Compatible matching and synergy operation optimization of hydrogen-electric hybrid energy storage system in DC microgrid by Banghua Du, Yanyu Peng, Yang Li, Changjun Xie, Shihao Zhu, Wenchao Zhu, Yang Yang, Li You, Leiqi Zhang, Bo Zhao

“…A multi-objective optimization model is then developed to balance efficiency and lifespan, which is solved by the NSGA-III algorithm. …”
Get full text

Parametric study and optimization of thermal performance and pressure drop in heat sinks with double-layer porous microchannels by Fahimeh Aliyari, Keivan Fallah, Hossein Zolfaghary Azizi, Farhad Hosseinnejad

“…Accordingly, the optimization process was pursued using the multi-objective genetic algorithm to find the optimal parameters that achieve the best thermal performance along with the lowest pressure drop, ensuring a desirable balance between improved thermal performance and reduced pressure drop. …”
Get full text

Urban intersection traffic flow prediction: A physics-guided stepwise framework utilizing spatio-temporal graph neural network algorithms by Yuyan Annie Pan, Fuliang Li, Anran Li, Zhiqiang Niu, Zhen Liu

“…Compared to traditional models such as ARIMA, KNN, and Random Forest, PG-STGNN significantly improves prediction accuracy, achieving MAPE reductions of 19.9 %, 18.6 %, 6.1 %, 20.7 %, 5.0 %, 1.8 %, and 1.1 % against KNN, ARIMA, RF, BP, T-GCN, STGCN, and ST-ED-RMGC, respectively. …”
Get full text

Deceptive Cyber-Resilience in PV Grids: Digital Twin-Assisted Optimization Against Cyber-Physical Attacks by Bo Li, Xin Jin, Tingjie Ba, Tingzhe Pan, En Wang, Zhiming Gu

“…A deep reinforcement learning (DRL)-based defense model optimizes adaptive attack mitigation strategies, ensuring real-time response to evolving cyber threats. …”
Get full text

Quantum-inspired robust optimization for coordinated scheduling of PV-hydrogen microgrids under multi-dimensional uncertainties by Yunxiao Bai, Yu Sui, Xiaoyu Deng, Xiangbing Wang

“…Stress-testing under scenarios such as 48-hour grid failure, signal-based cyberattacks, and 40% PV output curtailment reveals substantial gains: operational costs are reduced by 9.3%, resilience scores improve by over 20% in adverse conditions, and convergence speed increases by 42% relative to classical optimization. …”
Get full text

Bearing fault diagnosis method based on improved compressed sensing and deep multi-kernel extreme learning machine by FU Qiang, HU Dong, YANG Tongliang, LUO Guoqing, TAN Weimin

Get full text

YOLOv10n-Based Defect Detection in Power Insulators: Attention Enhancement and Feature Fusion Optimization by Zhihao Wei, Yan Wei

Get full text

Prediction and reliability analysis of rigid pipeline response in soft soil using improved particle swarm neural network by Laifu Song, Shun Zhang, Jun Wang, Hongtao Fu, Jiayu Cai

“…The simulation results are validated against data from field tests. Second, an improved particle swarm optimization (PSO) algorithm is introduced to optimize the weights and thresholds of a backpropagation neural network (BPNN). …”
Get full text

Bearing fault diagnosis method based on improved compressed sensing and deep multi-kernel extreme learning machine by FU Qiang, HU Dong, YANG Tongliang, LUO Guoqing, TAN Weimin

Get full text

LDC-GAT: A Lyapunov-Stable Graph Attention Network with Dynamic Filtering and Constraint-Aware Optimization by Liping Chen, Hongji Zhu, Shuguang Han

“…To address these issues, we propose LDC-GAT (Lyapunov-Stable Graph Attention Network with Dynamic Filtering and Constraint-Aware Optimization), which jointly optimizes both forward and backward propagation processes. …”
Get full text

An investigation into multi-objective decision-making in fresh cold chain supply chain networks within a dual distribution framework by Junyan Sun, Xing Li, Zefei Chen

“…The algorithm results show that, compared to the traditional NSGA-II and the SA-NSGA-II algorithms with random initialization, the LHS-SA-NSGA-II algorithm demonstrates clear advantages in terms of total cost, carbon emissions, and distribution time, confirming its superiority in optimizing cold chain networks. …”
Get full text

Artificial Intelligence-Based Tools for Process Optimization: Case Study—Bromocresol Green Decolorization with Active Carbon by Gabriel Dan Suditu, Elena Niculina Drăgoi, Alexandra Georgiana Apostică, Andra Maria Mănăilă, Veronica Mădălina Radu, Adrian Cătălin Puițel, Mircea Teodor Nechita

“…In addition, a modified bacterial foraging optimization algorithm was applied as an alternative optimizer in combination with artificial neural networks in order to determine multiple combinations of parameters that can lead to maximum process efficiency. …”
Get full text

Multi-objective optimization of the heating oil circuit inside the calendering roller for the lithium battery pole piece by Shuangqiu Sun, Junqiang Wang, Rongying Zhang, Zhenchao Si, Zhijie Yang

“…Then, the improved NSGA-II algorithm is selected to execute the optimization loop. …”
Get full text

Numerical Optimization of Laser Powder Bed Fusion Process Parameters for High-Precision Manufacturing of Pure Molybdenum by İnayet Burcu Toprak, Nafel Dogdu, Metin Uymaz Salamci

“…Optimization of process parameters is performed using FLOW-3D Release 7 software in conjunction with the HEEDS-SHERPA algorithm. …”
Get full text

Small-Signal Stability Analysis and Parameters Optimization of Virtual Synchronous Generator for Low-Inertia Power System by Alaa Altawallbeh, Abdulrahman Alassi, Nader Meskin, Mohammed A. Al-Hitmi, Ahmed M. Massoud

“…We further propose a hybrid Particle Swarm Optimization (PSO) algorithm with a multi-objective cost function to optimize VSG controller gains. …”
Get full text

Explainable artificial intelligence for sustainable urban water systems engineering by Shofia Saghya Infant, Sundaram Vickram, A Saravanan, C M Mathan Muthu, Devarajan Yuarajan

“…In terms of numbers, XAI applications in water distribution systems have led to up to 20 % savings in energy consumption by optimizing pump schedules based on interpretable machine learning models. …”
Get full text

Smart CAR-T Nanosymbionts: archetypes and proto-models by Juan C. Baena, Juan C. Baena, Juan Sebastián Victoria, Juan Sebastián Victoria, Alejandro Toro-Pedroza, Alejandro Toro-Pedroza, Cristian C. Aragón, Cristian C. Aragón, Joshua Ortiz-Guzman, Joshua Ortiz-Guzman, Joshua Ortiz-Guzman, Juan Esteban Garcia-Robledo, Juan Esteban Garcia-Robledo, David Torres, Lady J. Rios-Serna, Lady J. Rios-Serna, Ludwig Albornoz, Joaquin D. Rosales, Joaquin D. Rosales, Carlos A. Cañas, Carlos A. Cañas, Carlos A. Cañas, Gustavo Adolfo Cruz-Suarez, Gustavo Adolfo Cruz-Suarez, Gustavo Adolfo Cruz-Suarez, Gustavo Adolfo Cruz-Suarez, Felipe Ocampo Osorio, Felipe Ocampo Osorio, Felipe Ocampo Osorio, Tania Fleitas, Ivan Laponogov, Alexandre Loukanov, Alexandre Loukanov, Alexandre Loukanov, Kirill Veselkov, Kirill Veselkov

“…However, despite this promise, translation into clinical settings remains difficult due to regulatory hurdles, scalability issues, and inconsistent reproducibility in human models. At the same time, artificial intelligence (AI), with its powerful algorithms for data analysis and predictive modeling, is transforming how we design, evaluate, and monitor advanced therapies, including the optimization of manufacturing processes. …”
Get full text

Optimization of MXene-based aqueous ionic liquids for solar systems using conventional and AI-based techniques by Mohamed Bechir Ben Hamida, Ali B. M. Ali, Narinderjit Singh Sawaran Singh, Loghman Mostafa

“…Response surface methodology (RSM) is used for predictive modeling, while enhanced hill climbing (EHC), non-dominated sorting genetic algorithm II (NSGA-II), and the multi-objective generalized normal distribution optimizer (MOGNDO) are applied for multi-objective optimization. …”
Get full text

Optimizing radiomics for prostate cancer diagnosis: feature selection strategies, machine learning classifiers, and MRI sequences by Eugenia Mylona, Dimitrios I. Zaridis, Charalampos Ν. Kalantzopoulos, Nikolaos S. Tachos, Daniele Regge, Nikolaos Papanikolaou, Manolis Tsiknakis, Kostas Marias, ProCAncer-I Consortium, Dimitrios I. Fotiadis

“…Key Points Radiomics is a growing field that can still be optimized. Feature selection method impacts radiomics models’ performance more than ML algorithms. …”
Get full text

Parametric Optimization and Assessment of Modern Heritage Shading Screen for a Mid-Rise Building in Arid Climate: Modernizing Traditional Designs by Anwar Ahmad, Lindita Bande, Waleed Ahmed, Kheira Tabet Aoul, Mukesh Jha

“…This research explores how parametric design and optimization based on genetic algorithms (GAs) can improve shading structures to reduce solar radiation and lower cooling energy consumption. …”
Get full text