Optimal selection of the nutritive value by Tomas Petkus, Gintautas Dzemyda

“…The metodology includes a formal problem statement, interactive selection of parameters of the optimized function and application of the algorithms of non-linear programming. The method enables us to get the optimal values of the objective function argument with the best parameters of the function, according to the planners. …”
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δ-Cut Decision-Theoretic Rough Set Approach: Model and Attribute Reductions by Hengrong Ju, Huili Dou, Yong Qi, Hualong Yu, Dongjun Yu, Jingyu Yang

“…Furthermore, with respect to criterions of decision-monotonicity and cost decreasing, two different algorithms are designed to compute reducts, respectively. …”
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Image Dehazing Based on Improved Color Channel Transfer and Multiexposure Fusion by Shaojin Ma, Weiguo Pan, Hongzhe Liu, Songyin Dai, Bingxin Xu, Cheng Xu, Xuewei Li, Huaiguang Guan

“…In recent years, more and more algorithms have been applied to image dehazing and achieved good results. …”
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Prediction of case types from non-searchable pdf documents in arabic: Comparison of machine learning and deep learning with image processing by El Arrasse Mouad, Khourdifi Youness, Mounir Soufyane, El Alami Alae

“…To achieve this, we utilized image processing, text cleaning techniques, and machine learning algorithms.We carried out a comparative study using both machine learning and deep learning techniques. …”
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Load recognition method based on convolutional neural network and attention mechanism by ZHAO Yitao, LI Zhao, LIU Xinglong, LUO Zhao, WANG Gang, SHEN Xin

“…Aiming at the problems of poor recognition performance of traditional algorithms and difficulty in adapting to the current complex electricity environment, a NILM load recognition method integrating convolutional neural network (CNN)-self-attention mechanism is proposed from the optimization idea of enhancing the feature extraction performance of classification algorithms. …”
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Comparative analysis of Q-learning, SARSA, and deep Q-network for microgrid energy management by Sreyas Ramesh, Sukanth B N, Sri Jaswanth Sathyavarapu, Vishwash Sharma, Nippun Kumaar A. A., Manju Khanna

“…This research presents a novel application of Reinforcement Learning (RL) algorithms—specifically Q-Learning, SARSA, and Deep Q-Network (DQN)—for optimal energy management in microgrids. …”
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A Scalable Ensemble Learning-Based Model for Optimal Placement of Circuit Breaker and Sectionalizer in Power Distribution Systems with the Aim of Reliability Improvement by Mehrdad Ebrahimi, Mohammad Rastegar

“…However, existing mathematical optimization algorithms, such as classic and metaheuristic methods, cannot solve the optimal switch placement problem for large-scale systems. …”
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A human-on-the-loop approach for labelling seismic recordings from landslide site via a multi-class deep-learning based classification model by Jiaxin Jiang, David Murray, Vladimir Stankovic, Lina Stankovic, Clement Hibert, Stella Pytharouli, Jean-Philippe Malet

“…Recent advances in machine learning have introduced algorithms for classifying seismic events associated with landslides, such as earthquakes, rockfalls, and smaller quakes. …”
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Technical and Economic Assessment of Choosing Location of Step-Down Transformer Substation by V. V. Krotenok, Yu. V. Rabskaya

“…The paper considers a problem concerning existing methods for  choosing location of a step-down transformer substation (STS). Algorithms and program segments for calculation of STS location using  existing and CG methods have been developed in the paper. …”
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The role of endothelial cell-related gene COL1A1 in prostate cancer diagnosis and immunotherapy: insights from machine learning and single-cell analysis by Gujun Cong, Jingjing Shao, Feng Xiao, Haixia Zhu, Peipei Kang

“…A diagnostic model was then constructed and validated using a combination of 108 machine learning algorithms. The XGBoost and Random Forest algorithms highlighted the significant role of COL1A1, and we further analyzed the expression and correlation of COL1A1, AR, and EGFR through multiplex immunofluorescence staining. …”
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Bioinformatics insights into mitochondrial and immune gene regulation in Alzheimer's disease by Tian Meng, Yazhou Zhang, Yuan Ye, Hui Li, Yongsheng He

“…Then, using machine learning algorithms, biomarkers with good diagnostic value were selected, and a nomogram was constructed. …”
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Novel approach for noninvasive pelvic floor muscle strength measurement using extracorporeal surface perineal pressure measurement and machine learning modeling by Ui-jae Hwang, Sun-hee Ahn, Hyeon-ju Lee, Yurin Jeon, Myung Jae Jeon

“…Seven ESPP variables were calculated based on ESPP data and intra- and inter-rater reliabilities were assessed. Machine learning algorithms predicted bladder base displacement from ESPP variables. …”
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Feasibility Study on the Use of a Portable NIR Spectrometer and Multivariate Data Analysis to Discriminate and Quantify Adulteration in Fertilizer by Ernest Teye, Charles L. Y. Amuah, Kofi Atiah, Ransford Opoku Darko, Kwadwo Kusi Amoah, Emmanuel Afutu, Rebecca Owusu

“…The overall results indicated that a handheld NIR spectrometer together with appropriate algorithms could be employed for fast and on-site determination of fertilizer integrity.…”
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Machine learning methods of satellite image analysis for mapping geologic landforms in Niger: A comparison of the Aïr mountains, Niger River basin and Djado Plateau by Lemenkova Polina

“…Data were processed by scripts using ML algorithms by modules r.random, r.learn.train, r.learn.predict, i.cluster, and i.maxlik. …”
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Improving Linearity and Symmetry of Synaptic Update Characteristics and Retentivity of Synaptic States of the Domain-Wall Device Through Addition of Edge Notches by Raman Hissariya, Debanjan Bhowmik

“…Compute-in-memory (CIM) crossbar arrays of non-volatile memory (NVM) synapse devices have been considered very attractive for fast and energy-efficient implementation of various neural network (NN) algorithms. High retention time of the synaptic states and high linearity and symmetry of the synaptic weight update characteristics (long-term potentiation (LTP) and long-term depression (LTD)) are major requirements for the NVM synapses in order to obtain high classification accuracy upon implementation of the NN algorithms on the corresponding crossbar arrays. …”
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Personal data privacy protection method based onvertical partitioning by RUAN Huafeng, LI Rui, LUO Kailun

“…This MLVP scheme utilized machine learning algorithms to analyze the correlation between attributes, optimized all correlations, and transformed the vertical partitioning problem into a satisfiability problem, which was then solved using a satisfiability solver. …”
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Computational models based on machine learning and validation for predicting ionic liquids viscosity in mixtures by Bader Huwaimel, Jowaher Alanazi, Muteb Alanazi, Tareq Nafea Alharby, Farhan Alshammari

“…These algorithms include Random Forest (RF), Gradient Boosting (GB), and XGBoost (XGB). …”
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Predicting the Adsorption Efficiency Using Machine Learning Framework on a Carbon-Activated Nanomaterial by Kalapala Prasad, V. Ravi Kumar, R. Suresh Kumar, A. S. Rajesh, Anjani Kumar Rai, Essam A. Al-Ammar, Saikh Mohammad Wabaidur, Amjad Iqbal, Dawit Kefyalew

“…Multicomponent adsorption modelling is difficult because it is challenging to anticipate the relationships among the adsorbates in this artificial intelligence-based modelling, a choice among different algorithms. Utilizing various algorithms, many studies assessed the single and binary adsorption of paracetamol on activated carbon. …”
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An Approach to Integrating Tactical Decision-Making in Industrial Maintenance Balance Scorecards Using Principal Components Analysis and Machine Learning by Néstor Rodríguez-Padial, Marta Marín, Rosario Domingo

“…In the proposed Custom Balance Scorecard design, an exploratory data phase is integrated with another analysis and prediction phase using Principal Component Analysis algorithms and Machine Learning that uses Artificial Neural Network algorithms. …”
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A Prediction Model Optimization Critiques through Centroid Clustering by Reducing the Sample Size, Integrating Statistical and Machine Learning Techniques for Wheat Productivity by Muhammad Islam, Farrukh Shehzad

“…Machine learning algorithms are rapidly deploying and have made manifold breakthroughs in various fields. …”
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