Odor prediction of whiskies based on their molecular composition by Satnam Singh, Doris Schicker, Helen Haug, Tilman Sauerwald, Andreas T. Grasskamp

“…The predictions outperform the inter-panelist agreement and thus demonstrate previously impossible data-driven sensory assessment in mixtures.…”
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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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Utilizing the Novel Developed MLP Techniques to Survey Pile Subsidence via Optimization Algorithms by Augustinus Sieck, Graciela Daniels

“…The Klang Valley Mass Rapid Transit network built in Kuala Lumpur, Malaysia, was chosen to test the piles' settlement and earth properties algorithms. In the prediction process, the R2 value of MLP-AOA and MLP-BBO were obtained at 0.93 and 0.94, respectively. …”
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UNVEILING GENDER FROM INDONESIAN NAMES USING RANDOM FOREST AND LOGISTIC REGRESSION ALGORITHMS by Musthofa Galih Pradana, Pujo Hari Saputro, Dyah Listianing Tyas

“…Both of these algorithms can predict classes with perfect accuracy in 6 experimental data, then the results of 526 experimental data resulted in a final accuracy of 0.94 for logistic regression and 0.93 for random forest. …”
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Energy Optimization in Ultrasound Tomography Through Sensor Reduction Supported by Machine Learning Algorithms by Bartłomiej Baran, Tomasz Rymarczyk, Dariusz Majerek, Piotr Szyszka, Dariusz Wójcik, Tomasz Cieplak, Marcin Gąsior, Marcin Marczuk, Edmund Wąsik, Konrad Gauda

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Evaluating the RMR correlation with the rock mass wave velocity using the meta-heuristics algorithms by Pouya Koureh Davoodi, Farnusch Hajizadeh, Mohammad Rezaei

“…Results indicated that all suggested models provide high accuracy in predicting RMR. However, the hybrid TRR-GA model emerging as the best model in predicting RMR based on the Vp and Vs. …”
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Thermal Runaway Warning of Lithium Battery Based on Electronic Nose and Machine Learning Algorithms by Zilong Pu, Miaomiao Yang, Mingzhi Jiao, Duan Zhao, Yu Huo, Zhi Wang

“…Characteristic gas detection can be an efficient way to predict the degree of thermal runaway of a lithium battery. …”
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Cutting-Edge Stochastic Approach: Efficient Monte Carlo Algorithms with Applications to Sensitivity Analysis by Ivan Dimov, Rayna Georgieva

“…In recent years, researchers have developed advanced algorithms based on the analysis of variance (ANOVA) technique for computing numerical sensitivity indicators. …”
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Using Deep Learning algorithms to detect the success or failure of the Electroconvulsive Therapy (ECT) sessions by usef faghihi, Cyrus kalantarpour

“…So far, to our knowledge, researchers have used multi-parametric magnetic resonance imaging (MRI) techniques combined with statistical methods and/or linear machine learning algorithms to predict patients’ responses to ECT. However, the aforementioned methods are very expensive and time-consuming. …”
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RAM analysis and performance optimization of paper manufacturing plant using nature-inspired algorithms by Ashish Kumar, Sumaira Rasool, Monika Saini

“…To achieve the objective of the proposed study, initially RAMD investigation of each subsystem and a complete power plant is performed and later a stochastic model is developed for performance prediction of the paper plant using nature-inspired algorithms. …”
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Sensitivity and Performance Evaluation of Multiple-Model State Estimation Algorithms for Autonomous Vehicle Functions by Olivér Törő, Tamás Bécsi, Szilárd Aradi, Péter Gáspár

“…The paper examines the suitability of different probabilistic state estimation methods, namely, the Extended Kalman Filter (EKF) and the more general Particle Filter (PF) with the addition of the Interacting Multiple Model (IMM) approach. These algorithms are not capable of predicting motion for long term in road traffic conditions, though their robustness and model classification capability are essential for the overall system. …”
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AUTOMATIC ALGORITHMS OF AGRICULTURAL FIELDS SEGMENTATION ON AERIAL IMAGES FOR REMOTE SENSING AND ENVIRONMENTAL MONITORING by V. A. Kovalev, A. A. Kalinovsky, A. A. Dmitruk, V. A. Liauchuk

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Comparison of Single Exponential Smoothing and Double Moving Average Algorithms to Forecast Beef Production by Tundo, Rachmat Hidayat Insani, Rasiban, Untung Suropati

“…The two algorithms are compared to get the lowest error rate. …”
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Comparative Analysis of KNN and Neavy Bayes Algorithms in Socio-Economic Data Classification in Indonesia by Kiki Buhori, Andrianingsih

“…Based on this problem, the data mining classification method is used in determining the algorithm that is suitable for predicting socio-economic data in Indonesia. …”
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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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Integrating response surface methodology and decision tree algorithms for valorization of cheese whey wastewater by Iremsu Kayan, Nilgun Ayman Oz

“…The machine learning (ML) method validates that RSM predictions are consistent and accurate. The results show that it is possible to combine traditional optimization methods with more advanced ML methods to facilitate the design and the operation of the treatment plants.…”
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Optimizing Renewable Energy Systems Placement Through Advanced Deep Learning and Evolutionary Algorithms by Konstantinos Stergiou, Theodoros Karakasidis

“…Validation against real-world data demonstrates improved prediction accuracy using metrics like root mean squared error (RMSE), mean absolute error (MAE), and mean absolute percentage error (MAPE). …”
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TONE MAPPING METHOD AND IMAGE PROCESSING algorithms under BRIght ambient lightING by A. V. Sycev, A. A. Stepanov, A. G. Smirnov, K. .. Blankenbach

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Comparison of Different Machine Learning Algorithms to Classify Epilepsy Seizure from EEG Signals by Pankaj Kunekar, Chanchal Kumawat, Vaishnavi Lande, Sushant Lokhande, Ram Mandhana, Malhar Kshirsagar

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