introduces an enhanced algorithm for global path planning of Differential Wheeled Mobile Robots (DWMRs) that merges the Whale Optimization Algorithm (WOA) and Particle Swarm Optimization (PSO). …”
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A Gradient-Based Optimization Algorithm for Optimal Control Problems With General Conformable Fractional Derivatives by Essia Ben Alaia, Slim Dhahri, Omar Naifar

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Provide a Solution Based on Teacher and Student Learning Algorithm to Reduce Regression Test Cases by Mahmood Deypir, Amirhossein Mohammadpour

“…Also, the results of teacher-student algorithm were compared with previous approaches of regression test case reduction. …”
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