A Deep Reinforcement Learning Framework for Adaptive Resiliency Enhancement in Smart Power Grids by Boyu Wang, Aliasghar Baziar, Mohammad Reza Askari

“…To overcome these limitations, we propose a deep reinforcement learning framework based on the Deep Deterministic Policy Gradient (DDPG) algorithm, optimized using the Root Mean Square Propagation (RMSprop) method for stable and efficient training. …”
Get full text

Optimization of Thermal Insulation Parameters for Vertical Perimeters in Buildings with Single-Layer Walls by Walery Jezierski, Paula Szczepaniak, Cezary Leszczyński

“…Using THERM 7.6 software for computational experiments, data were obtained to develop deterministic mathematical models of these relationships. …”
Get full text

An Improved Toeplitz Measurement Matrix for Compressive Sensing by Xu Su, Yin Hongpeng, Chai Yi, Xiong Yushu, Tan Xue

“…In this paper, Toeplitz matrix is employed and optimized as a deterministic measurement matrix. A hardware platform for signal efficient acquisition and reconstruction is built by field programmable gate arrays (FPGA). …”
Get full text

Time-Delayed Feedback Control in the Multiple Attractors Wind-Induced Vibration Energy Harvesting System by Qin Guo, Zhongkui Sun, Ying Zhang, Wei Xu

“…In the deterministic case, the time delay can control efficiently the birhythmic properties; thus one can realize a dividing line in the parameter plane that separates the space into two subspaces of generically distinct nature. …”
Get full text

Artificial intelligence demonstrates potential to enhance orthopaedic imaging across multiple modalities: A systematic review by Umile Giuseppe Longo, Alberto Lalli, Guido Nicodemi, Matteo Giuseppe Pisani, Alessandro De Sire, Pieter D'Hooghe, Ara Nazarian, Jacob F. Oeding, Balint Zsidai, Kristian Samuelsson

“…The aim of this systematic review is to evaluate the effectiveness and reliability of AI applications in orthopaedic imaging, focusing on their impact on diagnostic accuracy, image segmentation and operational efficiency across various imaging modalities. Methods Based on the PRISMA guidelines, a comprehensive literature search of PubMed, Cochrane and Scopus databases was performed, using combinations of keywords and MeSH descriptors ('AI', 'ML', 'deep learning', 'orthopaedic surgery' and 'imaging') from inception to March 2024. …”
Get full text

Sustainable Energy and Exergy Analysis in Offshore Wind Farms Using Machine Learning: A Systematic Review by Hamid Reza Soltani Motlagh, Seyed Behbood Issa-Zadeh, Abdul Hameed Kalifullah, Arife Tugsan Isiacik Colak, Md Redzuan Zoolfakar

“…Offshore wind energy represents a cornerstone in the global transition to low-carbon economies due to its scalability and superior energy yields; however, its complex operational environment, characterized by harsh marine conditions and logistical constraints, necessitates innovative analytical tools. Traditional deterministic methods often fail to capture the dynamic interactions within wind farms, thereby underscoring the need for ML-integrated approaches that enhance precision in energy forecasting, fault detection, and exergy analysis. …”
Get full text

Research on Ship Heave Motion Compensation Control Under Complex Sea State Environment Based on Improved Reinforcement Learning by ZHANG Qin, ZHOU Jingyi, WANG Xingyue, HU Xiong

“…Therefore, this study presents a compensation control method for ship heave under complex sea conditions using an improved reinforcement learning approach.MethodsThis novel method imparts fresh insights into addressing heavy compensation in offshore operations and heralds a new trajectory for the evolution of future offshore operation technologies. …”
Get full text

Degeneralization Algorithm for Generation of Büchi Automata Based on Contented Situation by Laixiang Shan, Jun Qin, Mingshi Chen, Zheng Qin

“…These ideas are implemented in a conversion algorithm used to build a property automaton corresponding to the given LTL formulae. We compare our method to previous work and show that it is more efficient for four sets of random formulae generated by LBTT.…”
Get full text

Bio-inspired cryptography based on proteinoid assemblies. by Panagiotis Mougkogiannis, Essam Ghadafi, Andrew Adamatzky

“…We present an innovative cryptographic technique inspired by the self-assembly processes of proteinoids-thermally stable proteins that form spontaneously under prebiotic conditions. By emulating the deterministic yet complex interactions within proteinoid assemblies, the proposed method generates secure encryption keys and algorithms. …”
Get full text

Decomposing Imaginary-Time Feynman Diagrams Using Separable Basis Functions: Anderson Impurity Model Strong-Coupling Expansion by Jason Kaye, Zhen Huang, Hugo U. R. Strand, Denis Golež

“…We present a deterministic algorithm for the efficient evaluation of imaginary-time diagrams based on the recently introduced discrete Lehmann representation (DLR) of imaginary-time Green’s functions. …”
Get full text

Optimization of distribution networks using quantum annealing for loss reduction and voltage improvement in electrical vehicle parking management by Naser Rashnu, Babak Mozafari, Reza Sharifi

“…The results demonstrate the method’s scalability and effectiveness in handling real-time EV integration while reducing operational costs and supporting voltage stability. …”
Get full text

THE TASK OF MINIMAX ADAPTIVE MANAGEMENT OF INNOVATIVE PROCESSES AT AN ENTERPRISE WITH RISK ASSESSMENT by Vitalina Babenko, Elena Alisejko, Zoya Kochuyeva

“…In view of this, it is suggested to use the deterministic approach based of the methods of the theory of optimal management and dynamic optimization. …”
Get full text

Enhancing Security With Hybrid Active- Passive RIS: A DRL Approach Against Eavesdropping and Jamming by Abdul Wahid, Syed Zain Ul Abideen, Nouman Imtiaz, Mian Muhammad Kamal, Abdullah Alharbi, Amr Tolba, M. A. Al-Khasawneh, Inam Ullah

“…To tackle this, we employ a Deep Reinforcement Learning (DRL) approach using the Deep Deterministic Policy Gradient (DDPG) algorithm, enabling efficient and dynamic optimization. …”
Get full text

Quality of Experience Optimization for AR Service in an MEC Federation System by Huong Mai do, Tuan Phong Tran, Myungsik Yoo

“…We propose an improved deep deterministic policy gradient algorithm for efficient solution exploration. …”
Get full text

Longitudinal Hierarchical Control of Autonomous Vehicle Based on Deep Reinforcement Learning and PID Algorithm by Jialu Ma, Pingping Zhang, Yixian Li, Yuhang Gao, Jiandong Zhao

“…A hierarchical longitudinal control system that integrates deep deterministic policy gradient (DDPG) and proportional–integral–derivative (PID) control algorithms was proposed in this paper to ensure safe and efficient vehicle operation. …”
Get full text

UV-enhanced exfoliated MoS2/PtSe2 heterostructure for ultra-sensitive NO2 detection at room temperature by Mubdiul Islam Rizu, Dalal Fadil, Eduard Llobet

“…Both MoS2 and PtSe2 were synthesized by mechanical exfoliation, and the heterostructure was prepared using deterministic dry transfer method. Comprehensive characterization was performed using optical microscopy, field emission scanning electron microscopy, energy-dispersive X-ray spectroscopy, high resolution transmission electron microscopy, Raman spectroscopy and atomic force microscopy. …”
Get full text

Energy Management of Industrial Energy Systems via Rolling Horizon and Hybrid Optimization: A Real-Plant Application in Germany by Loukas Kyriakidis, Rushit Kansara, Maria Isabel Roldán Serrano

“…To solve the resulting nonlinear and constrained optimization problem at each RHA iteration, we propose a novel hybrid algorithm that combines Bayesian optimization (BO) with the Interior Point OPTimizer (IPOPT). While global deterministic and stochastic optimization methods are frequently used in practice, they often suffer from high computational costs and slow convergence, particularly when applied to large-scale, nonlinear problems with complex constraints. …”
Get full text

Data-Driven Modeling and Simulation in Forestry and Agricultural Product Transportation Management by Small Businesses: A Case Study by Galina Merkurjeva, Vitalijs Bolsakovs, Jurijs Merkurjevs, Andrejs Romanovs, Wouter Faes

“…As new data become available, relationships within the symbolic regression method are discovered more accurately, and simulations are updated accordingly. …”
Get full text

Network control theory uncovers aberrant connectome controllability in trigeminal neuralgia by Tiantian Chu, Juan Peng, Feng Gao, Fei Xiong, Ye Tu

“…This study investigated structural network controllability in TN to elucidate disease-specific alterations in brain network control properties. Methods Eighty-two TN patients and 42 healthy controls (HCs) underwent diffusion tensor imaging. …”
Get full text

Advanced predictive machine and deep learning models for round-ended CFST column by Feng Shen, Ishan Jha, Haytham F. Isleem, Walaa J.K. Almoghayer, Mohammad Khishe, Mohamed Kamel Elshaarawy

“…Comparison with 10 analytical models demonstrates that these traditional methods, though deterministic, struggle to capture the nonlinear interactions inherent in CFST columns, thus yielding lower accuracy and higher variability. …”
Get full text