Modeling of Energy Management System for Fully Autonomous Vessels with Hybrid Renewable Energy Systems Using Nonlinear Model Predictive Control via Grey Wolf Optimization Algorithm by Harriet Laryea, Andrea Schiffauerova

“…The EMS combines nonlinear model predictive control (NMPC) with metaheuristic optimizers—Grey Wolf Optimization (GWO) and Genetic Algorithm (GA)—and is benchmarked against a conventional rule-based (RB) method. …”
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Validation of an artificial intelligence-based algorithm for predictive performance and risk stratification of sepsis using real-world data from hospitalised patients: a prospective observational study by Ji-Hyun Kim, Chi-Heum Cho, In-Cheol Kim, Kwang Joon Kim, KyungHyun Lee, Eun Yeong Ha, Sun Hyo Park, Gyeong Im Yu, Byung Eun Ahn, Yeeun Jeong, Joo-Yun Won, Taeyong Sim, Hochan Cho, Ki-Byung Lee

“…VitalCare-SEPsis Score (VC-SEPS) is a deep learning-based algorithm that predicts sepsis and monitors patient conditions based on electronic medical record data. …”
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Big data, dementia prediction and knowledge organization by D. Grant Campbell

“…This paper uses principles of knowledge organization to explore the application of big data algorithms to the task of predicting dementia diagnoses. …”
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Voltage-based prediction technique for efficient MPPT method for SPV systems under non-uniform insolation and partial shading conditions by Haider A. Mohamed-Kazim, Ahmed Hussein Shatti, Ahmed Aldhahab, Ikhlas Abdel-Qader, Sarmad K. Ibrahim, Rusul Noori Saraj

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Malware prediction technique based on program gene by Da XIAO, Bohan LIU, Baojiang CUI, Xiaochen WANG, Suoxing ZHANG

“…With the development of Internet technology,malicious programs have risen explosively.In the face of executable files without source,the current mainstream malware detection uses feature detection based on similarity,with lack of analysis of malicious sources.To resolve this status,the definition of program gene was raised,a generic method of extracting program gene was designed,and a malicious program prediction method was proposed based on program gene.Utilizing machine learning and deep-learning algorithms,the forecasting system has good prediction ability,with the accuracy rate of 99.3% in the deep-learning model,which validates the role of program gene theory in the field of malicious program analysis.…”
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Early Detection of Congenital Heart Diseases among Infants Using Artificial Neural Network Algorithm by Lucy Ifeyinwa Ezigbo, Anthony Kwubeghari, Francis Okoye

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Annotation-free prediction of microbial dioxygen utilization by Avi I. Flamholz, Joshua E. Goldford, Philippa A. Richter, Elin M. Larsson, Adrian Jinich, Woodward W. Fischer, Dianne K. Newman

“…As an example of this broader principle, we developed algorithms that accurately predict microbial dioxygen utilization directly from genome sequences without annotating genes, e.g., by considering only the amino acids in protein sequences. …”
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Real-Time Football Match Prediction Platform by An Zhongqi

“…Future work will focus on enhancing model algorithms and incorporating more complex data sources, such as social media sentiment analysis, to further improve prediction accuracy.…”
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CNN-based Gender Prediction in Uncontrolled Environments by Kazım Yıldız, Engin Güneş, Anil Bas

“…In this study, Convolutional Neural Networks (CNN), one of the deep learning algorithms, was used. The model created with this algorithm was trained with facial images and gender prediction was made. …”
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Power Load Prediction Based on Fractal Theory by Liang Jian-Kai, Carlo Cattani, Song Wan-Qing

“…The attractor is obtained using an improved deterministic algorithm based on the fractal interpolation function, a day’s load is predicted by three days’ historical loads, the maximum relative error is within 3.7%, and the average relative error is within 1.6%. …”
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Learning from the machine: is diabetes in adults predicted by lifestyle variables? A retrospective predictive modelling study of NHANES 2007–2018 by Efrain Riveros Perez, Bibiana Avella-Molano

“…The performance of five machine learning algorithms (logistic regression, support vector machine, random forest, XGBoost and CatBoost) was evaluated using accuracy, sensitivity, specificity, positive predictive value, negative predictive value, and the area under the receiver operating characteristic curve (AUC). …”
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Research on short-term precipitation forecasting method based on CEEMDAN-GRU algorithm by Hua Xu, Zongkai Guo, Yu Cao, Xu Cheng, Qiong Zhang, Dan Chen

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Machine Learning Approaches for Software Defect Prediction by Hijab Zehra Zaidi, Ubaid Ullah, Muddassira Arshad, Hanan Aljuaid, Muhammad Arslan Rauf, Nadeem Sarwar, Rimsha Sajid

“…The paper reviews the use of machine learning algorithms in software defect prediction framework’s bug prediction while assessing their performance across multiple environments. …”
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Data Mining Classification Techniques for Diabetes Prediction by Hindreen Rashid Abdulqadir, Adnan Mohsin Abdulazeez, Dilovan Assad Zebari

“…Many analyses include multiple Machine Learning algorithms for various disease assessments and predictions to improve overall issues. …”
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Photovoltaic Generation Prediction of CCIPCA Combined with LSTM by E. Zhu, D. Pi

“…In order to remedy problems encompassing large-scale data being collected by photovoltaic (PV) stations, multiple dimensions of power prediction mode input, noise, slow model convergence speed, and poor precision, a power prediction model that combines the Candid Covariance-free Incremental Principal Component Analysis (CCIPCA) with Long Short-Term Memory (LSTM) network was proposed in this study. …”
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Odor prediction of whiskies based on their molecular composition by Satnam Singh, Doris Schicker, Helen Haug, Tilman Sauerwald, Andreas T. Grasskamp

“…Due to chemical interactions of these compounds in the olfactory system, assessing or even predicting the olfactory quality of such mixtures is a difficult task, not only for statistical models, but even for trained assessors. …”
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Advances and challenges in neoantigen prediction for cancer immunotherapy by Yi Zhang, Ting-Ting Chen, Xiong Li, Ai-Lin Lan, Peng-Fei Ji, Ya-Juan Zhu, Xue-Yao Ma

“…Future advancements will focus on dynamic tumor microenvironment monitoring, multi-omics integration, improved computational models and algorithms to refine neoantigen prediction, and developing optimized personalized vaccines.…”
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Prediction of cardiovascular diseases based on GBDT+LR by Zengxiao Chi, Li Liu, Liqin Yi, Lin Shi

“…The cardiovascular disease prediction model using the GBDT+LR algorithm has the best prediction performance. …”
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Prediction of Corona-Virus Using Deep Learning by Laith Al-Ali

“…Thus, this research provides an important indicator for the possible prediction of COVID-19 infection. …”
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PREDICTION OF THE USE OF REFRIGERANTS IN LOW-TEMPERATURE EQUIPMENT by J. V. Tatarenko, V. M. Mizin, N. O. Rachkovskiy

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