A novel classification method for balance differences in elite versus expert athletes based on composite multiscale complexity index and ranking forests. by Yuqi Cheng, Dawei Wu, Ying Wu, Youcai Guo, Xinze Cui, Pengquan Zhang, Jie Gao, Yanming Fu, Xin Wang

“…Data were recorded during 30-second trials on both soft and hard support surfaces, with eyes open and closed. …”
Get full text

RATIONAL COMPROMISE SEARCHING METHOD IN ONE CLASS OF MULTIOBJECTIVE OPTIMIZATION PROBLEM IN EVALUATION OF INDETERMINATE OBJECTIVES SET BY THE FUNCTIONS OF ONE VARIABLE by Oleh V. Borovyk, Liudmyla V. Borovyk, Mykola V. Krasovsky

“…Presently, the task of indeterminate objectives evaluation in multiobjective decision making problems, which are reduced to "soft formal characterization" system analysis problems, remains topical. …”
Get full text

Deep Reinforcement Learning: A Chronological Overview and Methods by Juan Terven

“…The survey extends to policy gradient methods, actor–critic architectures, and state-of-the-art algorithms such as proximal policy optimization, soft actor–critic, and emerging model-based approaches. …”
Get full text

Deep and hybrid learning of MRI diagnosis for early detection of the progression stages in Alzheimer’s disease by Ibrahim Abunadi

“…The fourth proposed system diagnoses the data set using ANN and FFNN algorithms based on the hybrid features of ResNet-18 and AlexNet deep learning models and traditional algorithms (LBP, DWT, and GLCM). …”
Get full text

Linear and Nonlinear Multivariate Classification of Iranian Bottled Mineral Waters According to Their Elemental Content Determined by ICP-OES by J.B. Ghasemi, E. Zolfonoun, R. Khosrokhavar

“…The combinations of inductively coupled plasma-optical emission spectrometry (ICP-OES) and three classification algorithms, i.e., partial least squares discriminant analysis (PLS-DA), least squares support vector machine (LS-SVM) and soft independent modeling of class analogies (SIMCA), for discriminating different brands of Iranian bottled mineral waters, were explored. …”
Get full text

Automated Classification of Snow Crab Shell Condition Using Analysis of Field Images by Ibrahim Kadri, Tobie Surette, Sid Ahmed Selouani, Mohsen Ghribi, Ryan LeBlanc

“…Both the Support Vector Machine (SVM) and Multilayer Perceptron (MLP) algorithms were able to reproduce reliable field identifications of five shell conditions (New-soft, New-hard, Intermediate, Old, and Very-old) to an accuracy of 87.6% and 91.7%, respectively. …”
Get full text

Prediction of alkali-silica reaction expansion of concrete using explainable machine learning methods by Yasitha Alahakoon, Hirushan Sajindra, Ashen Krishantha, Janaka Alawatugoda, Imesh U. Ekanayake, Upaka Rathnayake

Get full text

Enhancing piezoelectric control of cracks in thin solid aluminum plates using finite element data and a neural networks approach by Abdul Aabid, Muneer Baig, Mohammad Abdul Malik

“…In addition, artificial neural networks, specifically feedforward neural networks, are employed for optimal SIF prediction, showcasing the ability to integrate soft computing with mechanical engineering challenges. …”
Get full text

A triple pronged approach for ulcerative colitis severity classification using multimodal, meta, and transformer based learning by Md. Nasim Ahmed, Dipta Neogi, Muhammad Rafsan Kabir, Shafin Rahman, Sifat Momen, Nabeel Mohammed

“…We systematically evaluate multiple vision transformer architectures, discovering that a Swin-Base model achieves an accuracy of 90%, while a soft-voting ensemble of diverse ViT backbones boosts performance to 93%. …”
Get full text

Reinforcement Learning-Based Control for Robotic Flexible Element Disassembly by Benjamín Tapia Sal Paz, Gorka Sorrosal, Aitziber Mancisidor, Carlos Calleja, Itziar Cabanes

“…The RL-based approach is evaluated in a simulation using soft actor–critic (SAC), deep deterministic policy gradient (DDPG), and proximal policy optimization (PPO) algorithms, benchmarking their effectiveness in dynamic environments. …”
Get full text

HSDT-TabNet: A Dual-Path Deep Learning Model for Severity Grading of Soybean Frogeye Leaf Spot by Xiaoming Li, Yang Zhou, Yongguang Li, Shiqi Wang, Wenxue Bian, Hongmin Sun

“…However, both conventional field monitoring and machine learning algorithms remain challenged in achieving rapid and accurate detection. …”
Get full text

Evaluation of machine learning techniques for real-time prediction of implanted lower limb mechanics by Chase Maag, Clare K. Fitzpatrick, Paul J. Rullkoetter

“…Several predictive algorithms were explored, including linear regression (LRM), multilayer perceptron (MLP), bi-directional long short-term memory (biLSTM), convolutional neural network (CNN), and transformer-based approaches. …”
Get full text

Demonstration of 4 <inline-formula> <tex-math notation="LaTeX">$\times$</tex-math></inline-formula> 128-Gb/s DFT-S OFDM Signal Transmission over 320-km SMF With IM/DD by Yuanquan Wang, Jianjun Yu, Nan Chi

“…Meanwhile, a combination of advanced digital signal processing (DSP) algorithms, such as pre-equalization, nonlinearity equalization (NE), and decision-directed least mean square (DDLMS), are utilized to mitigate the system distortions and improve system performance. …”
Get full text

Integrating dimension reduction and out-of-sample extension in automated classification of ex vivo human patellar cartilage on phase contrast X-ray computed tomography. by Mahesh B Nagarajan, Paola Coan, Markus B Huber, Paul C Diemoz, Axel Wismüller

“…However, the large size of feature sets extracted in such studies motivates an investigation into algorithmic feature reduction for computing efficient feature representations without compromising their discriminatory power. …”
Get full text

Event recognition technology and short-term rockburst early warning model based on microseismic monitoring and ensemble learning by Zibin Li, Dengpan Qiao, Tianyu Yang, Jun Wang, Hao Chen

“…The rockburst early warning model V-soft achieves peak accuracy and F1 scores of 0.9394 and 0.9173, respectively, demonstrating performance improvements of 6.59–15.68% in accuracy and 14.11–27.21% in F1 score compared to conventional machine learning algorithms and ensemble classifiers. …”
Get full text

Advancements in Retinal Tissue-Mimicking Optical Coherence Tomography Phantoms: Materials, Properties, and Applications by Mukhit Kulmaganbetov

“…Optical coherence tomography (OCT) phantoms are essential tools for calibrating imaging systems, validating diagnostic algorithms, and bridging technological advancements with clinical applications. …”
Get full text

Enhancing revenue generation in Bangladesh’s FinTech sector: a comprehensive analysis of real-time predictive customer behavior modeling in AWS using a hybrid OptiBoost-EnsembleX m... by Avijit Chowdhury

“…The investigation utilized a range of machine learning algorithms, such as random forest, support vector machine (SVM), XGBoost, CatBoost, and LightGBM, to develop models. …”
Get full text

Comprehensive flexible framework for using multi-machine learning methods to optimal dynamic transient stability prediction by considering prediction accuracy and time by Ali Abdalredha, Alireza Sobbouhi, Abolfazl Vahedi

“…This paper presents a flexible framework for using the desired number of ML algorithms and combines the results of them to extract the final optimal transient stability perdition (TSP). …”
Get full text

STRATEGIC MANAGEMENT OF THE ECONOMIC SUSTAINABILITY OF A COMPANY IN THE PARADIGM OF FUZZY LOGIC by Yu. A. Malyukov, A. O. Nedosekin, Z. I. Abdoulaeva

“…It is necessary to develop optimal algorithms for managing economic systems under adverse effects (AE) of a natural, technological, or military nature. …”
Get full text

Predicting fertilizer treating of maize using digital image processing and deep learning approaches by Eshete Derb Emiru, Kassie Bishaw

“…A Convolutional Neural Network (CNN) with VGG16 and VGG19 architectures, along with a SoftMax classifier, was employed to analyze and classify the images into eight distinct categories based on their characteristics. …”
Get full text