Automatic Morpheme Segmentation for Russian: Can an Algorithm Re-place Experts? by Дмитрий Алексеевич Морозов, Тимур Александрович Гарипов, Ольга Николаевна Ляшевская, Светлана Олеговна Савчук, Борис Леонидович Иомдин, Анна Валерьевна Глазкова

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Research on SBMPC Algorithm for Path Planning of Rescue and Detection Robot by Lin-Lin Wang, Li-Xin Pan

“…Sampling-Based Model Predictive Control (SBMPC) algorithm is proposed basing on the construction of cost function and predictive kinematics model. …”
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Sampling error‐based model‐free predictive current control of open‐end winding induction motor with simplified vector selection by Mahdi S. Mousavi, S. Alireza Davari, Freddy Flores‐Bahamonde, Cristian Garcia, Jose Rodriguez

“…In the proposed scheme, the prediction algorithm is iterated 14 times instead of 27 iterations of the conventional predictive algorithm. …”
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Designing Predictive Tools for Personalized Functionalities in Knitted Performance Wear by Martijn ten Bhömer, Hai-Ning Liang, Difeng Yu, Yuanjin Liu, Yifan Zhang, Eva de Laat, Carola Leegwater

“…(2) How to design interactions and interfaces that use intelligent predictive algorithms to stimulate creativity during the fashion design process? …”
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A predictive analytics framework for opportunity sensing in stock market by Shruti Mittal, C.K. Nagpal

“… Large volume, random fluctuations and distractive patterns in raw price data lead to overfitting in stock price prediction. Thus research papers in this area suffer from multiple limitations: Very short prediction period from one day to one week, consideration of few stocks only instead of whole of stock market spectrum, exploration of more suitable machine learning algorithms. …”
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Balancing Predictive Performance and Interpretability in Machine Learning: A Scoring System and an Empirical Study in Traffic Prediction by Fabian Obster, Monica I. Ciolacu, Andreas Humpe

“…This paper investigates the empirical relationship between predictive performance, often called predictive power, and interpretability of various Machine Learning algorithms, focusing on bicycle traffic data from four cities. …”
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Generative and predictive neural networks for the design of functional RNA molecules by Aidan T. Riley, James M. Robson, Aiganysh Ulanova, Alexander A. Green

“…SANDSTORM and GARDN thus represent powerful new predictive and generative tools for the development of RNA molecules with improved function.…”
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Robust Predictive Maintenance for Robotics via Unsupervised Transfer Learning by Arash Golibagh Mahyari, Thomas locher

“…In this paper, we propose a novel solution based on transfer learning which addresses a well-known challenge in predictive maintenance algorithms by passing the knowledge of the trained model from one task to another in order to prevent the need for retraining and to eliminate such false alarms. …”
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Power Loss Reduction and Reliability Improvement of Radial Distribution Systems Using Optimal Capacitor Placement Technique by Mohanad Muneer Yaqoob, Ali Nasser Hussain, Wathiq Rafa Abed, Daniel Augusto Pereira

“…The proposed technique has been tested with 69 typical IEEE RDS buses using the Improved Binary Particle Swarm Optimization (IBPSO) algorithm. The proposed algorithm shows a high ability to find the best location and size of injected capacitors inside the RDS to implement a single-objective function for minimization of Active Power Loss (APL). …”
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Composite fault feature extraction for gears based on MCKD-EWT adaptive wavelet threshold noise reduction by Yanchang LV, Jingyue Wang, Chengqiang Zhang, Jianming Ding

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Hydrofoil Installation and Performance Optimisation for Ship Resistance Reduction in Trimaran Through Particle Swarm Optimisation Method by Ghadimi Aliakbar, Ghadimi Parviz, Ghassemi Hassan

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Generative Adversarial Network-Based Distortion Reduction Adapted to Peak Signal-to-Noise Ratio Parameters in VVC by Weihao Deng, Zhenglong Yang

“…Additionally, the LPIPS value reaches 0.2639, representing a 10.42% reduction, and effectively addresses the issue of image quality deterioration during transmission.…”
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Optimization of air conditioning mechanical ventilation using simulated annealing for enhanced energy efficiency and cost reduction by Enio Pedone Bandarra Filho, Gleyzer Martins, Muhammad Bilal Riaz, Sardar Muhammad Bilal, Oscar Saul Hernandez Mendonza

“…The methodology integrates principles of fluid mechanics with computational modeling to perform mass and pressure balances, combined with a simulated annealing algorithm for system optimization. The results demonstrate notable reductions in energy consumption, installation costs, and root mean square deviation of airflow rates from design targets. …”
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Gaussian Pulse-Based Two-Threshold Parallel Scaling Tone Reservation for PAPR Reduction of OFDM Signals by Lei Guan, Anding Zhu

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PCA-counseled k-means and k-medoids with dimension reduction for improved in determining optimal aid clustering by Achmad Jauhari, Ika Oktavia Suzanti, Devie Rosa Anamisa, Fadhila Tangguh Admojo

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Preamble Allocation and Access Delay Reduction for Improved Massive Random Access in 5G Beamforming Networks by Gangwoo Lee, Jaewook Jung, Jong-Moon Chung

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Analysis and Implementation of the Crowbar Clamping Circuit for Surge Voltage Reduction in the DC Solid-State Circuit Breaker by Phanit Sok, Sung-Geun Song, Feel-Soon Kang

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Carbon Emission Reduction in Traffic Control: A Signal Timing Optimization Method Based on Rainbow DQN by Juan Lv, Zhaowei Wang, Jianxiao Ma

“…A comparison with DQN and D3QN models further demonstrates the superiority of the proposed model, achieving a 15% reduction in average waiting time and a 6.5% reduction in CO₂ emissions. …”
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Neural Dynamics during Resting State: A Functional Magnetic Resonance Imaging Exploration with Reduction and Visualization by Wei Li, Miao Wang, Wen Wen, Yue Huang, Xi Chen, Wenliang Fan, The Alzheimer's Disease Neuroimaging Initiative

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Self-supervised predictive learning accounts for cortical layer-specificity by Kevin Kermani Nejad, Paul Anastasiades, Loreen Hertäg, Rui Ponte Costa

“…Inspired by self-supervised learning algorithms, we propose a computational theory in which layer 2/3 (L2/3) integrates past sensory input, relayed via layer 4, with top-down context to predict incoming sensory stimuli. …”
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